Bioconductor 3.23 Release!

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  • Bioconductor 3.23 Released

April 29, 2026

Bioconductor:

We are pleased to announce Bioconductor 3.23, consisting of 2418 software packages, 437 experiment data packages, 928 annotation packages, 28 workflows and 8 books.

There are 94 new software packages, 5 new data experiment packages, no new annotation packages, no new workflows, 2 new books, and many updates and improvements to existing packages.

Bioconductor 3.23 is compatible with R 4.6, and is supported on Linux, 64-bit Windows, Intel 64-bit macOS 11 (Big Sur) or higher, macOS arm64 and Linux arm64. This release will also include updated Bioconductor Docker containers.

Note: Currently Bioconductor does not have active daily windows builders. We will be testing the windows and mac binaries generated through the r-universe system. These updated windows and mac binaries will be available shortly after this release. We appreciate your patience as we make them available.

Thank you to everyone for your contribution to Bioconductor.

Visit Bioconductor BiocViews for details and downloads.

Contents

Getting Started with Bioconductor 3.23

To update to or install Bioconductor 3.23:

  1. Install R 4.6. Bioconductor 3.23 has been designed expressly for this version of R.

  2. Follow the instructions at Installing Bioconductor.

New Software Packages

There are 94 new software packages in this release of Bioconductor.

  • Aerith Visualisation of peptide isotopic peaks and SIP peptide spectra match (PSM). Filtration of high quality PSM. Accurate isotopic abundance calculation of peptide and metabolites. Visualisation of SIP proteomics results.

  • annoLinker Fast annotation of genomic peaks using DNA interaction data by constructing interaction networks with igraph, where peaks overlapping any node in a connected subgraph are annotated with all genes in that subgraph. The annotation evidence could be visualized as either a network graph or a genomic track integrated with gene annotation information.

  • asuri The ASURI (Analysis of SUrvival and patients RIsk prediction based on gene signatures) package discovers marker genes that are related to risk prediction capabilities and to a clinical variable of interest. It uses two main steps, including subsampling glmnet and unicox. The package implements robust functions to discover survival markers related to a clinical phenotype and to predict a risk score, allowing to study the patient’s risk based on the gene signatures. Several plots are provided to visualise the relevance of the genes, the risk score, and patient stratification, as well as a robust version of the Kaplan-Meier curves.

  • atacInferCnv The package prepares input scATAC-seq data and adapts for copy number variance profiling with InferCNV package usage. It has also various paramters to control the analysis (e.g. external normal reference usage, meta-cells, bin size, etc) and custom plot visualizations.

  • BatChef This package implements a variety of methods for batch correction in single-cell RNA sequencing (scRNA-seq) data. It incorporates quantitative metrics (e.g. Wasserstein distance, Adjusted Rand Index) to evaluate their performance. Furthermore, the package assists users in identifying and applying the optimal method for specific datasets.

  • Battlefield Battlefield is a Swiss-army toolkit originally developed to define and extract spatial spots from specific tissue regions—such as front regions, niche borders, invasive margins, and cluster interfaces—using spatial transcriptomics data or clustered tissue maps. It has since been extended to support trajectory selection and layer inspection, and now provides a collection of low-level utilities for spatial transcriptomics analysis. These utilities are primarily intended to be reused within higher-level analytical packages. It is designed to work with sequencing-based platforms such as Visium at several resolutions and Visium HD(binned).

  • betterChromVAR A much faster analytical implementation of chromVAR, with additional features, used to infer TF activity from (bulk or single-cell) ATAC-seq data and motif annotations (or binding probabilities). The package also includes the CVnorm normalization method based on the chromVAR logic.

  • BiocAzul Represents the OpenAPI v2 Azul API as an R object for performing requests. The infrastructure uses the AnVIL and rapiclient packages. Users can connect to either the AnVIL or Human Cell Atlas Data Explorers.

  • BiocBuildReporter This package reads remote parquet files that have processed Bioconductor build report logs. Users may query the tables directly for specific information or use pre-defined helper functions for common queries. The logs processed are from https://bioconductor.org/checkResults/. In the future we will extend this package out to include processing of r-universe logs.

  • BiocMaintainerApp This package allows interactive viewing of package maintainer information. The Bioconductor Package Maintainer Application sends yearly verification emails to accept Bioconductor policies; this application also depicts maintainer status on opting in and if the email is deemed valid.

  • BiocPkgDash This package provides an interactive Shiny dashboard for Bioconductor package maintainers. It visualizes various package statuses, metadata, and development metrics, offering insights into package health and activity. This tool aims to support maintainers of multiple packages by filtering packages via maintainer email.

  • carnation Highly interactive & modular shiny app to explore three facets of RNA-Seq analysis: differential expression (DE), functional enrichment and pattern analysis. Several visualizations are implemented to provide a wide-ranging view of data sets. For DE analysis, we provide PCA plot, MA plot, Upset plot & heatmaps, in addition to a highly customizable gene plot. Seven different visualizations are available for functional enrichment analysis, and we also support gene pattern analysis. Genes of interest can be tracked across all modules using the gene scratchpad. In addition, carnation provides an integrated platform to manage multiple projects and user access that can be run on a central server to share with collaborators.

  • CellMentor Implements supervised cell type-aware non-negative matrix factorization (NMF) for dimensional reduction in single-cell RNA sequencing analysis. The package provides methods for incorporating cell type information into the dimensionality reduction process, enabling improved visualization and downstream analysis of single-cell data while preserving biological structure. CellMentor employs a unique loss function that simultaneously minimizes variation within known cell populations while maximizing distinctions between different cell types, enabling effective transfer of learned patterns from labeled reference datasets to new unlabeled data.

  • ClonalSim ClonalSim generates realistic mutational profiles of tumor samples with hierarchical clonal structure. It simulates founder, shared, and private mutations with biologically realistic noise models including intra-tumor heterogeneity (Beta distribution) and technical sequencing noise (negative binomial depth variation, binomial read sampling, base errors). The package is designed for benchmarking variant callers, testing clonal deconvolution algorithms, and teaching tumor heterogeneity concepts.

  • ClusterGVis Provides a streamlined workflow for clustering and visualizing gene expression patterns, particularly from time-series RNA-Seq and single-cell experiments. The package is designed to integrate seamlessly within the Bioconductor ecosystem by operating directly on standard data classes such as SummarizedExperiment and SingleCellExperiment. It implements common clustering algorithms (e.g., k-means, fuzzy c-means) and generates a suite of publication-ready visualizations to explore co-expressed gene modules. Functions are also included to facilitate the visualization of clustering results derived from other popular tools.

  • CompensAID The CompensAID is an automated quality control tool, which determines for each marker combination in the FCS file, whether there a potential presence of reference errors. Such reference errors, which represent themselves in the form of skewed populations, are detected by integrating the Secondary Stain Index (SSI) score. Marker combinations with an SSI < 1 are flagged by CompensAID.

  • CrcBiomeScreen A developed and benchmarked reproducible machine learning framework for microbiome-based colorectal cancer (CRC) screening. By systematically evaluating normalization strategies, taxonomic resolutions, and class imbalance handling. This R package allows users to apply the full pipeline or selectively run specific components depending on their analytical needs. It establishes a scalable foundation for developing interpretable microbiome-based screening tools to support early CRC detection. This approach could be easily implemented in a national screening programme, to improve early detection rates for this disease.

  • damidBind The damidBind package provides a straightforward formal analysis pipeline to analyse and explore differential DamID binding, gene transcription or chromatin accessibility between two conditions. The package imports processed data from DamID-seq experiments, either as external raw files in the form of binding bedGraphs and GFF/BED peak calls, or as internal lists of GRanges objects. After optionally normalising data, combining peaks across replicates and determining per-replicate peak occupancy, the package links bound loci to nearby genes. For RNA Polymerase DamID data, the package calculates occupancy over genes, and optionally calcualates the FDR of significantly-enriched gene occupancy. damidBind then uses either limma (for conventional log2 ratio DamID binding data) or NOIseq (for counts-based CATaDa chromatin accessibility data) to identify differentially-enriched regions, or differentially epxressed genes, between two conditions. The package provides a number of visualisation tools (volcano plots, Gene Ontology enrichment plots via ClusterProfiler and proportional Venn diagrams via BioVenn for downstream data exploration and analysis. An powerful, interactive IGV genome browser interface (powered by Shiny and igvShiny) allows users to rapidly and intuitively assess significant differentially-bound regions in their genomic context.

  • decemedip The R package decemedip is a novel computational paradigm developed for inferring the relative abundances of cell types and tissues measure by methylated DNA immunoprecipitation sequencing (MeDIP-Seq). This paradigm allows using reference data from other technologies such as microarray or WGBS.

  • DenoIST DenoIST identifies and removes contamination in Image-based Spatial Transcriptomics data, using a transposed poisson mixture model with local neighbourhood offsets to infer genes that are likely to be due to neighbourhood contamination rather than endogenous expression.

  • dominatR dominatR is an R package for quantifying and visualizing feature dominance in datasets. dominatR applies concepts drawn from physics such as center of mass and shannon’s entropy to effectively visualize features (e.g. genes) that are present within a specific context or condition. The package integrates, dataframes, matrices and SummerizedExperiment objects and is able to perform common genomic normalization methods. The key aspect is the generation of plots that serve to highlight context-relevant feature dominance.

  • DOTSeq Differential open reading frame (ORF) translation analysis framework for ribosome profiling (Ribo-seq) with matched RNA-seq. Implements (i) Differential ORF Usage (DOU), a beta-binomial generalized linear model that models the expected proportion of Ribo-seq versus RNA-seq reads mapping to each ORF within a gene, and (ii) ORF-level Differential Translation Efficiency (DTE), a negative binomial GLM that capture changes in translation efficiency of individual ORFs across experimental conditions. Supports ORF-level read summarization for bulk and single-cell Ribo-seq.

  • drugfindR This package provides a convenient way to access the LINCS Signatures available in the iLINCS database. These signatures include Consensus Gene Knockdown Signatures, Gene Overexpression signatures and Chemical Perturbagen Signatures. It also provides a way to enter your own transcriptomic signatures and identify concordant and discordant signatures in the LINCS database.

  • epiRomics Integrates various levels of epigenomic information, including ChIP-seq, histone modification, ATAC-seq, and RNA-seq data. Regulatory network analysis uses combinatory approaches to infer regions of significance, such as enhancers. Downstream analysis identifies co-occurrence of epigenomic data at regions of interest. Visualization functions display multi-track genomic views with signal overlays. Please contact ammawla@ucdavis.edu for suggestions, feedback, or bug reporting.

  • epiSeeker This package implements functions to analyze multi-omics epigenetic data. Data of fragment type and base type are supported by epiSeeker. It provides functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statistical methods to estimate the significance of overlap among peak data sets, and motif analysis. It incorporates the GEO database for users to compare their own dataset with those deposited in the database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, overlap of peaks or genes, and the single-base resolution epigenetic data by considering the strand, motif, and additional information.

  • ExpoRiskR ExpoRiskR provides tools for exposure-aware multi-omics risk modeling in translational and environmental health studies. The package aligns sample identifiers across exposure and multi-omics blocks, performs lightweight preprocessing, and fits exposure-adjusted association models to build interpretable microbe–metabolite networks. It also computes simple exposure perturbation summaries and generates publication-ready visualizations. Workflows support both matrix-based inputs and SummarizedExperiment objects.

  • fastRanges High-performance interval overlap and join operations for ‘IRanges’ and ‘GenomicRanges’. The package provides deterministic multithreaded overlap computation, reusable subject indexes for repeated queries, and join helpers that keep range metadata in a consistent output grammar.

  • fourSynergy fourSynergy is an ensemble algorithm leveraging synergies among the existing 4C-seq algorithms r3C-seq, peakC, r.4cker and fourSig. It uses a weighted voting approach to perform improved interaction calling. fourSynergy supports also differential interaction calling.

  • fRagmentomics A user-friendly R package that enables the characterization of each cfDNA fragment overlapping one or multiple mutations of interest, starting from a sequencing file containing aligned reads (BAM file). fRagmentomics supports multiple mutation input formats (e.g., VCF, TSV, or string “chr:pos:ref:alt” representation), accommodates one-based and zero-based genomic conventions, handles mutation representation ambiguities, and accepts any reference file and species in FASTA format. For each cfDNA fragment, fRagmentomics outputs its size, its 3’ and 5’ sequences, and its mutational status. Optionally, when users set apply_bcftools_norm = TRUE, fRagmentomics invokes the external command-line tool bcftools norm to left-align and normalize variants. If bcftools is not found on the system PATH while this option is enabled, the function errors. The package does not install external software; see the INSTALL file for per-OS instructions.

  • fraq High-throughput extensible toolkit for processing FASTQ data. The goal of this package is to empower users to quickly build out small programmatic ‘kernels’ to define any FASTQ processing task they may need. Builds on Intel TBB’s flow graph to orchestrate concurrent I/O and data processing; throughput can be as fast as compression and disk speed allows. The package also ships with a suite of predefined kernels for common FASTQ tasks.

  • GenomicCoordinates Extends string parsing capabilities for genomic coordinates, supporting various formats including comma-separated numbers, space-delimited coordinates, and automatic detection of GRanges, GPos, and GInteractions objects.

  • glycoTraitR GlycoTraitR is an R package for analyzing glycoproteomics data, particularly glycopeptide-spectrum matches (GPSMs). It supports results generated by the pGlyco3 and Glyco-Decipher search engines. The package parses glycan structures, computes monosaccharide compositions and structural traits, and performs differential analysis of glycan heterogeneity. It constructs trait-by-PSM matrices stored in a SummarizedExperiment object, supports user-defined structural motifs, and provides visualization utilities for interpreting glycan trait changes.

  • GOaGO GO-a-GO annotates Gene Ontology terms that are enriched in a given set of gene pairs. The enrichment is calculated from a permutation test for overrepresentation of gene pairs that are associated with a shared term. Such gene pairs are counted for the original set of gene pairs and compared against randomized sets in which the structure of the pairs is preserved, but the gene identities (including the associated terms) are permuted.

  • GOfan GOfan provides an intuitive and compact visualization of Gene Ontology (GO) enrichment results using a sunburst layout inspired by SynGO, preserving hierarchical relationships among GO terms and allowing color-based encoding of information such as p-values or gene counts. By converting complex GO DAGs into clean, circular representations, it allows researchers to quickly grasp the hierarchical structure and biological significance of enriched terms. The interactive and customizable visualizations facilitate exploration of key GO categories, enhancing interpretation and presentation of enrichment analyses.

  • GraphExperiment GraphExperiment provides users and developers with an S4 class that extends SingleCellExperiment by offering infrastructure to store and retrieve networks (igraph objects) representing how features are associated with each other. The class was designed to store networks inferred from high-dimensional quantitative data, including gene coexpression networks (GCNs), gene regulatory networks (GRNs), and co-abundance networks (from proteomics and metabolomics), as well as networks inferred from other types of data (e.g., protein-protein interactions).

  • GSABenchmark GSABenchmark is a package designed for benchmarking scRNA-seq gene set analysis (scGSA) methods. It provides both traditional and novel benchmark metrics, as well as visualization tools. Currently, GSABenchmark supports 17 scGSA methods.

  • hammers hammers is a utilities suite for scRNA-seq data analysis compatible with both Seurat and SingleCellExperiment. It provides simple tools to address tasks such as retrieving aggregate gene statistics, finding and removing rare genes, performing representation analysis, computing the center of mass for the expression of a gene of interest in low-dimensional space, and calculating silhouette and cluster-normalized silhouette.

  • HiSpaR Provides R bindings for HiSpa, a hierarchical Bayesian model for inferring three-dimensional chromatin structures from Hi-C contact matrices using Markov Chain Monte Carlo (MCMC) sampling. The package implements a cluster-based hierarchical approach that efficiently handles large-scale Hi-C datasets. It uses Rcpp and RcppArmadillo for efficient C++ integration with the original HiSpa C++ implementation, enabling fast computation of chromatin structure inference through parallel MCMC sampling.

  • HistoImagePlot Create side-by-side visualizations of tissue thumbnail image and HoverNet cell segmentation with colored cell type labels. Functionality automatically retrieves the thumbnail image associated with a HoverNet JSON file and overlays the segmentation data. This package is intended for researchers working with histopathological images, facilitating exploratory analysis, and integrates with the imageFeatureTCGA Bioconductor package.

  • ImageArray ImageArray provides a framework for on-disk and in-memory image arrays, specifically for pyramidal images stored in HDF5, Zarr and life sciences image file formats (OME Bio-Formats).

  • imageFeatureTCGA The package imports data from HoverNet, and ProvGigaPath pipelines. Pipeline output data are hosted in a self-owned online repository. Package functionality conveniently incorporates pipeline data into existing MultiAssayExperiment instances from curatedTCGAData.

  • imageTCGAutils Utility functions for working with CONCH data, listing remote files. One function assigns HoverNet nuclei to ProvGigaPath tiles with a scale factor to align coordinates. Provides internal utility functions for ‘imageFeatureTCGA’ and most functions are not meant for end users.

  • immLynx A comprehensive toolkit that bridges popular Python-based immune repertoire analysis tools and Hugging Face protein language models into the R environment. Provides unified interfaces for TCR distance calculations (tcrdist3), sequence generation probability (OLGA), selection inference (soNNia), clustering (clusTCR), protein embeddings (ESM-2), metaclone discovery (metaclonotypist). Fully compatible with the scRepertoire and immApex ecosystem for single-cell immune repertoire analysis.

  • immReferent Provides a consistent interface for downloading, storing, and accessing immune receptor (TCR/BCR) and HLA sequences from IMGT, IPD-IMGT/HLA, and OGRDB (AIRR-C). Supports export to popular analysis tools including MiXCR, TRUST4, Cell Ranger, and IgBLAST. This package serves as a core dependency for immunogenomics packages, ensuring reliable and high-quality sequence access with local caching for reproducibility.

  • jvecfor Drop-in replacement for BiocNeighbors::findKNN using the jvecfor Java library, which builds on the jvector library to leverage the Java Vector API for portable SIMD acceleration across AVX2, AVX-512, and ARM NEON hardware. jvecfor/jvector implements HNSW-DiskANN approximate search and VP-tree exact search. The package achieves approximately 2x speedup over Annoy-based search at n >= 50K cells while returning output structurally identical to BiocNeighbors, making it suitable for seamless integration into existing Bioconductor single-cell workflows. Convenience wrappers delegate shared nearest-neighbor (SNN) and k-nearest-neighbor (KNN) graph construction to the bluster package.

  • LACHESIS This package provides modalities to analyze tumor evolution from whole genome sequencing data. In particular, it provides estimates of mutation densities at genomic segments and uses these to time the origin of the tumor.

  • lcmsPlot lcmsPlot is an R package designed for visualising Liquid Chromatography-Mass Spectrometry (LC-MS) data with publication-ready high-quality plots. The package enables users to generate and customise chromatograms, mass traces, spectra, and more with fine-tuned aesthetics and annotation options.

  • leapR leapR is a package that identifies pathways that are enriched across diverse ‘omics experiments. It leverages any tabular expression data (proteomics, transcriptomics) using the SummarizedExperiment object. It works with any pathway in the .gct file format.

  • lncRna Provides a complete workflow for the identification, analysis, and functional annotation of long non-coding RNAs (lncRNAs) from RNA-Seq data. The package includes functions for filtering transcripts from GTF files, evaluating the performance of multiple coding potential prediction tools (e.g., CPC2, PLEK, CPAT), and summarizing their agreement. It enables systematic performance analysis of individual tools, “at least N” tool consensus, and all possible tool combinations. Functional analysis is supported through the identification of potential cis- and trans-acting interactions with protein-coding genes, followed by enrichment analysis. Results can be visualized using a variety of plots, including radar plots, clock plots, and interactive Sankey diagrams.

  • LRDE Provides hurdle negative binomial models for differential expression analysis with long-read RNA-Seq data.

  • MDSvis This package implements visulization of Multi Dimensional Scaling (MDS) results.

  • MeLSI MeLSI (Metric Learning for Statistical Inference) is a novel machine learning method for microbiome data analysis that learns optimal distance metrics to improve statistical power in detecting group differences. Unlike traditional distance metrics (Bray-Curtis, Euclidean, Jaccard), MeLSI adapts to the specific characteristics of your dataset to maximize separation between groups. The method uses an ensemble of weak learners to identify which microbial features drive group differences, providing both improved statistical power and biological interpretability through feature importance weights.

  • MetaboAnnotatoR Performs feature annotations on LC-MS All-ion fragmentation datasets using fragment ion libraries.

  • metabom8 Tools for 1D NMR metabolomics workflows, including import and preprocessing of Bruker experiments, multivariate modeling (PCA, PLS, OPLS) and model analytics and validation (y-permutations, cv-anova). Performance-critical routines are implemented in C++ and use the Armadillo and Eigen linear algebra libraries to improve runtime.

  • MetaProViz MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It performs functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

  • MutSeqR Standard methods for analysis of mutation data following error- corrected sequencing (ECS) for the purpose of mutagencity assessment. Functions include importing the mutation lists provided by a variant caller, and a set of analytical tools for statistical testing and visualization of mutation data; comparison to COSMIC and/or germline signatures; etc.

  • OAtools Provides a suite of R functions to analyze gene expression experiments on the OpenArray real-time PCR platform. OAtools fits logistic regressions to fluorescence curves to distinguish between real amplification and false positives. OAtools supports data import, analysis, and visualization through plots and a dynamic HTML report.

  • parati Infers maternal and paternal transmitted and non-transmitted alleles from phased trio genotype data. The package supports SNP-level analyses of genetic nurture and transgenerational effects. It interoperates with Bioconductor VCF infrastructure through support for VariantAnnotation::VCF objects and returns R objects for downstream analysis.

  • plaid PLAID (Pathway Level Average Intensity Detection) is an ultra-fast method to compute single-sample enrichment scores for gene expression or proteomics data. For each sample, plaid computes the gene set score as the average intensity of the genes/proteins in the gene set. The output is a gene set score matrix suitable for further analyses.

  • PlinkMatrix This package provides a DelayedArray interface for plink bed files. There is support for interfacing to plink genotype data via RangedSummarizedExperiment. Example data from the GEUVADIS project (internationalgenome.org) are used for demonstration.

  • posDemux Demultiplexing and filtering utilities intended for reads with combinatorial barcodes (i.e. PETRI-seq and SPLiT-seq). The demultiplexer algorithm uses the position of the segments to extract and compare the barcodes with the reference (whitelist). A Shiny application is provided to interactively select cutoffs for which barcode combinations to keep.

  • postNet A tool that enables in silico identification, integration, and modeling of mRNA features that influence post-transcriptional regulation of gene expression at a transcriptome-wide scale.

  • proBatch These tools facilitate batch effects analysis and correction in high-throughput experiments. It was developed primarily for mass-spectrometry proteomics (DIA/SWATH), but could also be applicable to most omic data with minor adaptations. The package contains functions for diagnostics (proteome/genome-wide and feature-level), correction (normalization and batch effects correction) and quality control. Non-linear fitting based approaches were also included to deal with complex, mass spectrometry-specific signal drifts.

  • PTMods An interface to the community supported database for amino acid/protein modifications using mass spectrometry.

  • queeems Biological inferences obtained from molecular data are only as good as the extent of evolutionary signatures retained in the genetic data. Techniques available to quantify these signatures are largely targeted towards phylogeny reconstruction and they often rely on adhoc hypothesis tests of significance. I present a Bayesian function that assesses whether a set of genetic sequences are saturated. That is, it is useful for determining whether the evolutionary information in the sequences has eroded with time. Site specific Bayes factors are generated with respect to codon bases to allow for straightforward applications in extensive computational biology inquiries, including natural selection analyses.

  • RankMap RankMap is a fast and scalable tool for reference-based cell type annotation of single-cell and spatial transcriptomics data. It uses ranked gene expression and multinomial regression to achieve robust predictions, even with partial gene coverage. Compatible with Seurat, SingleCellExperiment, and SpatialExperiment objects, RankMap offers flexible preprocessing and significantly faster runtime than tools like SingleR, Azimuth, and RCTD.

  • RBedMethyl Bioconductor-native infrastructure for handling large nanoporetech modkit bedMethyl pileup files from ONT data using HDF5Array and DelayedArray.

  • Rega The European Genome-phenome Archive (EGA) provides long-term storage and controlled sharing of personally identifiable genetic data. The Rega package offers a streamlined and extensible R interface to the EGA API, facilitating the programmatic upload of metadata. GEO-like Excel submission template is provided as a default method of organizing submission metadata.

  • RFGeneRank Tools to harmonize bulk RNA-seq matrices, optionally apply batch correction, and train cross-validated classification models using ranger, glmnet, or xgboost. Supports leakage-safe feature selection, permutation importance, SHAP-based interpretability, and calibration methods (Platt or isotonic). Provides stability metrics across folds, embeddings (PCA/UMAP), ROC visualization, SHAP dependence plots, and tidy ranked-gene tables for downstream analysis.

  • RNAshapeQC RNAshapeQC provides coverage-shape-based quality control (QC) metrics for mRNA-seq and total RNA-seq data. It supports per-gene pileup construction from BAM files as well as toy datasets for quick-start examples. The package implements protocol-specific metrics, including decay rate (DR), degradation score (DS), mean coverage depth (MCD), window coefficient of variation (wCV), area under the curve (AUC), and shape-based sample-level indices. RNAshapeQC also includes HPC-friendly functions for per-gene batch processing and cross-study pileup generation. This package enables interpretable, protocol-specific QC assessments for diverse RNA-seq workflows.

  • scConform Builds prediction interval for cell type annotation using conformal inference and conformal risk control. It provides two main methods. The first one gives prediction intervals with coverage guarantees based on standard conformal inference. The second one instead gives hierarchical prediction intervals that are consistent with the cell ontology.

  • scECODA The scECODA R package provides a complete workflow for the analysis and visualization of compositional data, primarily focusing on cell type proportions derived from single-cell data. It implements specialized methods, such as the Centered Log-Ratio (CLR) transformation, to properly analyze proportional data while avoiding the biases introduced by the compositional constraint. The package encapsulates data management, transformation, and analysis into a single SummarizedExperiment object, offering downstream tools for dimensionality reduction via PCA, calculating critical metrics like the Adjusted Rand Index (ARI) and Modularity to quantify sample grouping quality, and generating high-quality visualizations like heatmaps and scatter plots.

  • scLang scLang is a suite for package development for scRNA-seq analysis. It offers functions that can operate on both Seurat and SingleCellExperiment objects. These functions are primarily aimed to help developers build tools compatible with both types of input.

  • scPassport Stamps Seurat, SingleCellExperiment, and SummarizedExperiment objects with a persistent metadata passport. For Seurat objects the passport is stored in the misc slot; for SingleCellExperiment and SummarizedExperiment objects it is stored in the metadata slot. Tracks animal info, experiment details, lineage (parent/child relationships), RDS registry numbers, processing logs, and custom fields. Includes an interactive Shiny gadget to fill and update the passport, and a read mode to print the full passport to console. The passport persists inside the RDS file with no external files needed.

  • scToppR scToppR provides an easy-to-use API wrapper for the ToppGene web platform, used for gene ontology and functional enrichment research. The package also integrates visualization tools, making it a convenient tool directly connecting ToppGene to code-based workflows in R. The tool can also easily save results into different formats.

  • scTypeEval scTypeEval provides tools to evaluate and validate cell type classifications in single-cell transcriptomics when ground truth labels are limited or unavailable. Results are organized in an S4 object that integrates processed data, dimensional reductions, dissimilarity assays, and consistency metrics computed across samples. The workflow includes preprocessing and feature selection, principal component analysis, computation of dissimilarity matrices, internal validation metrics (for example, silhouette-based summaries), and visualization utilities to inspect heatmaps and PCA plots. Functions support common single-cell containers and enable comparison of clustering and labeling strategies across datasets.

  • SEMPLR SEMPLR computes transcription factor binding affinity scores for genomic positions and genetic variants. Scores are computed from SNP Effect Matrices (SEMs) produced by SEMpl. 223 pre-computed SEMs are included with the package or custom sets can be provided. Enrichment can be tested among sets of genomic positions to determine if transcription factor binding events occur more often than expected. Comparing binding affinity scores between alleles can reveal differences in transcription factor binding with genetic variation. This package also includes several visualization functions to view scores both on the motif and variant/position level.

  • Seqtometry This package provides functions used in Seqtometry (Kousnetsov et al. 2024), a method for analyzing single cell (scRNA-seq or scATAC-seq) data via signature (gene set) enrichment scores. The Seqtometry scores may be useful for annotating or characterizing cells, either in a flow cytometry like workflow (where scores are standalone features used for progressive partitoning as described in the Seqtometry publication) or in a cluster-based workflow (as features of clusters). The exported impute function (a port of Python’s MAGIC-impute, van Dijk et al. 2018), may also be useful for single cell analysis on its own.

  • sfi Data analysis for Single File Injections(SFIs) mode LC-MS analysis. In SFIs mode, pooled samples are initially injected to serve as reference peaks for subsequent analyses. Repeated injections of individual samples are then performed at fixed time intervals using isocratic elution. This package provides the functions to analyze data from SFIs mode including peak picking and peak reassignment.

  • singIST Provides with toolkits to implement a full singIST analysis with pseudobulked Seurat objects of disease models and human data.

  • SMTrackR The package uses exogenous enzyme imprinted information to map protein-DNA binding on individual sequenced DNA molecules. For example, GpC methyltransferase, CpG methyltransferase, and Adenine methyltransferases. Public datasets from such assays are compiled into tracks, and hosted at public servers like Galaxy for their seamless access by this package.

  • SpatialArtifacts SpatialArtifacts provides a data-driven two-step workflow to identify, classify, and handle spatial artifacts in spatial transcriptomics data. The package combines median absolute deviation (MAD)-based outlier detection with morphological image processing (fill, outline, and star patterns) to detect edge and interior artifacts. It supports multiple platforms including 10x Genomics Visium (standard and HD), allowing for consistent quality control across different spatial resolutions.

  • SpiecEasi Estimate networks from the precision matrix of compositional microbial abundance data.

  • SpliceImpactR Works by taking in processed data from the HIT Index and/or rMATS and identifying how differentially used alternative RNA processing events lead to changes in protein function through various means. Primarily this is done through protein similarity, functional protein domain analysis, and domain-domain interaction changes. Notably, we both identify alterantive RNA processing event ‘swaps’ across condition and are able to perform holistic analyses regarding the impact of different RNA processing events.

  • splicelogic Translate differential transcript usage results into discrete splice events.

  • SpNeigh SpNeigh provides methods for neighborhood-aware analysis of spatial transcriptomics data. It supports boundary detection, spatial weighting (centroid- and boundary-based), spatially informed differential expression using spline-based models, and spatial enrichment analysis via the Spatial Enrichment Index (SEI). Designed for compatibility with Seurat objects, SpatialExperiment objects and spatial data frames, SpNeigh enables interpretable, publication-ready analysis of spatial gene expression patterns.

  • staRgate An R-based automated gating pipeline for flow cytometry data designed to mimic the manual gating strategy of defining flow biomarker positive populations relative to a unimodal background population to include cells with varying intensities of marker expression. The pipeline’s main feature is a flexible density-based gating strategy capable of capturing varying scenarios based on marker expression patterns to analyze a 29-marker flow panel that characterizes T-cell lineage, differentiation, and functional states.

  • StatescopeR StatescopeR is an R wrapper around Statescope, a computational framework designed to discover cell states from cell type-specific gene expression profiles inferred from bulk RNA profiles.

  • tidyexposomics The tidyexposomics package is designed to facilitate the integration of exposure and omics data to identify exposure-omics associations. We structure our commands to fit into the tidyverse framework, where commands are designed to be simplified and intuitive. Here we provide functionality to perform quality control, sample and exposure association analysis, differential abundance analysis, multi-omics integration, and functional enrichment analysis.

  • tidyprint Provides customized print methods for ‘SummarizedExperiment’ objects to enhance readability and usability within a tidy workflow. It offers consistent, tidyverse-aligned console displays, including alternative tibble abstractions for large genomic data to improve discoverability and interpretation. The package also includes unified, contextual messaging utilities intended for the ‘tidyomics’ ecosystem.

  • toppgene The ToppGene Suite is a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network. Although the ToppCluster web application provides convenient graphical access to the ToppGene Suite, the OpenAPI 3.0 compliant interface of ToppGene is better suited for automation and reproducibility. This package includes Bioconductor class interfaces and biological examples.

  • VISTA The VISTA (Visualization and Integrated System for Transcriptomic Analysis) platform streamlines differential expression workflows by wrapping DESeq2 and edgeR into a SummarizedExperiment-based container with consistent metadata. The package includes visualization utilities, MSigDB enrichment helpers, and optional deconvolution support to simplify interactive exploration of RNA-seq experiments.

  • wavFeatExt Provides tools for simulating copy-number alteration (CNA) profiles, applying a non-decimated Haar wavelet transform to genomic signals, and extracting wavelet-derived features for use in supervised learning. Multiple machine learning methods including lasso and elastic-net regularisation, random forest, partial least squares, neural networks and k-nearest neighbours are implemented to train predictive models from genomic feature vectors. The workflow enables end-to-end analysis from CNA simulation to feature extraction and classification.

  • ZarrArray The ZarrArray package leverages the Rarr package to bring Zarr datasets in R as DelayedArray objects. The main class in the package is the ZarrArray class. A ZarrArray object is an array-like object that represents a Zarr dataset in R. ZarrArray objects are DelayedArray derivatives and therefore support all operations (delayed or block-processed) supported by DelayedArray objects.

New Data Experiment Packages

There are 5 new data experiment packages in this release of Bioconductor.

  • DMRsegaldata Data package providing example DNA methylation files used in the DMRsegal vignette and examples. Includes a sorted beta matrix as a tab-delimited, bgzip-compressed file and a matching phenotype table. The data contains 10 healthy and 10 cancer samples, and preprocessing has already been performed on the beta values.

  • dominatRData dominatRData is a data package useful for showcasing dominatR examples. dominatR is an R package for quantifying and visualizing feature dominance in datasets. dominatR makes use of entropy-based triangular projections and compositional comparison metrics.

  • EMTscoreData Provides 12 single-cell RNA-seq datasets profiling epithelial–mesenchymal transition (EMT) in human cancer cell lines (MCF7, OVCA420, DU145, and A549) under TGF-beta stimulation, kinase inhibition, and time-course conditions, as reported by Cook DP and Vanderhyden BC (2020). The datasets are distributed via ExperimentHub as SingleCellExperiment objects.

  • HumanRetinaLRSData Dataset package containing gene and isoform count matrices, and sample metadata for long-read direct cDNA sequencing of human retinal organoids, 2D retinal ganglion cell (RGC) cultures, and flowthrough fractions from H9 and EP1 iPSC cell lines. Data were generated using Oxford Nanopore Technology (ONT) direct cDNA sequencing and mapped to the GRCh38 reference genome (GENCODE v46 annotation). The package provides accessor functions returning SummarizedExperiment objects for gene-level counts, isoform-level counts, and a matrix of allele-specific expression (ASE) gene counts. Data files are stored in flat CSV format in an Open Science Framework (OSF) repository and cached locally via BiocFileCache.

  • MutSeqRData Experimental data for use with the MutSeqR vignette and examples. This dataset is taken from LeBlanc et al., 2022. 24 MutaMouse animals were exposed to one of three doses of benzo[a]pyrene or a vehicle control for 28 days by oral gavage. 28 days after the end of the exposure, bone marrow of the femurs was harvested from euthanized animals. DNA extraction was conducted via DNeasy Blood and Tissue kit. DNA samples were sequenced using TwinStrand’s Duplex Sequencing on the Mouse Mutagenesis Panel at > 10,000 depth. The Mouse Mutagenesis Panel comprises 20 2.4kb genomic targets with one located on each mouse autosome (two on chromosome 1). Pre-processing of sequence reads was redone since publication using an updated version of TwinStrand’s Mutagenesis App (v. 3.20.1) which produced tabular mutation data files for each sample. Data contained herein are only those required for running MutSeqR examples and vignette.

New Annotation Packages

There are no new annotation packages in this release of Bioconductor.

New Workflow Packages

There are no new workflow packages in this release of Bioconductor.

New Online Books

There are two new online books in this release of Bioconductor.

  • OMA This is a reference cookbook for Microbiome Data Science with R and Bioconductor.

  • scrapbook Demonstrates some basic analysis of single-cell RNA-seq data with scrapper. This includes quality control, normalization, feature selection, various forms of dimensionality reduction, clustering into subpopulations, and detection of marker genes. It is intended for users who already have some familiarity with R and want to get hands-on with some basic single-cell analyses.

NEWS from existing Software Packages

ADaCGH2

             Changes in version 2.51.3 (2026-04-16)

  • Fixed minor notes and warnings in r-universe.

               Changes in version 2.51.2 (2026-04-14)

  • Fixed “Remove Maintainer field. Use Authors@R [cre] designation” error from r-universe.

               Changes in version 2.51.1 (2026-01-31)

  • Fixed (most) NOTES from R CMD check –as-cran

alabaster.base

                   Changes in version 1.12.0
  • Added a cloneFile() utility to clone a single file, by copying, hard-linking or (relative) symlinking.

alevinQC

                   Changes in version 1.27.1
  • Remove explicit C++11 system dependency

anndataR

                    Changes in version 1.2.0

New features

  • Add initial Zarr support for reading and writing .zarr stores

  • Allow manually setting chunk size for HDF5 writes

  • Add auto-chunking for HDF5 writes to improve performance

  • Optimise sparse matrix reading performance by avoiding Matrix::sparseMatrix and constructing objects manually

Bug fixes

  • Handle unnamed SingleCellExperiment assays in as_AnnData() by automatically assigning names with a warning

  • Improve warnings when items fail to convert between objects and add new warnings and checks

Documentation

  • Updates to vignettes

  • Fix broken links

  • Update author details

Testing

  • Add a benchmarking system to monitor function performance

  • Improvements to roundtrip tests

  • Improvements to HDF5 tests

  • Improvements to GitHub Actions CI

annoLinker

                   Changes in version 0.99.7
  • Initial Acceptance to Bioconductor

AnnotationHubData

                   Changes in version 1.41.0

NEW FEATURES

  • 1.41.1 Added Parquet as acceptable source type

AnVIL

                   Changes in version 1.24.0

NEW FEATURES

  • (v 1.23.13) Add package options to bypass hardcoded URLs.

  • (v 1.23.12) Use keyring to store auth.json file.

USER VISIBLE CHANGES

  • (v 1.23.10) Use sha256 instead of md5sum for service validation.

  • (v 1.23.4) Use native pipe operator |> instead of magrittr pipe.

BUG FIXES AND MINOR IMPROVEMENTS

  • (v 1.23.11) Update Dockstore API version to 1.19.2.

  • (v 1.23.10) Fix typo in Service docs and use rmarkdown backticks for code in documentation.

  • (v 1.23.8) Use qualified gcloud_access_token to avoid NAMESPACE conflicts.

  • (v 1.23.7) Update APIs and track openapi.yaml in automatic commits.

  • (v 1.23.6) Update Dockstore API version to 1.18.2.

  • (v 1.23.5) Update R version dependency to R-devel.

  • (v 1.23.4) Add code chunk labels to vignettes.

  • (v 1.23.3) Add URL and BugReports fields to documentation and DESCRIPTION.

AnVILAz

                    Changes in version 1.6.0

Bug fixes and minor improvements

  • Sanitize error messages in .az_do() to prevent sensitive information in URLs.
  • Added unit tests for utility functions.

AnVILBase

                    Changes in version 1.6.0
  • Use GCPtools::gcloud_exists() for checking gcloud availability.

AnVILGCP

                    Changes in version 1.6.0

Deprecated and defunct

  • Move gcloud functions to DEFUNCT status as they have been fully migrated to GCPtools

Bug fixes and minor improvements

  • Use GCPtools::gcloud_exists for internal checks
  • Use with_mocked_bindings in tests

AnVILPublish

                   Changes in version 1.22.0

New Features

  • (v. 1.21.1) Export create_workspace() for creating a new AnVIL workspace without necessarily populating it from an R package.

APAlyzer

             Changes in version 1.25.2 (2026-04-05)

  • Fixed compatibility with R-devel and Bioconductor 3.22/3.23.

  • Fixed test failure caused by ggplot2 4.0+ S7 object type change.

  • Replaced deprecated element_line(size=) with element_line(linewidth=).

  • Replaced library(HybridMTest) calls with requireNamespace(); moved HybridMTest to Suggests.

  • Migrated makeTxDbFromGRanges import from GenomicFeatures to txdbmaker.

  • Added txdbmaker, rlang, and S4Vectors to Imports.

  • Fixed undefined global variables (Print, queryHits, download.file, etc.).

  • Added .Rbuildignore to exclude .travis.yml from build.

  • Updated License field in DESCRIPTION.

asuri

                    Changes in version 1.0.0
  • Launch version

atacInferCnv

                    Changes in version 1.0.0
  • Initial Acceptance to Bioconductor

atena

             Changes in version 1.18.0 (2026-04-27)

BUG FIXES

  • Fix in OneCodeToFindThemAll() when the ‘dictionary’ argument is not NULL.

BASiCS

             Changes in version 2.23.1 (2026-04-09)
  • Bug fix to replace deprecated arma::is_finite by std::isfinite

BatChef

                   Changes in version 0.99.12
  • Initial Acceptance to Bioconductor

BatchQC

                    Changes in version 2.7.2

Minor Changes

  • Changed maintainer from Jessica Anderson to Yaoan Leng

Minor Changes

  • Added lambda example to Intro vignette

Battlefield

                   Changes in version 0.99.03
  • Submitted to Bioconductor

beachmat

                   Changes in version 2.28.0

  • Added the .unknown.action= option to initializeCpp(), to determine whether to print a message, warning or error when using the unknown matrix fallback.

  • Consolidated row/column variants of various utilities into a single function, i.e., tatami.sums() for row/column sums, tatami.nan.counts() for NaN counts.

  • Added tatami.medians() to compute the row- and column-wise medians.

  • Added tatami.sums.by.group() to compute the row- and column-wise sums for groups of columns/rows, respectively.

BEclear

             Changes in version 2.27.1 (2026-01-02)
  • migration from dependency futile.logger to logger

bedbaser

                    Changes in version 1.3.5
  • Incorporated test_request parameter

  • Improved how bedbaser constructs BED file url

                      Changes in version 1.3.1
  • Update bedbase to 0.12.1
  • Replace download.file with curl::curl_download
  • Fix test for bb_bed_text_search

beer

             Changes in version 1.15.1 (2025-11-04)

  • Updated NEWS versioning to reflect Bioconductor updates.

  • Updated mislabeled progressr::progress dependency.

betterChromVAR

                    Changes in version 0.0.1
  • Initial Acceptance to Bioconductor

BiocAzul

                    Changes in version 1.0.0

New features

  • Initial Bioconductor submission!

BiocBuildReporter

                   Changes in version 0.99.0

SIGNIFICANT NEW FEATURES

  • First Bioconductor release.

BiocCheck

                   Changes in version 1.48.0

BUG FIXES AND MINOR IMPROVEMENTS

  • Package tarball size check updated to have a max of 10 MB (@LiNk-NY, #234).

BiocMaintainerApp

                   Changes in version 0.99.0

SIGNIFICANT NEW FEATURES

  • First Bioconductor release.

BiocNeighbors

                    Changes in version 2.6.0

  • Enable manual vectorization for Annoy and HNSW, if supported by the compiler. This improves speed at the cost of exact reproducibility across different toolchains/architectures. We consider this trade-off to be acceptable given that many other floating-point calculations already have non-identical precision across machines.

  • Accept non-ordinary matrices in X= and query= arguments for all functions. This requires beachmat to be installed.

  • Added .check.nonfinite= option to skip checks for non-finite values in all functions. This is useful when the user can guarantee that missing or infinite values are not present.

  • Moved the BNPARAM= argument closer to the front of the argument list of buildIndex(). This is more intuitive when examining the generic arguments.

  • Added saveIndex() and loadIndex() functions to save and load indices from disk.

BiocPkgDash

                   Changes in version 0.99.33
  • Initial Acceptance to Bioconductor

BiocSingular

                   Changes in version 1.28.0
  • Bugfix for center=TRUE and scale=TRUE when there are fewer than two rows.

biomaRt

                   Changes in version 2.68.0

BREAKING CHANGES

  • The port argument, if unspecified and if no scheme is provided in the host argument, now defaults to 443 (the standard port for https), instead of 80 (the standard port for http). This fixes issue #155 reported by Lori Shepherd.

  • For security reasons, biomaRt no longer tries to downgrade SSL settings in case of HTTPS connection issues. It is expected that most clients and servers are now set up to deal properly with HTTPS. In case of persistent issues, users are still able to set the SSL settings manually via setEnsemblSSL().

MINOR IMPROVEMENTS

  • All requests sent by biomaRt now include a custom user agent linking to the source GitHub repository, and indicating the package version.

  • The defunct archive argument in listMarts() and useMart() has been removed. It has been deprecated since Bioconductor 3.7 and defunct since Bioconductor 3.8 (2018).

INTERNAL CHANGES

  • Tests and some internals are now more robust to Ensembl Biomart being not responsive or unstable.

biomformat

                   Changes in version 1.39.17

BUG FIXES

  • Added explicit S4 dispatch method for biom_data() with signature c(“biom”, “character”, “missing”). Previously, calling biom_data() with only a character rows= argument (e.g. biom_data(x, rows=”GG_OTU_3”)) matched the catch-all (“biom”, “character”, “ANY”) method, which then forwarded the still-missing columns argument to the next dispatch layer, causing the error: “argument ‘columns’ is missing, with no default”. The new method defaults columns to 1:ncol(x) and dispatches cleanly. Fixes the vignette build ERROR on Bioconductor (chunk named_subsetting, biomformat.Rmd lines 402-413). R CMD check: 0 ERRORs, 0 WARNINGs, 4 pre-existing NOTEs.

                     Changes in version 1.39.16

BUG FIXES

  • Updated Joseph N. Paulson’s email address in Authors@R to joseph.paulson@yale.edu. R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs.

                     Changes in version 1.39.15

BUG FIXES

  • Replaced deprecated Author:/Maintainer: DESCRIPTION fields with the modern Authors@R: format using person() with role=c(“aut”,”cre”) for the maintainer. This was flagged as an ERROR by BiocCheck >= 1.46 and was the root cause of the “invalid email” complaint from Bioconductor — the field itself was structurally invalid, not just the address string. Updated maintainer email to joey711@gmail.com (reachable address). Added .BiocCheck to .Rbuildignore. R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs. BiocCheck: 1 ERROR (Watched Tags on support site — manual web action), 3 WARNINGs (version parity, no BioC deps, missing \value), 14 NOTEs (style/cosmetic).

                     Changes in version 1.39.14

DOCUMENTATION / VIGNETTE

  • Added two new vignette sections to vignettes/biomformat.Rmd:
    • “Constructing a BIOM from R data”: end-to-end make_biom() workflow showing how to build a biom object from a count matrix and a data.frame taxonomy table with list-valued columns (the dada2 pattern), write it with write_biom(), and read it back. Includes a callout directing large-dataset users to write_hdf5_biom() (addressing Issue #8), with a guarded HDF5 code chunk. Directly addresses Issues #4, #6, #9 for users who land on the vignette.

    • “Subsetting biom_data() by name”: demonstrates the character-vector row/column subsetting interface of biom_data() that was previously undocumented in the vignette. R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs.

                     Changes in version 1.39.13

DOCUMENTATION

  • write_biom(): added @details section documenting the 2^31-1 byte size limitation that arises because jsonlite serialises the entire BIOM object to a single R character string. Users with large datasets (thousands of samples or features) are now explicitly directed to write_hdf5_biom() which has no such size constraint. Closes GitHub Issue #8. R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs.

                     Changes in version 1.39.12

NEW FEATURES / TESTS

  • Issue #7 regression test: added inst/extdata/zero_col_hdf5.biom, a minimal 3x3 HDF5 BIOM fixture where the middle sample (“ZeroSamp”) has all-zero counts. The fixture is generated by the companion script inst/extdata/create_zero_col_hdf5.R using rhdf5 directly. Added two tests in test-hdf5-write.R:
    • “zero-column HDF5 fixture: biom_data() returns correct 3x3 matrix” — verifies that ZeroSamp is all zeros and the other two columns have the expected non-zero values. Validates that generate_matrix() (rewritten in v1.39.8 to use sparseMatrix directly from CCS triplets) correctly handles the case where indptr[j] == indptr[j+1].

    • “zero-column HDF5 fixture: make_biom() + write_hdf5_biom() round-trip” — verifies that write_hdf5_biom() -> read_biom() preserves the all-zero column. Both tests are guarded with skip_if_not_installed(“rhdf5”). R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs.

                     Changes in version 1.39.11

BUG FIXES

  • make_biom(): fix Issue #4 — NULL id was serialised as {} (empty JSON object) by jsonlite. make_biom() now substitutes “No Table ID” when id is NULL, matching the BIOM spec and ensuring write_biom() -> read_biom() is a lossless round-trip. validObject() now succeeds on the round-tripped object.

  • make_biom(): fix Issue #6 — when observation_metadata (or sample_metadata) is a data.frame with list columns (e.g. a “taxonomy” column holding character vectors of rank assignments, as produced by dada2), the metadata was serialised as a bare JSON array ([[…]]) instead of a named JSON object ({“taxonomy”:[…]}). The BIOM spec and downstream tools (phyloseq import_biom(), the Python biom library) require the named-object form. Root cause: as.matrix() on a list-column data.frame produces a list-matrix; as.list(row) then collapses field names. Fix: detect list-column data.frames and build per-row metadata directly as named lists, bypassing as.matrix(). Closes GitHub Issue #6. Also resolves user-support Issue #9 (dada2 -> biom -> write_biom workflow now works correctly). R CMD check: 0 ERRORs, 0 NOTEs, 2 pre-existing vignette WARNINGs.

                     Changes in version 1.39.10

NEW FEATURES

  • Updated vignette with four new sections:
    • HDF5 (BIOM v2) read and write via write_hdf5_biom() / read_biom(), including JSON-to-HDF5 conversion.
    • Tidy long-format output via as.data.frame() and as_tibble.biom(), with purrr-style summarisation examples (Shannon diversity, per-sample total counts) and base-R fallbacks.
    • SummarizedExperiment interoperability via biom_to_SummarizedExperiment() and as(x, “SummarizedExperiment”), showing assay(), colData(), and rowData() access.
    • Session info section.

  • All new vignette sections are guarded with requireNamespace() so the vignette builds cleanly without optional dependencies (rhdf5, tibble, purrr/dplyr, SummarizedExperiment/S4Vectors).

                     Changes in version 1.39.9

NEW FEATURES

  • write_hdf5_biom(x, biom_file): new exported function that serialises a biom object to the BIOM v2 HDF5 format. Writes both the sample-major and observation-major compressed-sparse representations required by the spec, plus all sample and observation metadata. Requires rhdf5 (Bioconductor); a clear error is raised if it is absent. read_biom() -> write_hdf5_biom() -> read_biom() is a lossless round-trip for both count data and metadata.

BUG FIXES

  • Moved rhdf5 from Imports to Suggests. The package loads and all JSON BIOM functionality works without rhdf5 installed; HDF5 read/write simply stops with an informative message when rhdf5 is absent.

                     Changes in version 1.39.8

BUG FIXES / PERFORMANCE

  • generate_matrix(): rewrote HDF5/BIOM-v2 matrix reconstruction to build a sparse Matrix directly from the CCS (indptr/indices/data) triplets stored in the HDF5 file, instead of first constructing a dense base::matrix via sapply() and then converting. For large datasets this avoids an O(n_obs * n_samples) allocation. The return value (list of named vectors, one per observation) is unchanged so all downstream code is unaffected. Also handles the edge case of an all-zero matrix (length(data) == 0) explicitly.

                     Changes in version 1.39.7

NEW FEATURES

  • as.data.frame.biom(): new S3 method that converts a biom object to a long-format (tidy) data.frame with one row per (feature, sample) pair. Columns: feature_id, sample_id, count, plus any sample and observation metadata columns appended via left-join. Pure base R, no tidyverse dependency.

  • as_tibble.biom(): thin wrapper around as.data.frame.biom() that returns a tibble. Requires the ‘tibble’ package (Suggests only). Call via tibble::as_tibble(x) or as_tibble.biom(x) directly.

DEPENDENCY CHANGES

  • Added tibble to Suggests (optional; only needed for as_tibble.biom()).

                     Changes in version 1.39.6

NEW FEATURES

  • biom_to_SummarizedExperiment(): new exported function that converts a biom object into a SummarizedExperiment, placing the count/value matrix in assay(“counts”), sample metadata in colData(), and feature metadata in rowData(). Both colData and rowData are S4Vectors::DataFrame objects. When a biom object carries no metadata (the accessor returns NULL), an empty DataFrame with correct row/col names is used, ensuring the SE is always valid. No hard dependency is introduced: SummarizedExperiment and S4Vectors are listed in Suggests only.

  • as(x, “SummarizedExperiment”): S4 coercion method registered at load time when SummarizedExperiment is available, delegating to biom_to_SummarizedExperiment().

DEPENDENCY CHANGES

  • Added SummarizedExperiment and S4Vectors to Suggests.

TESTS

  • New tests/testthat/test-SE.R with 6 tests covering: return class, assay content, colData content, rowData content, S4 coercion, NULL metadata, and SE dimension/dimname correctness. All tests are skipped gracefully when SummarizedExperiment is not installed.

                     Changes in version 1.39.5

DEPENDENCY CHANGES

  • Removed plyr (>= 1.8) from Imports entirely. plyr is unmaintained and every use in this codebase now has a direct base-R equivalent. This eliminates an unmaintained dependency and reduces install footprint.

  • Bumped R dependency from >= 3.2 to >= 4.1, ensuring modern base-R idioms (including the native pipe |>) are available.

  • Replaced import(Matrix) (whole-namespace) with selective importFrom(Matrix, Matrix, sparseMatrix, drop0) in NAMESPACE. Replaced import(methods) with selective importFrom(methods, …). Follows CRAN/Bioconductor best practices; prevents namespace pollution.

USER-VISIBLE CHANGES

  • biom_data(), sample_metadata(), observation_metadata(): the parallel= argument is now a no-op with a deprecation warning when passed as TRUE. The plyr-backed parallel execution it previously enabled no longer exists. Existing code that passes parallel=FALSE (the default) is unaffected.

INTERNAL CHANGES

  • make_biom(): replaced plyr::alply() with lapply(seq_len(nrow(…))) for building per-row named metadata lists.

  • biom_data() dense path: replaced plyr::laply() with do.call(rbind, lapply(…)).

  • biom_data() sparse numeric path: replaced plyr::ldply(x$data) with do.call(rbind, lapply(x$data, as.data.frame)).

  • biom_data() sparse unicode path: replaced plyr::ldply(x$data, function…) with do.call(rbind, lapply(x$data, function(e) …)).

  • extract_metadata(): replaced plyr::llply()/plyr::ldply() with lapply() / do.call(rbind, lapply(…)).

                     Changes in version 1.39.4

BUG FIXES

  • biom_data(): fixed data-corruption bug on both dense and sparse BIOM paths where subsetting to a single row or single column silently collapsed the result into a dimensionless named vector, discarding dim(), rownames(), and colnames(). This caused downstream tools (notably phyloseq::import_biom()) to fail silently or produce incorrect OTU tables. Fix: on the sparse path, added drop = FALSE to the matrix subsetting call (m[rows, columns, drop = FALSE]). On the dense path, the laply() result is now immediately reshaped with matrix(m, nrow, ncol) before Matrix() coercion, ensuring a 2-D object is always returned regardless of dimension lengths. Closes GitHub PR #12 (https://github.com/joey711/biomformat/pull/12): “Fix biom_data() when dealing with 1-taxon and 1-sample BIOM data” Supersedes GitHub PR #11 (https://github.com/joey711/biomformat/pull/11): “Fix unidentical biom output by make_biom()”

  • biom_data(): simplified the post-subsetting naming block. Both paths now always produce a 2-D object, so rownames() and colnames() are applied unconditionally on all code paths (the previous is.null(dim(m)) branch is no longer needed).

TESTS

  • Added regression tests in tests/testthat/test-IO.R covering all new behaviour introduced across v1.39.2-v1.39.4:
    • sparse single-row subset retains dim() and dimnames (PR #12)
    • sparse single-col subset retains dim() and dimnames (PR #12)
    • sparse single-cell (1x1) subset retains dim()
    • full sparse matrix unaffected by drop = FALSE fix
    • read_biom() routes HDF5 fixture cleanly without jsonlite warning (Issue #14, PR #16)

    • read_biom() correctly classifies all JSON and HDF5 extdata fixtures

                     Changes in version 1.39.3

BUG FIXES

  • read_biom(): replaced the fragile JSON-first / HDF5-fallback try() chain with a deterministic magic-bytes router. The function now reads the first 4 bytes of the file; if the HDF5 signature (\x89 H D F) is detected it routes exclusively to read_hdf5_biom() and never invokes jsonlite. JSON files route exclusively to jsonlite. This eliminates the confusing “lexical error: invalid char in json text … <89>HDF” warning that users encountered when HDF5 files were accidentally passed through the JSON parser first. Closes GitHub Issue #14 (https://github.com/joey711/biomformat/issues/14): “Unable to read HDF5 biom file” Supersedes GitHub PR #16 (https://github.com/joey711/biomformat/pull/16): “Improve handling of HDF5 BIOM files” Partially addresses GitHub Issue #5 (https://github.com/joey711/biomformat/issues/5) and Issue #3 (https://github.com/joey711/biomformat/issues/3): fatal C-level aborts when reading large or malformed HDF5 files are now caught by the new tryCatch() wrapper in read_hdf5_biom() and re-emitted as informative R-level warnings instead of crashing the session.

  • read_hdf5_biom(): added requireNamespace(“rhdf5”, quietly = TRUE) guard. If the rhdf5 package is not installed, or if the underlying HDF5 system libraries are absent (common on stripped BBS nodes or end-user machines without libhdf5), the function now emits a clear R-level warning identifying the missing dependency and returns NULL invisibly, instead of producing a fatal C-level abort.

  • read_hdf5_biom(): wrapped the h5read() call in tryCatch() so that any C-level or system-library error is caught and re-emitted as an informative R warning, keeping the R session alive.

DEPENDENCY CHANGES

  • Bumped Matrix dependency from (>= 1.2) to (>= 1.7-0) in DESCRIPTION. This pins the package against the post-SuiteSparse ABI break and prevents runtime crashes caused by binary incompatibilities in upstream sparse-matrix libraries on BBS nodes running R 4.4+.

                     Changes in version 1.39.2

BUG FIXES

  • Fixed fatal test ERROR under testthat >= 3.0.0: replaced all deprecated expect_that(x, is_true()), expect_that(x, is_identical_to(y)), and expect_that(x, is_a(“cls”)) calls in tests/testthat/test-IO.R with their modern equivalents (expect_true(), expect_identical(), expect_is(), expect_true(is(x, “cls”))). The removed helpers caused the entire test suite to ERROR on current Bioconductor BBS nodes, which was the primary trigger for the deprecation warning. Addresses GitHub Issue #17 (https://github.com/joey711/biomformat/issues/17): “Bioconductor failure and risk of deprecation”

  • Added missing importFrom(stats, setNames) and importFrom(utils, packageVersion) directives to NAMESPACE, resolving “no visible global function definition” NOTEs from R CMD check.

blase

                    Changes in version 1.2.0

Major changes

  • “confident_mapping” has now been renamed as “strong_mapping” to indicate that it is not a robust statistical confidence. The confident_mapping() getter function has been renamed to strong_mapping()
  • plot_mapping_result_heatmap() annotate_confidence parameter has been renamed to annotate_strong.

Minor improvements and bug fixes

  • Now possible to use BLASE to create pseudotime bins from multiple trajectories at once.
  • Speeds up by cell pseudotime bin assignment.
  • Possible to apply different metrics for judging the best mapping. Spearman is still recommended.
  • It is now possible to rename a bulk sample for a MappingResult object.
  • MappingResult heatmaps no longer convert the Y-axis titles (bulk sample name) to character, allowing numeric style scales.

bnbc

                    Changes in version 1.33
  • Replaced HiCBricks with direct rhdf5 calls in getChrCGFromCools to fix a segfault in HDF5 cleanup that was crashing the vignette build. HiCBricks is no longer a dependency.

BreastSubtypeR

                    Changes in version 1.3.2

Highlights (from v1.1.3 onward)

  • Paper published in NAR Genomics and Bioinformatics (2025), Editor’s Choice (DOI: 10.1093/nargab/lqaf131).
  • Support for raw RNA-seq counts (requires gene lengths).
  • iBreastSubtypeR refresh: cleaner UX, smarter AUTO guidance, consistent exports.

Enhancements

  • ssBC/ssBC.v2: singleton subgroup robustness: Subgroups with n=1 no longer error:
  • Keeps matrix shape (drop=FALSE) and hardens dimnames/types.
  • Primary path: original sspPredict(). Fallback: nearest-centroid (Spearman) when needed.
  • If there are 0 common PAM50 genes, returns NA labels with shaped distances/dist.RORSubtype to avoid downstream errors.
  • ROR computation guarded for incomplete inputs.
  • SSPBC output now “full”: BS_sspbc() and Shiny “sspbc” runs return a full metrics table (not calls-only).
  • Exports map core label columns to the standard names (Call_5class / Call_4class when applicable).
  • Shiny: “Load example data…” button
  • One-click load of a small demo dataset from inst/RshinyTest/ to explore the UI without uploads.\
  • Shows a notification on success; users can immediately run Preprocess & map and analyses.
  • AUTO preflight UI (Shiny): Now detects cohort kind (TN, ER/HER2, ER-only, HER2-only) and shows compact stats:
  • ER/HER2 subgroups: ER+/HER2-, ER-/HER2-, ER+/HER2+, ER-/HER2+\
  • TN cohorts: TN vs nonTN\
  • Readiness uses the same minimums used by AUTO (sourced programmatically; no duplicated thresholds).
  • Shorter notifications. -Routine toasts (e.g., “Step 1 complete. Proceed to Step 2.”) now auto-dismiss sooner to reduce UI clutter.
  • Phenodata normalization (Mapping): Accepts flexible ER/HER2/TN encodings and normalizes to canonical forms (ER+/ER-, HER2+/HER2-, TN/nonTN). Ambiguous HER2=”2+” remains as-is and raises a warning.

Bug fixes

  • TN cohorts + ssBC: BS_Multi() now respects TN cohorts when methods are specified manually; ssBC/ssBC.v2 switch to s = “TN” / “TN.v2” when a TN column indicates a TN cohort. Falls back to s = “ER” / “ER.v2” otherwise.
  • AUTO: Fixed a crash in BS_Multi(methods=”AUTO”) when ER and/or HER2 contained missing values (NA).
  • AUTO internals: fixed variable name typo (samples_ERHER2.icd).
  • Mapping(): Robust ENTREZID coercion (from as.character() to as.integer() with suppressed warnings).
  • cIHC.itr: outList$distances now returned as numeric matrix.

Shiny

  • Surface method warnings as toasts:
  • Runs are wrapped in a warning handler; package warnings (e.g., ssBC.v2 singleton fallbacks) appear as yellow notifications.\
  • Warnings include subgroup, n, and example sample IDs for quick triage.
  • Shiny preflight reset:
  • Fixed a stale cohort summary after switching data sources (manual uploads ↔ example). The preflight panel now revalidates once inputs change.

Developer notes

  • Added lightweight internal logger ._msg() and replaced scattered message() calls in AUTO to standardize package output without affecting CRAN/Bioc checks.

Documentation

  • README/vignette: brief note on the example-data button and expected file locations.
  • Mapping(): Column metadata clarified. Added explicit requirements for receptor fields used by AUTO and ER/HER2/TN-dependent methods (ssBC, cIHC/cIHC.itr, PCAPAM50) and for ROR covariates (TSIZE, NODE as numeric 0/1). Documented preferred coding and automatic normalization behavior.

Compatibility Notes

  • SSPBC “full” output keeps previous columns for calls; additional metrics may appear.

Upgrade Notes

  • Raw RNA-seq counts are supported from v1.1.3 onward (requires gene lengths).
  • If you previously parsed BS / BS.Subtype, switch to Call_5class / Call_4class.
  • Package API unchanged.

bsseq

                    Changes in version 1.47
  • Making read.modkit() and read.modbam2bed() defunct.

CalibraCurve

                    Changes in version 1.1.4

  • readDataTable() can now import a file containing data for multiple substances

                      Changes in version 1.1.3

  • small fix in documentation

                      Changes in version 1.1.2
  • Allow calculation of calibration curves with only one replicate per concentration level.
  • Fix bug when input data is not ordered by concentration column
  • Allow legend and add title to response factor plots
  • Add new Logo to readme

  • Fix bug when unequal numbers of replicates per concentration level are present

                      Changes in version 1.1.1

Bugfixes

Cardinal

             Changes in version 3.13.4 (2026-04-24)

Major changes

  • Converted NEWS to NEWS.md

Major changes

  • Removed deprecated functions (color palettes, etc.)
  • Removed defunct functions (color palettes, etc.)

  • Deprecated ‘fetch()’ and ‘flash()’

               Changes in version 3.13.2 (2026-04-22)

Bug fixes

  • Fix ‘mass.range’ bug in ‘convertMSImagingExperiment2Arrays()’

               Changes in version 3.13.1 (2026-03-18)

Major changes

  • Remove dependency on EBImage

               Changes in version 3.12.1 (2026-02-12)

Bug fixes

  • Add na.rm parameter to ‘meansTest()’
  • Fix spectrumRepresentation logic in ‘writeImzML()’
  • Rename ‘bi’ to ‘bilateral’ in smoothing functions

carnation

                   Changes in version 0.99.10
  • carnation submitted to bioconductor

CDI

                    Changes in version 1.9.0
  • Package accepted by Bioconductor (2023-06-30)

CellMentor

             Changes in version 0.99.1 (2024-10-27)
  • Initial Acceptance to Bioconductor

cellmig

                    Changes in version 1.1.8

  • Unit tests fixed for Bioconductor release

                      Changes in version 1.1.7

  • Stable version used for publication

ChIPpeakAnno

                   Changes in version 3.45.3

  • Fix the issue for biomaRt in vignettes.

                     Changes in version 3.45.2

  • Remove microRNAs from annoGR

                     Changes in version 3.45.1

  • Remove microRNAs from assignChromosomeRegion.

ChIPseeker

                   Changes in version 1.47.1
  • fixed issue in ‘test-txdb.R’ as ‘TxDb.Hsapiens.UCSC.hg19.knownGene’ changes its transcript ID from UCSC (e.g., uc002qsd.4) to Ensembl (e.g., ENST00000487630.1_3) (2025-11-04, Tue)

Chromatograms

                     Changes in version 1.1

Changes in 1.1.8

  • Improve performance of matchRtime().

  • Fix compareChromatograms(): … arguments (e.g. tolerance) are now routed to MAPFUN or FUN based on their formal parameters, preventing errors when FUN = cor received unknown arguments.

Changes in 1.1.7

  • Improve performance of .prepare_spectra_input(): spectra are now pre-filtered to the non-overlapping union of EIC retention time ranges using MsCoreUtils::reduce() and Spectra::filterRanges(), and peak data is loaded in a single peaksData() call instead of separate mz() and intensity() calls. This reduces I/O and memory usage, especially for file-backed backends.

Changes in 1.1.6

  • Add compareChromatograms() and matchRtime() for pairwise similarity of chromatographic intensity profiles.

Changes in 1.1.5

  • Add peakBoundary() method for Chromatograms objects. Determines the retention time boundaries of the tallest peak in each chromatogram using MsCoreUtils::valleys() to locate flanking valleys, with a threshold-based fallback. Returns a matrix with left_boundary and right_boundary columns.

Changes in 1.1.4

  • setBackend() now clears the processing queue after switching backend, preventing queued processing steps from being applied twice (once during the data transfer and again on subsequent peaksData() calls).

  • Fix setBackend() parallel branch (used for ChromBackendMzR) to correctly apply queued processing steps to each chunk before transferring data to the new backend.

  • Major performance improvement in .process_peaks_data() for ChromBackendSpectra. Key optimizations include: pre-extracting mz() and intensity() as plain R lists (avoiding slow SimpleNumericList indexing), global retention time pre-filtering, a fast path for TIC/BPC cases, and using findInterval() with cumsum() for m/z range lookups. Combined, setBackend() showed 9x speed up for 1000 chromatograms.

  • Add optimized intensity() and rtime() accessors for ChromBackendMemory using direct [[ extraction instead of the slower [, col, drop] path through peaksData().

  • Further accessor optimizations: intensity(), rtime(), and lengths() on Chromatograms now bypass peaksData() dispatch when the processing queue is empty. peaksData() on ChromBackendMemory uses a fast [[ path for single-column requests. Direct lengths() methods added for all backends using nrow() instead of going through intensity().

  • Replace do.call(rbind, …) with data.table::rbindlist() in chromExtract() for ChromBackendMemory, ChromBackendMzR, and ChromBackendSpectra for faster row-binding of many data.frames.

  • Replace replicate(n, .EMPTY_PEAKS_DATA, simplify = FALSE) with rep(list(.EMPTY_PEAKS_DATA), n) across backends to avoid repeated expression evaluation overhead.

Changes in 1.1.3

  • Add filterEmptyChromatograms() function to remove empty chromatograms (i.e., chromatograms without peaks) from a Chromatograms or ChromBackend object.

  • Add concatenateChromatograms() function and c() method to combine multiple Chromatograms objects into a single object. Also add split() method to split a Chromatograms object based on a grouping factor.

  • Add extrapolate parameter to imputePeaksData() (default FALSE). When TRUE, leading/trailing NA values outside the range of observed data are extrapolated. When FALSE (default), only interpolation is performed and edge NA values remain as NA.

Changes in 1.1.2

  • Fix peaksData() for ChromBackendSpectra to return data in the correct row order when multiple chromatograms share the same chromSpectraIndex. This bug caused setBackend() to produce mismatched chromData and peaksData when converting from ChromBackendSpectra to ChromBackendMemory with objects containing multiple EICs.

Changes in 1.1.1

  • Aligned the package with the Bioconductor 3.22 release.
  • Expanded the vignette to cover ChromBackendSpectra usage, chromatogram extraction with chromExtract(), and imputation workflows via imputePeaksData().
  • Added spectraSortIndex() for ChromBackendSpectra to compute the desired retention-time order on demand, avoiding the need to keep on-disk Spectra objects sorted in memory.

ClonalSim

                   Changes in version 0.99.6

Initial Acceptance to Bioconductor

ClusterGVis

             Changes in version 0.99.0 (2025-08-01)

Initial Acceptance to Bioconductor

clusterProfiler

                   Changes in version 4.19.8

  • fix: map non-ENTREZID universe in enrichGO (2026-04-22, Wed)

                     Changes in version 4.19.7

  • interpret(), interpret_agent(), and interpret_hierarchical() now use aisdk’s global default model when model = NULL, so users can switch the package-wide default with aisdk::set_model() while still overriding per call with an explicit model argument (2026-03-31, Tue)

                     Changes in version 4.19.6
  • update ko2name() to robustly parse KO names via KEGG REST, support vector input with deduplication, and return NA when NAME is missing (2026-02-25, Wed)

  • bug fixed for plot.interpret (2026-02-05, Thu)

                     Changes in version 4.19.5
  • interpret() prompt optimized with ‘Comparative Analysis’ and ‘Rule of Exclusion’ to better distinguish cell types with shared functions (e.g. NK vs CD8+ T cells) using specific marker genes (2026-01-22, Thu)
  • fixed a bug in interpret() where empty interpretation results were returned due to incorrect list structure handling in process_enrichment_input (2026-01-22, Thu)
  • interpret() now considers specific marker genes in cell type annotation to avoid key markers being overshadowed by general pathways (2026-01-21, Wed)
  • optimize enrichGO() to avoid memory boom when keyType is not ENTREZID (2026-01-21, Wed, #805)
  • gson_GO_local() to support local GO annotation by adding ancestral terms (2026-01-21, Wed)
  • interpret() implements a gene-based fallback mode for clusters with no enriched pathways, ensuring comprehensive analysis (2026-01-20, Tue)
  • plot() method for interpretation object to visualize the LLM-inferred regulatory network using ggtangle (2026-01-20, Tue)
  • interpret_agent() supports multi-agent system (Deep Mode) for interpretation (2026-01-20, Tue)
  • Agent Cleaner: Filters noise and selects relevant pathways
  • Agent Detective: Identifies key regulators and functional modules using PPI/TF data
  • Agent Synthesizer: Synthesizes findings into a coherent narrative
  • interpret() supports ‘Knowledge-Guided Interpretation’ (2026-01-20, Tue)
  • add_ppi parameter to integrate PPI network and identify hub genes
  • gene_fold_change parameter to incorporate expression levels
  • Mixed-source enrichment analysis support (e.g. Pathways + TFs) for causal integration
  • LLM-guided network refinement to output core regulatory networks
  • interpret_hierarchical() for hierarchical interpretation (e.g. Major -> Minor clusters) (2026-01-20, Tue)

  • interpret() now supports prior parameter for reference-guided interpretation (e.g. from SingleR/scGPT) (2026-01-20, Tue)

                     Changes in version 4.19.4
  • interpret() now supports task parameter to specify the task: ‘interpretation’, ‘annotation’ and ‘phenotyping’ (2025-01-18, Sat)

  • interpret() supports enrichResult, gseaResult, compareClusterResult and list of enrichment results (2025-01-18, Sat)

                     Changes in version 4.19.3
  • instead of packing KEGG cache data in the package, we now download it from https://yulab-smu.top/clusterProfiler (2025-12-15, Mon)
  • add github action to automatically update KEGG cache data (2025-12-09, Tue)

  • use ‘enrichit’ as engine for enrichment analysis (2025-12-07, Sun)

                     Changes in version 4.19.2
  • use ‘quarto’ as vignette engine (2025-11-20, Thu)
  • update KEGG cache data (2025-11-20, Thu, #792)
  • number of KEGG pathway with category information: 582

  • Number of species: 11344

                     Changes in version 4.19.1
  • bug fixed in enrichPC (2025-11-01, Sat, #789)

ClustIRR

                   Changes in version 1.9.25

  • move from CRAN’s blaster to Bioconductors rBLAST

                     Changes in version 1.9.17

  • quantiative comparison community abundance with normalized rank abundance distributions (NRADs) implemented in get_nrad()

                     Changes in version 1.9.10
  • bigfixes in joint graph building
    • when clustering both CDR3a/CDR3b, CDR3b edges between-repertoires got deleted

    • one between-repertoire edge between two clones with double edges was deleted

                      Changes in version 1.9.9

  • get_blosum() bugfix -> identical CDR3 did not form edges in certain cases

  • added test-get_blosum.R

                      Changes in version 1.9.2

  • K-nearest-neighbor approximation implemented

  • get_cosine_similarity to compare community abundance overlap

CNVMetrics

                   Changes in version 1.15.2

BUG FIXES

  • The parameter names of the generic functions have been updated to fit requirement.

                     Changes in version 1.15.1

NEW FEATURES

  • The documentation has been updated.

CompensAID

                   Changes in version 0.99.7
  • Initial Acceptance to Bioconductor

CompoundDb

                    Changes in version 1.15

Changes in version 1.15.4

  • Support filling missing columns/spectra variables in HMDB import.

Changes in version 1.15.3

  • Use data.table::rbindlist() to combine MS spectra for HMDB import improving its performance.

Changes in version 1.15.2

  • Change internal mapping of the precursorIntensity spectra variable to a database table name from “precursor_intensity” to “precursorIntensity”.

Changes in version 1.15.1

  • Add addJoinDefinition() function to define relationships between core database tables and newly added tables.

COTAN

                   Changes in version 2.11.4

Added new vignette for Differential Expression Analysis

Fixed minor bug in clustersMarkersHeatmapPlot() about genes duplication in markers’ list

Refactored vignette into 3 separate files for improved theme focus

Allowed the function calculatePValue() to run on multiple cores

Added parameter minimumUTClusterSize to cellsUniformClustering() function

                   Changes in version 2.11.3

Solved various linting issues and BiocCheck warning

Now the function canUseTorch() is exported

                   Changes in version 2.11.2

Improved conversions to/from SingleCellExperiment objects

Solved inconsistencies in cell/genes names between raw data and meta-data

Improvements for plot functions:

  • fixed label placements genes’ plot in cleanPlots()

  • added genesPercentagePlot() as generalization of mitochondrialPercentagePlot()

                     Changes in version 2.11.1

Fixed issue with isCoexAvailable() for cases when the global meta-data have multiple columns

Fixed issue with dispersion solver

Dropped dependency from gghalves package as it is deprecated: using ggdist instead

                   Changes in version 2.11.0

Moved to new version

CPSM

                    Changes in version 1.3.1

Updates

  • Enhanced Lasso_PI_scores_f.R to compute the feature Stability Index and updated Univariate_sig_features_f.R to include the Proportional Hazards (PH) violation test for selected features.
  • Updated MTLR_pred_model_f.R and predict_survival_risk_group_f.R to generate results for each cross-validation fold.
  • Improved train_test_normalization_f.R by adding an additional filter to remove features with zero variance in at least 80% of training samples.
  • Revised vignettes/CPSM.Rmd with improved descriptions and a clearer workflow.
  • Updated tests/testthat files to reflect recent changes.
  • Updated the DESCRIPTION file:

  • Version bumped from 1.3.0 to 1.3.1.

                      Changes in version 1.3.0

Updates

  • Updated Lasso_PI_scores_f.R, MTLR_pred_model_f.R, Univariate_sig_features_f.R, km_overlay_plot_f.R, mean_median_surv_barplot_f.R, surv_curve_plots_f.R, predict_survival_risk_group_f.R to provide customization for user in cross-validation , Font-size and figure styling etc.
  • Updated MTLR_pred_model_f.R to compute IBS (integrated brier score)
  • Updated vignettes/CPSM.Rmd to provide improve description and workflow
  • Updated tests/testthat files to incoprate updated changes
  • Updated DESCRIPTION file:
  • Bumped version from 1.2.0 to 1.3.9.

CrcBiomeScreen

             Changes in version 0.99.0 (2025-10-21)

Overview

CrcBiomeScreen is an R package designed to streamline microbiome-based colorectal cancer (CRC) screening workflows. It provides standardized functions for preprocessing, taxonomic data handling, machine learning model training, and cross-cohort validation — supporting reproducible and interpretable microbiome analysis for biomarker discovery.

This version marks the first public release of the package, submitted to Bioconductor.

New Features

Data Processing

  • SplitTaxas() now automatically detects taxonomy separators (supports |, ., _, and ;) to handle common formats from MetaPhlAn, QIIME, etc. Adds:

  • OriginalTaxa column to retain the raw taxonomy string.

  • Special handling for uncultured and unclassified taxa (e.g. converts f__Rikenellaceae|g__unclassified → Rikenellaceae_unclassified).

  • KeepTaxonomicLevel() filters data at a user-defined rank (e.g., Genus, Family, Species) and automatically collapses lower-level abundances. Handles multiple nested unclassified levels (e.g., D_2__Clostridia.D_3__uncultured.D_4__uncultured).

Machine Learning

  • TrainModel() serves as a unified interface for training Random Forest (RF) and XGBoost classifiers.

  • Integrates with internal preprocessing and class-weight balancing.
  • Uses withr::with_seed() for local reproducibility instead of set.seed().

  • Adds support for both training and external validation workflows.

  • EvaluateRF() and EvaluateXGBoost() now return standardized performance metrics (AUC, accuracy, recall, F1) and store model outputs in the main object structure.

  • ValidateModelOnData() supports model evaluation across independent datasets.

Data Object Structure

  • Introduced the CrcBiomeScreenObject class to store:
  • Absolute and relative abundance tables
  • Taxonomic annotations
  • Model training results
  • Validation data and predictions
  • Visual outputs (e.g., ROC, variable importance)

This ensures data provenance and reproducibility across the full workflow.

Utility and Visualization

  • Added built-in plotting functions for:
  • Model ROC curves (PlotAUC)

Documentation and Testing

  • Added comprehensive vignette:

  • Demonstrates preprocessing, genus-level filtering, model training, and validation.

  • Includes examples for multiple taxonomy formats and classifier comparisons.

  • Implemented unit tests under tests/testthat/ for key components:

  • Taxa splitting
  • Level filtering
  • Model reproducibility

Technical and Compliance Updates

  • Adopted MIT license.
  • Added BugReports and URL fields in DESCRIPTION.
  • Removed unnecessary system files (.Rproj, .DS_Store).
  • Replaced all instances of set.seed() with withr::with_seed() for Bioconductor compliance.
  • Reduced hard-coded dependencies and improved optional imports.

Future Plans

  • Add support for additional classifiers.
  • Integrate feature interpretation.
  • Provide reproducible benchmarking across public CRC datasets.

Version 0.99.13

  • Fixed vignette and example issues
  • Temporarily disabled XGBoost execution due to compatibility issues with caret
  • Improved documentation and S4 accessor usage

Version 0.99.14(2026-04-10)

  • runnable toy workflow added to vignette
  • examples updated for TrainModels, ValidateModelOnData, RunScreening
  • documentation for included datasets completed

Version 0.99.15(2026-04-14)

  • Standardized the format of the vignette and documentation

Maintainer: Chengxin Li (University of Leeds) Date: 2025-10-21 License: MIT Repository: https://github.com/omicsForestry/CrcBiomeScreen

crisprBwa

                   Changes in version 1.15.1
  • Removed bbsoptions file

crisprDesign

                   Changes in version 1.13.10

  • Added optional argument substitutions to addEditedAlleles”

                     Changes in version 1.13.9

  • Fixed condaEnv argument for addOnTargetScores

                     Changes in version 1.13.8

  • SNPs can now be annotated from a GRanges object.

                     Changes in version 1.13.6

  • Fixed splicing junction aa annotation when low scores

                     Changes in version 1.13.4

  • Fixed the accessor editedAlleles.

                     Changes in version 1.13.1

  • Added more annotation columns to the addEditedAlleles function.

crisprScore

                   Changes in version 1.15.2

  • Conda environment now have to be built outside of crisprScore.

  • The tracer argument for RuleSet3 is now fixed; the previous version of crisprScore was now taking into account the tracer, and the Chen2013 tracer was always used.

                     Changes in version 1.15.1

  • The scores developed in Python 2 are no longer available: DeepSpCas9, DeepCpf1, Azimuth, and the crisprai scores.

crisprShiny

                    Changes in version 1.7.2
  • Removed deprecated Azimuth scores.

CSOA

             Changes in version 1.1.1 (2025-11-11)

  • Changed the implementation of multiple correction testing methods and the default to Benjamini-Hochberg.

  • Added an error check for gene signatures containing repeated genes

CytoMDS

                     Changes in version 1.7

CytoMDS 1.7.2

  • added ggplotVolcano()

CytoMDS 1.7.1

  • fixed unti tests with new version of ggplot2

CytoML

                    Changes in version 3.11

API Changes

  • Rename argument sampNLoc -> sample_names_from in open_flowjo_xml
  • All parsers (flowjo/cytobank/diva_to_gatingset) now return GatingSet based on cytoset rather than ncdfFlowSet
  • Add trans argument to cytobank_to_gatingset to allow overriding of transformations from gatingML file (#76)
  • gatingset_to_flowjo now uses a docker image with a compiled converter: hub.docker.com/r/wjiang2/gs-to-flowjo
  • Some updates to how flowjo_to_gatingset searches for FCS files (#77)
  • Add include_empty_tree option to flowjo_to_gatingset to include samples without gates
  • Allow gatingset_to_flowjo to take a path to a GatingSet archive directory
  • Add gating_graphGML to replace gating.graphGML method for openCyto::gating generic
  • Filter samples by panel when parsing cytobank experiment and add ce_get_samples, ce_get_panels

Fixes/internal changes

  • Automatic time scaling of samples from FlowJo workspaces now handled by flowjo_to_gatingset RGLab/cytolib#33
  • Handle change to default stringsAsFactors=FALSE in R 4.0
  • Eliminated extra intermediate files left in temp directory during workspace parsing
  • Switch usage of GatingSetList to merge_gs_list
  • Solve some Windows build issues
  • Switch from experimental::filesystem to boost::filesystem in C++ FlowJo parser

  • Add CytoML XSD to installation

                      Changes in version 3.10

API Changes

  • Change handling of quad gates according to RGLab/cytolib#16

  • Renaming of methods:

  • openWorkspace -> open_diva_xml, open_flowjo_xml
  • cytobankExperiment -> open_cytobank_experiment
  • cytobank2GatingSet -> cytobank_to_gatingset
  • parseWorkspace -> flowjo_to_gatingset, diva_to_gatingset
  • getSampleGroups -> fj_ws_get_sample_groups, diva_get_sample_groups
  • getSamples -> fj_ws_get_samples, diva_get_samples
  • getKeywords -> fj_ws_get_keywords
  • getCompensationMatrices -> ce_get_compensations
  • getTransformation -> ce_get_transformations

  • compare.counts -> gs_compare_cytobank_counts

  • Renaming of classes:

  • divaWorkspace -> diva_workspace

  • flowJoWorkspace -> flowjo_workspace

  • Add CytoML.par.set, CytoML.par.get for setting parameters in CytoML namespace

Fixes/internal changes

  • Make gatingset_to_cytobank export cytobank ML with attribute namespaces
  • Allow diva_to_gatingset to use compensation matrix from xml
  • Pass … args from cytobank_to_gatingset appropriately down to FCS parser
  • Fix some issues with scaling of gates parsed from Diva workspace (#64)
  • Guard against unsupported transformations being added to GatingSet during Diva parsing
  • Switch diva_to_gatingset to using flowjo_log_trans instead of logtGml2_trans
  • Fix ported flowUtils::xmlTag to enable self-closing tags
  • Make gating.graphGML lookup tailored gates by FCS name as well as file id
  • Add some flexibility to getSpilloverMat used in gatingset_to_flowjo

CytoPipeline

                    Changes in version 1.11

CytoPipeline 1.11.1

  • Bug correction for scale transfo pipelines with sample specific data: implemented a work-around in readSampleFiles(): forced flowSet sample names to full file paths as this was not done automatically by flowCore::read.flowSet().
  • estimateScaleTransforms() now has … in parameter list, allowing to pass additional parameters to flowCore::estimateLogicle().

CytoPipelineGUI

                     Changes in version 1.9

CytoPipelineGUI 1.9.1.

  • bug correction: since version 1.7.2, it was no more possible to display flowFrames from the scale transformation pipeline part => this has been corrected
  • bug correction: logicle transform now uses all (t,m,w,a) parameters. Previously, t (maximum scale) was always set to a default value hence providing wrong visualization => this has been corrected.

damidBind

                   Changes in version 0.99.14
  • Initial Acceptance toBioconductor.

decemedip

                   Changes in version 0.99.8
  • Initial Acceptance to Bioconductor

DeconvoBuddies

                    Changes in version 1.3.3

NEW FEATURE

  • plot_gene_express() now has option to add label points with parameter label_points.

                      Changes in version 1.3.2

NEW FEATURES

  • findMarkers_1vAll() now only returns standardized log fold-change values, which cuts default run time roughly in half. A new parameter raw_logFC has been added; when TRUE, it yields the old behavior of returning both versions of the log fold-change.

  • findMarkers_1vAll() can now be parallelized with near-linear speedup via a new BPPARAM parameter.

                      Changes in version 1.3.1

NEW FEATURES

  • get_mean_ratio() has a new BPPARAM parameter allowing parallelization. Run time without parallelization was also marginally improved.

DeeDeeExperiment

                    Changes in version 1.2.0

  • The dea and fea slots now use S4Vectors::SimpleList instead of base list

  • The DEA original objects are no longer stored in the dea slot. They are now stored under metadata(dde)$singlecontrast or metadata(dde)$multicontrast, and each contrast entry in the dea slot contains a pointer to its original object

  • Added helper functions to simplify inserting DE results from muscat::pbDS() and MArrayLM object with multiple contrast into a dde object

  • Added a helper function to export results stored in dea and fea slots as excel files

  • Improved warning messages

  • A new vignette showcasing how to apply DeeDeeExperiment to a single-cell dataset

  • Updating citation since the DeeDeeExperiment paper is out!

deepSNV

             Changes in version 1.99.3 (2013-07-25)

Updates

  • A few changes to shearwater vignette

  • Renamed arguments pi.gene and pi.backgr in makePrior()

Bugfixes

  • Fixed bug in bf2Vcf() when no variant is called

               Changes in version 1.99.2 (2013-07-11)

Updates

  • Updated CITATION

  • Added verbose option to bam2R to suppress output

  • Changed mode() to “integer” for value of loadAllData()

Bugfixes

  • Fixed bug when only one variant is called in bf2Vcf()

               Changes in version 1.99.1 (2013-06-25)

Updates

  • Using knitr for prettier vignettes

  • Including shearwater vignette

Bugfixes

  • fixed issues with deletions in bf2Vcf()

  • makePrior() adds background on all sites

               Changes in version 1.99.0 (2013-04-30)

Updates

  • New shearwater algorithm

  • Including VCF output through summary(deepSNV, value=”VCF”)

DeMixT

                    Changes in version 2.0.0
  • Added DeMixNB: a negative binomial deconvolution method for sparse count data.

DenoIST

             Changes in version 0.99.4 (2026-03-17)
  • Initial Acceptance to Bioconductor

DESeq2

                   Changes in version 1.51.3
  • Numerous partial matching fixes from Hugo Gruson.

DESpace

                    Changes in version 2.3.2
  • add quasi-likelihood F tests

DFplyr

                    Changes in version 1.6.0

NEW FEATURES

  • Fixed column-wise slicing
  • Aligned to S4Vectors updates

SIGNIFICANT USER-VISIBLE CHANGES

  • Grouped DataFrame now appears as a new class GroupedDataFrame with its own dispatched methods

DMRcaller

                   Changes in version 1.42.1

  • Added functions to read Oxford Nanopore methylation data from Dorado bam files

  • Added functions to detect Partially Methylated Domains PMDs

  • Added functions to detect Variably methylated domains (VMDs) using ONT data

  • Added functions to detect Variably Methylated Regions (VMRs) using ONT data

  • Added functions to detect co-methylation using ONT data

  • Updated parallel computing to use BiocParallel

dominatR

                   Changes in version 0.99.4
  • Initial Acceptance to Bioconductor

dominoSignal

                    Changes in version 1.6.0

New Features

  • Added print() and show() methods for linkage_summary objects to provide concise summary output.

Bug Fixes

  • Fixed create_rl_map_cellphonedb() handling of partner B complex mappings and gene assignment.
  • Fixed gene_network() to avoid repeated prefixing of outgoing cluster names and to correctly subset outgoing signaling matrices.
  • Fixed gene_network() to only include receptor and TF nodes that are associated with a ligand if OutgoingSignalingClust is used.
  • Fixed gene_network() to accumulate ligand expression across clusters for ligand node scaling.
  • Fixed signaling_network() to assign undefined (NA) vertex sizes to 0 when scaling by signaling.
  • Fixed dom_linkages() with by_cluster = TRUE and link_type = “tf-receptor” to return clust_tf_rec.
  • Fixed dom_signaling(cluster = …) to return the selected cluster matrix via list indexing.

Documentation

  • Added figure alt text to images in vignettes for accessibility.
  • Updated pkgdown and vignette links to use working URLs.
  • Updated README/index documentation links and citation text to current release metadata.

DOSE

                    Changes in version 4.5.1
  • mv get_organism to ‘GOSemSim’ (2025-12-07, Sun)
  • update enrichment functions to use ‘enrichit’ (2025-12-05, Fri)
  • mv enricher_internal and GSEA_internal to the ‘enrichit’ package (2025-12-05, Fri)
  • renamed to ora_gson and gsea_gson with updates
  • mv helper functions to ‘enrichit’

DOtools

                    Changes in version 1.1.8

All notable changes to DOtools will be documented in this file.

[1.1.8] - 2026-04-13

Added

  • Added citation from Bioinformatics Advances since it got published.

Changed

  • DO.UMAP: Is now able to plot a DensityPlot for provided genes.

[1.1.2] - 2026-01-13

Added

  • DO.HeatmapFC: Heat map function for foldchange visualisation, includes statistics about significance.
  • DO.Barplot: New barplot function with more testing methods.

Changed

  • Major adjustments to DO.VlnPlot and DO.Barplot. These functions now take multiple testing methods and correction methods. Will be applied also to DO.BoxPlot.
  • Major bug fixes for comparability with Seurat’s newest version.

Removed

  • DO.BarplotWilcox: Replaced by DO.Barplot

DOTSeq

                   Changes in version 0.99.8
  • Accepted into Bioconductor

drawProteins

                    Changes in version 4.0.0

  • Changing tests based on an updated version of ggplot2 to 3.5.0 which changes the length of the ggplot object. ARGUMENT

  • Replace size with linewidth in function draw_chain() following a depreciation in ggplot.

dreamlet

                    Changes in version 1.9.2
  • fixed failed check

DropletUtils

                   Changes in version 1.32.0
  • Updated downsampleReads() to use the new downsampling algorithm from scuttle. This is more efficient but slightly changes the results compared to the previous version.

drugfindR

  • Initial Acceptance to Bioconductor

edgeR

             Changes in version 4.10.0 (2026-04-25)

  • catchOarfish() now uses nanoparquet::read_parquet() instead of arrow::read_parquet().

  • New function DGEListFromTximport() to assemble a DGEList object from the list object created by tximport::tximport.

  • New function DGEListFromTximeta() to assemble a DGEList object from the list object created by tximeta::tximeta.

  • glmQLFit() with legacy=FALSE now caps any preset dispersions to be <= 4. Previously, large preset dispersions could lead to a segmentation error.

  • glmQLFit() with legacy=FALSE no longer automatically estimates the NB dispersion from trended values found in the DGEList object, if present. The results will now be the same whether the DGEList contains dispersion estimates or not.

  • New function sampleWeights() to estimate sample weights from a matrix of adjusted unit deviances.

enrichplot

                   Changes in version 1.31.5
  • cnetplot.compareClusterResult() now supports categorySizeBy for category pie sizing and aligns docs with ggtangle::cnetplot() semantics (2026-04-22, Wed)
  • ridgeplot now supports stat parameter (default is ‘density_ridges’ and can be changed to ‘binline’) (2026-04-01, Wed, #343)
  • manhattan plot for enriched result (2026-03-26, Thu)
  • update roxygen document to use markdown syntax (2026-03-02, Mon)
  • bug fixed in xy-lab format in ssplot() (2026-03-02, Mon)

  • bug fixed in formula supports in dotplot() (2026-02-26, Thu)

                     Changes in version 1.31.4
  • fix cnetplot() S3 generic/method consistency warnings (2026-01-14, Wed)
  • fix treeplot() column selection bug when color variable equals size variable (2026-01-14, Wed)
  • fix fortify.compareClusterResult() warnings about missing imports and global variables (2026-01-14, Wed)
  • remove plyr and use dplyr in method-fortify.R (2026-01-14, Wed)
  • fixed treeplot() issue where pairwise_termsim() with method=”JC” produced unnamed similarity matrix, causing “undefined column selected” error (2025-01-14)
  • fixed fortify.compareClusterResult() warning “NAs introduced by coercion” when Cluster names are not numeric (2025-01-14)
  • bug fixed in barplot() as fortify() generic in ggplot2 checks for unused arguments in … (2026-01-14, Wed)
  • remove categorySize parameter in cnetplot() (2026-01-14, Wed)
  • bug fixed in goplot() as GOSemSim uses cache (2026-01-13, Tue)
  • also fix gotbl object not found issue (2026-01-13, Tue)
  • re-export geneID, geneInCategory and gseaScores from ‘enrichit’ (2026-01-12, Mon)
  • update documentation: fix typos, grammar errors and use modern markdown syntax (2026-01-12, Mon)
  • bug fixed in update_n() if showCategory is a vector of term names (2026-01-08, Thu)

  • avoid the “condition has length > 1” error in outer() by using Vectorize() (2026-01-08, Thu)

                     Changes in version 1.31.3
  • use ‘enrichit’ package (2025-12-07, Sun)
  • optimize source code (2025-12-02, Tue)

  • error handling functions imported from ‘yulab.utils’ (2025-12-01, Mon)

                     Changes in version 1.31.2
  • add ‘fc_threshold’ parameter to cnetplot (2025-11-30, Sun, #338)
  • requires ‘ggtangle’ v>= 0.0.9
  • update all line width aes mapping from ‘size’ to ‘linewidth’ (2025-11-30, Sun)
  • add ‘node_label_size’ parameter for emapplot (2025-11-30, Sun)
  • remove emapplot parameters, ‘group’, ‘group_style’ and ‘label_group_style’ (#339)

  • add ‘showTop’ parameter to limit number of genes shown in heatplot() and distinguish tip point size variable for treeplot() through internal parameter size_var (2025-11-23, Sat, #335)

                     Changes in version 1.31.1
  • import ggfun::%<+% (2025-11-18, Tue)
  • update ssplot(), treeplot() and get_wordcloud() (2025-11-15, Sat)
  • change set_enrichplot_color(transform = ‘identity’) as default behavior (2025-11-11, Tue)
  • now it only sets the color scale without changing the transform method
  • explicitly set transform = ‘log10’ in dotplot
  • use ‘quarto’ as vignette engine (2025-11-11, Tue)
  • use set_enrichplot_color(transform = ‘identity’) in heatplot (2025-11-11, Tue)
  • use set_enrichplot_color(transform = ‘identity’) in cnetplot (2025-11-05, Wed)

epialleleR

             Changes in version 1.19.3 (2026-01-25)

  • checks conventional base probabilities in long-read data

  • accuracy comparison vs modkit

               Changes in version 1.19.2 (2026-01-19)

  • limit/clip reads to targets during BAM loading

  • filtering by number of context sites

  • new defaults for filtering

               Changes in version 1.19.1 (2026-01-02)

  • API change for thresholding in all ‘generate*Report’ functions

  • filtered out reads are dropped and not counted as hypomethylated anymore

epigraHMM

                   Changes in version 1.19.1
  • epigraHMM examples and the vignette no longer use the chromstaRData package due to its deprecation

epiregulon

                    Changes in version 2.0.1

Fixed bugs that caused addWeights to fail when aggregateCells = TRUE. When aggregateCells is set to TRUE, cells are aggregated by calculating the mean of the original cell features rather than their sums. Fixed a warning about the class of the cellNum argument passed to calculateP2G, which was raised incorrectly.

epiRomics

                   Changes in version 0.99.5

Changes

  • Added public getter and setter methods for all five slots of the epiRomicsS4 class: annotations(), meta(), txdb(), organism(), and genome() (plus the corresponding <- assignment forms). Users should prefer these accessors over obj@slot or methods::slot(obj, “slot”). organism() extends the generic from BiocGenerics and genome() extends the generic from GenomeInfoDb, following Bioconductor convention. Every setter invokes methods::validObject() so invalid assignments (for example an empty-string genome) fail fast with a clear error. A full audit of the codebase confirms these five slots are the only slots on epiRomicsS4; the class definition has not changed, and downstream pipeline functions never introduce new slots — they only update the content of annotations (a GRanges, whose mcols carry the per-stage details).
  • Added ?epiRomicsS4-accessors overview topic that lists every getter/setter pair in one table with runnable examples. The ?epiRomicsS4-class page cross-references each individual accessor via @seealso and documents each slot with an explicit “Access via …” note pointing at the matching getter.
  • Refactored both vignettes to demonstrate the new accessor API. methods::slot() no longer appears in any user-facing example, vignette, or man page. getting-started-with-epiRomics.Rmd had 7 methods::slot() calls replaced with annotations(), plus a prose paragraph noting that users should prefer the getter API (one paragraph inserted in each vignette near first use). articles/full-analysis-with-epiRomics.Rmd had 22 methods::slot() calls replaced.
  • Every roxygen @examples block that previously used methods::slot(obj, “…”) now uses the matching getter (touched files: R/synthetic-data.R, R/enhanceosomes.R, R/enhancers.R, R/regions_of_interest.R).
  • Swapped the four runtime methods::slot(database, “…”) calls inside make_example_enhanceosome() in R/synthetic-data.R for the matching getters (genome(database), meta(database), txdb(database), organism(database)).
  • Updated user-facing roxygen prose that referred to database@meta or @annotations to reference the new meta() / annotations() accessors instead (touched files: R/synthetic-data.R, R/chromatin_states.R, R/enhancers.R, R/benchmark_enhancer_predictor.R, R/regions_of_interest.R).
  • Added tests/testthat/test-accessors.R with 20 test_that blocks / 50 assertions covering: every getter on the hg38 and mm10 fixtures and on a fresh empty object, every setter round-trip and class preservation, validity enforcement (genome(x) <- “” and txdb(x) <- “” must error), and confirmation that organism() / genome() extend the BiocGenerics / GenomeInfoDb generics rather than shadowing them. After this change the full package test suite runs 261 tests / 607 assertions with 0 failures, 0 errors, 7 legitimate skips (Windows-only harness checks and optional non-model-organism TxDb packages).
  • Added a one-time session tip to the rename-warning helper (.warn_renamed()): the first time a deprecated epiRomics_* alias fires, users also see a one-line note pointing them at the new accessor API (?epiRomicsS4-accessors).
  • Fixed the test-deprecated-aliases.R harness, which was still written against the pre-0.99.4 .Deprecated()-based behaviour and therefore was order-dependent under the message()-based rename helper introduced in 0.99.4. The harness now asserts against the message() condition (via invokeRestart(“muffleMessage”)) and resets .warn_renamed() state at the top of the block so every alias fires fresh exactly once, regardless of the order other test files ran in. No package code was changed by this test fix.

  • Quality gates for 0.99.5: R CMD check –as-cran reports 0 ERRORs / 0 WARNINGs / 1 NOTE (the expected “New submission” note); BiocCheck reports 0 ERRORs / 0 WARNINGs / 9 NOTES (all pre-existing and stylistic — none introduced by this change); both vignettes rebuild cleanly with the new accessor API.

                     Changes in version 0.99.4

Changes

  • Replaced .Deprecated() calls in renamed-function wrappers with one-time message() notices via a shared .warn_renamed() helper. Users calling the old epiRomics_* names still see a clear nudge to migrate to the new verb-first names (removal planned for the next release), but BiocCheck’s .Deprecated / .Defunct usage warning no longer fires.

                     Changes in version 0.99.3

Highlights

  • On-demand example data: cache_data() downloads example datasets (~1.3 GB) via BiocFileCache, keeping the package tarball under 5 MB. has_cache() and get_cache_path() check and locate cached data.

  • Base R graphics track layer: plot_tracks() renders publication-quality multi-track genome browser views in 1-2 seconds per locus using base R graphics. ATAC and RNA signals display in mirrored panels for direct cross-sample comparison.

  • Quick visualization: plot_quick_view() provides zero-setup BigWig signal visualization for any gene locus — no database required.

  • Gene-centered visualization: plot_gene_tracks() displays all database tracks at any gene locus without the enhanceosome pipeline.

  • Chromatin state classification: classify_chromatin_states() classifies regions into biologically meaningful states (active, bivalent, poised, primed, repressed, unmarked) following ChromHMM/Roadmap Epigenomics conventions.

  • TF co-binding analysis: analyze_tf_cobinding() uses Fisher’s exact test with odds ratios and pointwise mutual information (PMI) to identify significant TF co-binding pairs.

API

All exported functions follow Bioconductor naming conventions (verb-first, no package prefix). Legacy names remain exported as .Deprecated() aliases for one release cycle and will be removed in a future version.

Function names:

  • epiRomics_build_dB() → build_database()
  • epiRomics_quick_view() → plot_quick_view()
  • epiRomics_track_layer() → plot_tracks()
  • epiRomics_track_layer_fast() → plot_tracks_fast()
  • epiRomics_track_layer_gene() → plot_gene_tracks()
  • epiRomics_putative_enhancers() → find_putative_enhancers()
  • epiRomics_enhancers_co_marks() → find_enhancers_by_comarks()
  • epiRomics_enhanceosome() → find_enhanceosomes()
  • epiRomics_enhancers_filter() → filter_enhancers()
  • epiRomics_filter_accessible() → filter_accessible_regions()
  • epiRomics_chromatin_states() → classify_chromatin_states()
  • epiRomics_chromatin_states_categories() → chromatin_state_categories()
  • epiRomics_annotate_putative() → annotate_enhancers()
  • epiRomics_tf_cobinding() → analyze_tf_cobinding()
  • epiRomics_tf_overlap() → analyze_tf_overlap()
  • epiRomics_enhancer_predictor_to_ref() → benchmark_enhancer_predictor()
  • epiRomics_regions_of_interest() → get_regions_of_interest()
  • epiRomics_cache_data() → cache_data()
  • epiRomics_cache_path() → get_cache_path()
  • epiRomics_has_cache() → has_cache()

Parameter names (no deprecation shim — update calls directly):

  • epiRomics_dB → database
  • epiRomics_db_file → db_file
  • epiRomics_genome → genome
  • epiRomics_organism → organism
  • epiRomics_curated_database → curated_database
  • epiRomics_histone, epiRomics_histone_mark_1, epiRomics_histone_mark_2 → histone, histone_mark_1, histone_mark_2
  • epiRomics_track_connection → track_connection
  • epiRomics_index → index
  • epiRomics_keep_epitracks → keep_epitracks
  • epiRomics_type → type
  • epiRomics_test_regions → test_regions
  • epiRomics_putative_enhancers → putative_enhancers
  • epiRomics_putative_enhanceosome → putative_enhanceosome
  • epiRomics_enhanceosome → enhanceosome

The epiRomicsS4 class name is unchanged (the S4 suffix indicates class source).

  • genome is a free-form string validated against the user-supplied TxDb (validate_genome_matches_txdb()). No hardcoded whitelist; any organism with a TxDb.* and org.*.db package is supported.

Dependencies

  • TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Mmusculus.UCSC.mm10.knownGene, org.Hs.eg.db, org.Mm.eg.db, BiocFileCache, and parallel moved to Suggests with requireNamespace() guards at every call site.
  • Full @importFrom audit across all R files; NAMESPACE regenerated.

Examples and vignettes

  • Ships a ~0.8 MB toy dataset at inst/extdata/toy/ (400 kb hg38 chr11 window centred on the INS locus) curated from the Zenodo archive (https://zenodo.org/records/19189987). The Getting Started vignette runs end-to-end against the toy data; the full walkthrough is preserved as Full Analysis with epiRomics and resolves the Zenodo archive via cache_data().
  • The full walkthrough lives under vignettes/articles/ as a pkgdown-only article (listed in .Rbuildignore). It is rendered on the pkgdown site but is not built during R CMD check or package installation, so users never wait for the 1.3 GB Zenodo download at install time. The lightweight Getting Started vignette is the only registered vignette in the tarball.
  • Full walkthrough Interactive showcases section links to both the Mouse Islet (Mawla et al. 2023) and Human Islet (Mawla & Huising 2021) Shiny browsers.
  • Exported synthetic-data helpers — make_example_database(), make_example_putative_enhancers(), make_example_enhanceosome(), make_example_bigwig() — power every man-page example so examples run under R CMD check –run-donttest without network access. The only remaining \donttest block is in cache_data() (network download, justified).
  • Both vignettes open with visible setup chunks, interleave explanatory prose before and after every code chunk, and print data-frame structure (manifest CSVs, head() of result objects) so readers see inputs and outputs.
  • Getting-started introduction frames the multi-omics enhancer scope, enumerates Bioconductor integrations, and contrasts epiRomics against Gviz, trackViewer, and Signac.
  • vignettes/references.bib holds package citations; vignettes use [@mawla2023; @mawla2021] inline references.

Documentation and installation

  • README recommends Bioconductor installation first; GitHub install is flagged as not recommended and uses BiocManager::install().
  • README points users to browseVignettes(“epiRomics”), the pkgdown site (https://huising-lab.github.io/epiRomics/), and the Bioconductor landing page.
  • pkgdown site restored: _pkgdown.yml and a dedicated .github/workflows/pkgdown.yaml rebuild the site on every push to main and on every release.
  • Top-level doc/ directory removed from the source tree.
  • Comprehensive HTML and PDF vignettes with live BigWig signal visualizations.
  • .onAttach() startup message with version, cache status, and citation info.

Speed

  • Parallel overlap counting via parallel::mclapply() when available.
  • Pre-split annotations by type for O(1) lookup in find_enhanceosomes().
  • Vectorized chromatin state classification and signal aggregation.
  • BigWig RDS caching for memory-efficient large-scale analyses.

CI/CD

  • Cross-platform GitHub Actions matrix: Ubuntu (release/devel/oldrel-1), macOS ARM, macOS Intel, Windows.
  • BiocCheck validation on every push/PR.
  • Test coverage with full integration tests via cached example data.

Housekeeping

  • BiocCheck cleanups: eliminated paste() / paste0() usage inside condition signals across 5 files; removed «- from R/synthetic-data.R; refactored make_example_enhanceosome() to a synthetic fast path (analyze_tf_cobinding example now runs in <1 s, down from 35 s).
  • Fixed CRAN URL-redirect NOTE by pointing README and vignette links at canonical URLs.
  • Aligned README R-version minimum to DESCRIPTION Depends (R ≥ 4.5.0).
  • Trimmed residual >80-character lines from R source for BiocCheck line-length cleanliness.
  • Dataset provenance wording throughout the vignettes, toy README, and inst/scripts/make-toy-data.R clearly identifies the curator role and points at the package README for the full curation methodology (GEO GSE76268 source; ENCODE-DCC ATAC pipeline; MACS2; DiffBind; FANTOM5, Human Islet Regulome, UCNEs).

epiSeeker

                   Changes in version 0.99.12
  • Initial Acceptance to Bioconductor

escape

                    Changes in version 2.7.3

BUG FIXES

  • Robust Seurat v5/v3 assay handling: Fixed compatibility with latest SeuratObject where the slot argument to GetAssayData() is now defunct. All internal accessors (.cntEval(), .pull.Enrich()) now use the layer API for SeuratObject >= 5.0.0 and fall back to slot only for older versions.
  • Updated .adding.Enrich() to use the SeuratObject package version (not sc@version) when selecting CreateAssay5Object vs CreateAssayObject, preventing mismatches on objects created across Seurat versions.
  • Fixed performPCA() error (“Enrichment matrix must be numeric”) when enrichment data is returned as a sparse matrix from the Seurat v5 layer API.

ENHANCEMENTS

  • CI/CD: Added devel branch to R-CMD-check and test-coverage workflow triggers

  • Automated releases: Added GitHub Actions workflow to create releases from version tags (push v* tags to trigger)

                      Changes in version 2.6.2

NEW FEATURES

  • Added .themeEscape() internal theme function for consistent visualization styling across all plotting functions

ENHANCEMENTS

  • Seurat v5 compatibility: Updated .cntEval() to detect SeuratObject version and use layer argument instead of deprecated slot argument for SeuratObject >= 5.0.0
  • Consistent theming: Applied unified theme styling across all visualization functions (ridgeEnrichment(), splitEnrichment(), geyserEnrichment(), heatmapEnrichment(), scatterEnrichment(), pcaEnrichment(), densityEnrichment(), gseaEnrichment(), enrichItPlot())
  • Improved densityEnrichment(): Added plot title showing gene set name, alphanumeric sorting of group labels, and improved rug segment styling

DOCUMENTATION

  • Reformatted roxygen2 documentation across all exported functions for consistency
  • Standardized use of \code{}, \itemize{}, \enumerate{}, \strong{}, and \emph{} tags

  • Replaced Unicode characters with ASCII equivalents for better portability

               Changes in version 2.6.1 (2025-10-31)

Bioconductor Release 3.22

BUG FIXES

  • Fixed densityEnrichment() interaction with GSVA package through compute.gene.cdf — corrected boolean argument for internal CDF computation

EventPointer

                     Changes in version 4.0

  • Update version of EventPoint to work with BAM files

  • Use of bootstrap statistics in novel events

  • Update of vignette

EWCE

                   Changes in version 1.19.1

Bug fixes

  • bootstrap_enrichment_test / check_species
  • Validate species arguments before background generation.
  • Fail fast when fewer than the minimum number of input hits are supplied, so invalid inputs return errors instead of upstream warnings.

ExpoRiskR

                   Changes in version 0.99.3
  • Initial Acceptance to Bioconductor

fastreeR

                    Changes in version 2.7.1

  • Windowed / streaming VCF distance and tree output. Emit one distance matrix (or Newick tree) per genomic window of N base pairs or per N consecutive variants for VCF2DIST and VCF2TREE.

               Changes in version 2.5.0 (2026-02-02)

  • Added embedding-based distance calculation for VCF files (backend 2.5.0).

               Changes in version 2.3.0 (2025-12-01)

  • Implement reading compressed VCF input (gz, bzip2, xz).

               Changes in version 2.2.0 (2025-11-01)

  • Major update: enhanced streaming, faster bootstrapping, and backend v2.2.0 integration.

fenr

                    Changes in version 1.9.2

  • Corrected response to the error message from the responsive WikiPathways server, so it does not through error when on_error = “warn”.

                      Changes in version 1.8.1

  • Top gene ontology URL does not seem to be accessible directly anymore; changed the URL in fetch_go_genes_go() accordingly.

fgsea

                   Changes in version 1.37.1

  • Hash-based resolution of tied gene sets in the multilevel algorithm (by Nikita Golikov), properly fixes #151

  • P-avlues for ES close to 1 are more accurate now

  • Internally, the gene weights are now converted to integers (with scaling), which might introduce minor result discrepancies in rare cases

FlowSOM

                   Changes in version 2.19.4

  • Removed #include <PrtUtil.h> from the C script, as this is not supported anymore, and I don’t think we actually still used it.

                     Changes in version 2.19.3

  • Attempt to fix git issue with double file name

                     Changes in version 2.19.2

  • In NewData, only give warning messages when paramter in fsom object is TRUE

flowSpecs

             Changes in version 1.25.2 (2026-03-17)

  • +Bug fixes for version created yesterday

               Changes in version 1.25.1 (2026-03-16)

  • +Updates for S8 data, but with more general applicability: +specMatCalc now allows for a custom set of exclusion parameters +specMatCalc now allows for exclusion of the scatter gating step

fmrs

                    Changes in version 2.0.1

IMPROVEMENTS SINCE LAST RELEASE

  • Non-mixture of regression models are now added to the package.

BUG FIXES

  • Several bugs are fixed.

                      Changes in version 2.0.0

IMPROVEMENTS SINCE LAST RELEASE

  • The package is rewritten using .Call function.
  • The codes for Weibull distribution are improved.

BUG FIXES

  • Several bugs are fixed which caused the results to be different for the same analysis.

fourSynergy

                   Changes in version 0.99.12
  • Initial Acceptance to Bioconductor

fRagmentomics

            Changes in version 0.99.12 (2026-03-31)

Pre-release version on Bioconductor devel.

fraq

             Changes in version 0.99.2 (2026-02-12)
  • Initial Acceptance to Bioconductor

FRASER

                    Changes in version 2.6.1
  • Internal: use moved makeTxDbFromGFF function from txdbmaker instead from GenomicFeatures.

gcatest

             Changes in version 2.11.1 (2026-01-28)
  • Updated vignette from old Sweave to modern R markdown.

gDNAx

             Changes in version 1.10.0 (2026-04-27)

USER VISIBLE CHANGES

  • Changed default useRMSK=TRUE to useRMSK=FALSE in gDNAdx().

BUG FIXES

  • Fix in the calculations of the strandedness() function, and its corresponding unit tests.

gDR

           Changes in version 2025-10-30 (2025-10-30)

  • synchronize Bioconductor and GitHub versioning

             Changes in version 2025-06-11 (2025-06-11)

  • update installation instructions

gDRcore

           Changes in version 2026-04-27 (2026-04-27)

  • fix C++ compilation error on R-devel (STRING_PTR → STRING_PTR_RO)

             Changes in version 2026-04-13 (2026-04-13)
  • migrate from qs to qs2 package (qs::qread → qs2::qs_read, qs::qsave → qs2::qs_save)

  • update checkpoint and generated data file extensions from .qs to .qs2

             Changes in version 2026-02-18 (2026-02-18)

  • fix handling of numeric identifiers in annotation functions

             Changes in version 2026-02-16 (2026-02-16)

  • fix stack imbalance warnings during byte-compilation

             Changes in version 2026-02-02 (2026-02-02)

  • remove duplicated code from map_references in map_untreated

             Changes in version 2025-11-27 (2025-11-27)

  • add support for Incucyte data

             Changes in version 2025-11-17 (2025-11-17)
  • remove empty clids from day0 data during merging raw data

gDRimport

           Changes in version 2026-04-23 (2026-04-23)

  • add support for generation of day0 template for tdd files

             Changes in version 2026-04-13 (2026-04-13)
  • migrate from qs to qs2 package (qs::qread → qs2::qs_read, qs::qsave → qs2::qs_save)

  • update test data and reference file extensions from .qs to .qs2

             Changes in version 2026-04-07 (2026-04-07)

  • add support for excel format of new envision data

             Changes in version 2026-02-25 (2026-02-25)

  • add support for multi-plate new envision format

             Changes in version 2026-02-16 (2026-02-16)

  • fix stack imbalance warnings during byte-compilation

             Changes in version 2025-12-27 (2025-12-27)

  • extend support for csv EnVision format

             Changes in version 2025-12-17 (2025-12-17)
  • add support broad_id in PRISM data

  • add suport for combo data in private prism data

             Changes in version 2025-12-10 (2025-12-10)

  • make barcode detection more robust (Incucyte)

             Changes in version 2025-11-26 (2025-11-26)

  • add support for Incucyte data

             Changes in version 2025-11-17 (2025-11-17)
  • add support for new EnVision format

gDRutils

           Changes in version 2026-04-18 (2026-04-18)
  • migrate from qs to qs2 package (qs::qread → qs2::qs_read, qs::qsave → qs2::qs_save)

  • update batch file extension from .qs to .qs2

             Changes in version 2026-04-14 (2026-04-14)

  • add support for metadata in merge_MAE

             Changes in version 2026-03-23 (2026-03-23)

  • standardize_MAE standardizes also internal identifiers

             Changes in version 2026-02-12 (2026-02-12)

  • remove_drug_batch supports atomic vectors as input

             Changes in version 2025-12-02 (2025-12-02)

  • convert_se_assay_to_dt supports merging additional variables

             Changes in version 2025-11-27 (2025-11-27)

  • add support for the time-course experiment

             Changes in version 2025-11-03 (2025-11-03)
  • update merge_SE function to merge drugs with different batches together

gemma.R

                    Changes in version 4.0.0
  • get_annotation_children and get_annotation_parents are added. get_child_terms is deprecated in favor of get_annotation_children

GenomicPlot

                    Changes in version 1.9.2
  • Add chromInfo parameter support for non model organisms (custom organisms)

  • Bump up version number to trigger Bioconductor build

                      Changes in version 1.9.1
  • Fix bugs caused by plyranges update
  • Bump up version number to trigger Bioconductor build

geomeTriD

                    Changes in version 1.5.1

IMPROVEMENT

  • add citation.

GEOquery

                   Changes in version 2.99.1

Bug Fixes

  • Fixed error when parsing GSE matrix files with malformed or empty lines between sample metadata (e.g., GSE425). Sample lines are now extracted directly using pattern matching to avoid issues with irregular file formatting.

               Changes in version 2.99.0 (2024-10-01)

New Features

  • RNAseq data support for GEOquery. Now you can use RNASeq quantification data prepared by NCBI.
  • Basic search in GEO database. Now you can search for datasets in GEO database using GEOquery.
  • browseGEO() function to open a web browser with a GEO accession.

Breaking changes

  • getGEO() now returns a list of SummarizedExperiment objects. This is a breaking change from previous versions of GEOquery. If you are using GEOquery in a script, you will need to update your code to reflect this change.

Bug Fixes or Improvements

Not an exhaustive list, but some highlights:

  • Using httr2 instead of curl for better control over HTTP requests.
  • Removed dead gunzip code.

ggtree

                    Changes in version 4.1.2
  • make gheatmap() robust to missing tree labels in data row names by warning and auto-filling missing rows with NA instead of stopping (2026-03-23, Mon)
  • improve gheatmap() input validation and custom column label remapping (2026-03-09, Mon)
  • add native paired-tree/tanglegram support via ggdoubletree(), fortify.tanglegram(), fortify.cophylo(), and geom_tanglelink(), including support for raw trees, ggtree objects, deterministic crossing minimization, and optimize_side = “right”|”left”|”both” regression tests (2026-03-09, Mon)
  • add a deterministic tree_and_leaf layout inspired by the TreeAndLeaf package, with native ggtree() integration and regression tests (2026-03-09, Mon)
  • add a height parameter to collapse() supporting NULL, ggplot2::rel(), and absolute numeric heights for collapsed triangles, while restoring the original layout correctly on expand() (2026-03-09, Mon, #409)
  • optimize the daylight layout by caching subtree topology and removing repeated tidyverse reshaping while preserving the existing geometry; add regression tests for cached and uncached paths (2026-03-09, Mon)
  • fix custom layout handling in ggtree() when layout functions return an xy component (2026-03-09, Mon)
  • make geom_hilight() and geom_cladelabel() more compatible with recent ggplot2 changes, and strengthen regression tests (2026-03-09, Mon)
  • modernize roxygen documentation using markdown syntax (2026-01-12, Mon)
  • add ‘data’ argument to geom_rootedge() (2026-01-10, Sat, #696, #697)
  • more options in ggtree_set_interactive() (2025-12-19, Fri)
  • update default_aes to work with from_theme
  • geom_highlight and geom_taxalink (2025-12-18, Thu, #694)
  • fix issue of geom_taxalink by adding ‘outward’ argument (2025-12-18, Thu, #692)
  • print() method for ‘ggtree’ object (2025-12-17, Wed)
  • ggtree_set_interactive() and ggtree_unset_interactive() to set and unset interactive mode (2025-12-17, Wed)

  • if interactive mode is set and there are no interactive attributes, it will throw a warning message, which can be disabled if ggtree_set_interactive(check=FALSE)

                      Changes in version 4.1.1
  • bug fixed in geom_striplab (2025-10-30, Thu, #677)

ggtreeExtra

                   Changes in version 1.21.0
  • Bioconductor 3.22 released, and Bioconductor 3.23 (devel) bump. (2025-10-31, Fri)

GloScope

             Changes in version 2.1.1 (2025-09-27)
  • Fix so handles if no column names which was creating error with latest version of mclust

glycoTraitR

             Changes in version 0.99.0 (2025-12-04)

Initial Bioconductor submission

GNOSIS

             Changes in version 1.99.0 (2023-09-04)

  • Made the following significant changes o added functionality to select and upload cBioPortal study o deprecated ability to save R script with executed code

  • Submitted to Bioconductor

GOfan

                   Changes in version 0.99.2
  • Initial Acceptance to Bioconductor

GOSemSim

                   Changes in version 2.37.2
  • refactor .initial() to use a controlled environment for robust data loading (2026-01-15, Thu)
  • enhance cache reading robustness in computeIC() and wangMethod_internal() (2026-01-15, Thu)
  • update load_onto() documentation (2026-01-12, Mon)
  • enhance godata() input validation (2026-01-12, Mon)
  • refactor internal ontology type checking (2026-01-12, Mon)
  • fix cache integration in .initial and refactor consumers to use get_cache_element (2026-01-12, Mon)
  • fix load_onto() using cache incorrectly (2026-01-12, Mon)
  • use cache mechanisms defined in ‘yulab.utils’ for caching (2026-01-12, Mon)

  • update URLs, fix typos and refine roxygen documentation (2026-01-12, Mon)

                     Changes in version 2.37.1
  • use cache mechanisms defined in ‘yulab.utils’ for caching (2025-12-08, Mon)
  • update roxygen to use ‘markdown’ syntax and unify duplicated docs into templates (in ‘man-roxygen’ folder) (2025-12-07, Sun)
  • move get_organism() from ‘DOSE’ (2025-12-07, Sun)
  • move load_OrgDb() to ‘yulab.utils’ (2025-12-05, Fri)

GraphExperiment

                   Changes in version 0.99.0

NEW FEATURES

  • Initial Acceptance to Bioconductor

graphite

             Changes in version 1.57.1 (2026-04-26)
  • Updated all pathway data.

GSABenchmark

             Changes in version 0.99.0 (2025-11-05)
  • Submitted to Bioconductor

GSVA

                     Changes in version 2.6

USER VISIBLE CHANGES

  • Performance improvement in the calculation of GSVA scores from ranks.

  • Replaced trend=gssizes by trend=sqrt(gssizes) in the vignette that illustrates the limma-trend pipeline with GSVA scores.

  • Added support for ssGSEA, PLAGE and Z-score to work with large datasets stored using a DelayedArray backend, such as HDF5.

  • Moving from scuttle/scran used in the single-cell vignette to scrapper/bluster to fix deprecation warnings.

  • *Param() functions report more informative errors when the input expression data or gene sets do not correspond to one of the expected object classes.

  • Added new functions saveHDF5GSVAranks() and loadHDF5GSVAranks() to first save on disk the output of the gsvaRanks() function, and second, load that output from disk to callthe gsvaScores() function with it.

  • Improved unit test coverage to > 85%.

BUG FIXES

  • Fix on the handing of missing data with the GSVA method. Bug reported in issue #257.

  • Fix on the propagation of NA values with the GSVA method.

  • Fix in detecting rows with constant (nonzero) values.

  • Fix in kcdf=”Gaussian” when input is SparseArray.

  • Fix in fetching rows from SVT_SparseArray matrices.

  • Fix on handling NaN values, which were causing a core dump, they are now treated as NA values. Bug reported in issue #258.

  • Removed non-API calls from C code.

  • Code reorganization and multiple improvements and vulnerability fixes.

gVenn

                    Changes in version 1.1.1

New features

  • Add bg parameter to saveViz() for controlling plot background color, including transparent backgrounds. Users can now save plots with bg = “transparent” for use in presentations or publications requiring transparent backgrounds.
  • Add hex sticker logo created using the hexSticker R package.
  • Update graphical abstract highlighting gVenn’s overlap visualization and extraction capabilities

Documentation

  • Add example to vignette demonstrating transparent background export using bg = “transparent” parameter in saveViz()

hammers

                   Changes in version 0.99.0
  • Submitted to Bioconductor

Harman

                   Changes in version 1.39.0

  • Fix Linux build failure under C++20 by correcting the CFactorials constructor declaration in src/CMapSelectKFromN.h.

  • Updated Makevars to stop producing deprecation warnings.

HIBAG

                   Changes in version 1.48.0

  • remove “System requirements specified C++11” in DESCRIPTION

  • New optimized C codes for AArch64 (ARM 64-bit) architecture

  • improve Makevars.win: replace -ffixed-xmm16..31 with -fno-asynchronous-unwind-tables for AVX-512 compilation on Windows, allowing the GCC compiler to use all 32 XMM/ZMM registers for better performance

hipathia

             Changes in version 3.11.2 (2026-03-25)
  • Fist version using Zenodo as repository for necessary files

HiSpaR

             Changes in version 0.99.0 (2026-01-16)

  • Initial Bioconductor submission

  • Implements hierarchical Bayesian inference of 3D chromatin structures

  • Supports MCMC sampling with cluster-based hierarchical approach

  • Includes example Hi-C contact matrix dataset (su1_contact_mat)

  • Provides efficient C++ implementation via Rcpp and RcppArmadillo

  • OpenMP support for parallel computation

HistoImagePlot

                    Changes in version 1.0.0

New features

  • Initial Acceptance to Bioconductor

HPAanalyze

                    Changes in version 1.29
  • Changes in version 1.29.1
    • Update built-in data and internal gene name lookup table to v25.0

Ibex

                    Changes in version 1.1.1
  • Aligned version with Bioconductor release
  • Switched default branch to devel for Bioconductor compatibility
  • Updated CI workflows to target devel branch
  • Converted NEWS to NEWS.md format
  • Added automated GitHub Release workflow via tags
  • Ibex_matrix() now accepts character vectors of amino acid sequences directly
  • Removed rlang from Imports, added lifecycle
  • As per basilisk documentation:
  • Add .BBSoptions with UnsupportedPlatforms: win32
  • Add configure and configure.win scripts
  • Add Docker infrastructure with Dockerfile and .devcontainer/devcontainer.json
  • Improved testthat compatibility across platforms
  • Improve adherence to verbosity arguments

imageFeatureTCGA

                    Changes in version 1.0.0

New features

  • Added a NEWS.md file to track changes to the package.

imageTCGAutils

                    Changes in version 1.0.0

New features

  • Initial Bioconductor release!

imcRtools

             Changes in version 1.17.2 (2026-04-24)

  • Replaced deprecated aggregateAcrossCells function from scuttle package with scrapper implementation

               Changes in version 1.17.1 (2026-03-30)

  • update function page/vignette

immApex

                    Changes in version 1.5.4

BUG FIXES

  • Fixed vignette build failure when IMGT network data is unavailable (e.g., on Bioconductor build servers)

  • Fixed operator precedence bug in inferCDR() reference validation check

                      Changes in version 1.5.3

UNDERLYING CHANGES

  • getIMGT() now uses immReferent as a backend for downloading and caching IMGT reference sequences
  • Removed frame, max.retries, and verbose parameters from getIMGT()
  • Added refresh parameter to getIMGT() for controlling cache behavior
  • Removed hash, httr, and rvest package dependencies (now handled by immReferent)

  • Replaced .parseSpecies() with .mapSpecies() for immReferent species name compatibility

                      Changes in version 1.5.2

  • improved error message for the propertyEncoder() function when the suggested Peptides package is not installed.

                      Changes in version 1.5.0
  • Bioconductor devel branch update to match versions

immLynx

                   Changes in version 0.99.4
  • Initial Bioconductor submission

immReferent

                   Changes in version 0.99.7

New Features

  • Initial Acceptance to Bioconductor

InPAS

                   Changes in version 2.18.1
  • Remove plyranges::filter.

IntEREst

                   Changes in version 1.36.0

DEPRECATED AND DEFUNCT

  • miRBaseBuild parameter is removed from referencePrepare function as it was defunct in txdbmaker package.

iscream

                    Changes in version 1.1.8

INTERNAL

  • Remove an unused debug string for printing the locus ID from src/query_all.cpp

DOCUMENTATION

  • Use blockquote the “Getting Started” vignette to call out the note about chromosome formatting in input regions - chr1 vs 1.

                      Changes in version 1.1.7

BUG FIXES

  • Fix htslib_version() to return the version as a string instead of simply printing it to allow programmatic checks for libdeflate presence.

  • iscream now informs users whether they have libdeflate-enabled htslib on package load.

                      Changes in version 1.1.6

BUG FIXES

  • Fix a check for missing input files by correcting checking the filepath vector length

INTERNAL

  • Use inherits(x, “data.frame”) instead of “data.frame” %in% class(x)”

                      Changes in version 1.1.5

BREAKING CHANGES to summarize_regions() and summarize_meth_regions():

  • The summary output now has position as chromosome, start, and end columns instead of just a feature column with the position string. This allows direct conversion to GRanges objects without having to use rownames. It is still possible to use chromosome names as the input query regions (“chr1”), the start and end in those cases will be NA.

  • The feature column is now populated only if the input regions are named, if a vector, or the feature_col argument is set to a column for data.frame/GRanges inputs.

  • The count column from summarize_meth_regions() is now named count instead of cpg_count.

  • These functions now return a data.table instead of a data.frame to allow for faster in-place modifications and consistency with tabix() output. Use data.table::setDF() to convert to a data.frame in-place.

BUG FIXES

  • Rownames are no longer set for the summarize_regions() or summarize_meth_regions() output using the input region strings as these were repeating and not unique. It was only possible because they were set from the C++ scope instead of R.

ENHANCEMENTS

  • summarize_regions() and summarize_meth_regions() now support the following new functions, inspired by bedtools map:

  • Population standard deviation (pstddev)
  • First element (first)
  • Last element (last)
  • Mode (mode)
  • Anti-mode (antimode)
  • Absolute min (absmin)
  • Absolute max (absmax)

  • Count of unique values (count_distinct)

  • get_granges_string() can now extract names from its mcols using a feature_col argument as in get_df_string() - names were previously pulled only from names(). This means GRanges inputs to summarize_regions() can have the feature_col in its mcols rather than just as its names.

DOCUMENTATION

  • Update Zenodo URLs in vignettes to the updated record: https://zenodo.org/records/18089082. The genes.bed file used in vignette(“performance”) now contains the gene names that the vignette references.

INTERNAL

  • Refactored summarize_regions to collect similar validation and regions parsing functions

  • tabix() writes the input regions of interest to disk only once instead of doing it for every file

                      Changes in version 1.1.4

BUG FIX

  • Reduced the minimum R version from 4.5 to 4.4

                      Changes in version 1.1.3

DOCUMENTATION

  • Document how to make use of strand information with tabix()

  • Improve wording of tabix()’s’ aligner and col.names documentation

                      Changes in version 1.1.2

  • Fix typo in error message from thread count checks

                      Changes in version 1.1.1

BUG FIXES

  • Fix configure to correctly check htslib version when rhtslib is not used and not issue spurious warnings

iSEE

                   Changes in version 2.23.1
  • Use linewidth to set width of lines in plots, require ggplot2 >= 3.4
  • Allow sampling resolution and guide sizes to be non-integer values
  • Remove Windows line endings when validating inputs in the ace editor
  • Add line to load ggplot2 in the exported code
  • Fix bug in the reporting of collapsible box status. Addresses #701

IsoformSwitchAnalyzeR

                   Changes in version 2.11.1

  • Update type: Minor.

  • Updated deprecated functions and minor modifications

  • Updated version to sync with Bioconductor

  • Added Elena as contributed to package

isomiRs

                   Changes in version 1.39.1

FIX

  • Fix ggplot2 compatibility issues with labs() function - removed deprecated list() syntax

  • Fix ggplot2 deprecation warning by replacing aes_string() with modern aes() and tidy evaluation

jvecfor

                   Changes in version 0.99.0
  • Submitted to Bioconductor.
  • Initial implementation of fastFindKNN(), drop-in replacement for BiocNeighbors::findKNN using the jvecfor Java backend (HNSW-DiskANN and VP-tree).
  • Added fastMakeSNNGraph() and fastMakeKNNGraph() convenience wrappers delegating graph construction to the bluster package.
  • Supports euclidean, cosine, and dot_product distance metrics.
  • Multi-threaded index build and search via Java ForkJoinPool.
  • Optional Product Quantization (PQ) for approximately 4-8x search speedup.

KEGGREST

                   Changes in version 1.52.0

SIGNIFICANT USER-VISIBLE CHANGES

  • The mark.pathway.by.objects function has been removed.

LACHESIS

                   Changes in version 0.99.5

NEW FEATURES

o Initial Acceptance to Bioconductor

lcmsPlot

                   Changes in version 0.99.20
  • Initial Acceptance to Bioconductor

leapR

                   Changes in version 0.99.6
  • Built-in Plotting Function Created.

lefser

                   Changes in version 1.22.0

Minor improvements and bug fixes

  • Fixed issue identifying classes in the ldaFunction effect size calculation (@nnmbr, #88)
  • Fix default colors arguments in lefserPlot(), lefserPlotFeat(), and lefserPlotClad()
  • Added label.font.color and … (ellipses) parameters to lefserPlot() function for increased flexibility in customizing feature labels.
  • Added label.font.face parameter to lefserPlot() function to allow customization of font face for feature labels (e.g., “plain”, “italic”, “bold”, “bold.italic”)

lfa

             Changes in version 2.11.3 (2026-01-29)

  • Function sHWE for BEDMatrix inputs now deletes temporary files after they are no longer needed

               Changes in version 2.11.2 (2026-01-28)

  • Updated vignette from old Sweave to modern R markdown.

               Changes in version 2.11.1 (2026-01-28)
  • Function sHWE greatly reduced memory handling for BEDMatrix inputs by writing random genotypes to temporary plink1 BED files.
  • Packages BEDMatrix and genio are now in “imports” (used to be “suggests”).
  • Added option m_chunk to write temporary random genotypes in large chunks for favorable I/O.
  • Functions switched from deprecated to defunct: read.bed, read.tped.recode, model.gof, center
  • Package utils removed from “imports”

limma

             Changes in version 3.68.0 (2026-04-28)

  • New arguments offset and offset.prior for voom(). voom() now supports offsets in DGEList objects.

  • New argument treat.lfc for topSplice() to allow TREAT fold-change thresholding with diffSplice() output.

  • In normalizeCyclicLoess(), default for adaptive.span becomes TRUE, and the span is chosen using the default settings of chooseLoessSpan().

  • The function topTableF(), which has been deprecated for many years, is now formally removed.

limpa

             Changes in version 1.4.0 (2026-04-29)

  • A limpa documentation page has been created at https://github.com/SmythLab/limpa/ containing a number of case study analyses of real datasets. This URL has been addded to the package DESCRIPTION file and the package vignette now has a “Further documentation” section that links out to this site.

  • Change of terminology from “peptides” to “precursors” as the default unit of input data throughout the package. More discussion of precursors vs peptides and other levels of data in the vignette.

  • Further clarification in the vignette that limpa can process any level of data for which intensities are available, including fragments, precursors, peptides, proteins, or PTMs. limpa can summarize precursors to either peptides or proteins and can conduct differential analyses at any level. The vignette now cites the Corso et al (2026) preprint as an IP-MS example. limpa can also explore isoform-specific expression by conducting differential usage analyses of peptides or PTMs within proteins, and there is a case study of such an analysis at https://github.com/SmythLab/limpa/.

  • As part of the above change, the output column genes$NPeptides from dpcQuant() nas been renamed to genes$NPrec, and the progress message from dpcQuant() and dpcQuantByRows() now says “Precursors” instead of “Peptides” for the number of rows. (The column name and message are generic: the column name will still be NPrec and the message will still say “Precursors” even if fragments are being processed instead of precursors.) Percentage progress has also been added to the progress message.

  • A new function EListFromLongFormatFile() has been added to read intensities from any long format file, and readDIANN() and readSpectronaut() now call this function instead of handling their own read code. The input file can be either an uncompressed delimited text file or a Parquet file, and the file type is detected automatically from the file name. The new function uses the nanoparquet package to read Parquet files whereas readDIANN() previously used arrow. The new function adds a number of new arguments and changes the names of some existing arguments. It allows filtering by any number of columns and allows reading of observation-level covariates. All three functions now allow feature.column to be a vector of arbitrary length, which allows columns to be combined to created a unique precursor or fragment ID. Amongst other things, this functionality facilitates reading of fragment level data and reading of MSstats format files. All three functions have a new argument verbose to optionally output progress information and the number of intensity values that have been filtered.

  • readDIAN() has a new argument list to match EListFromLongFormatFile(). The old argument precursor.column is renamed to feature.column, qty.column to intensity.column, and extra.columns to annotation.columns. Default setting for q.columns is updated.

  • readSpectronaut() has a new argument list to match EListFromLongFormatFile(). The old argument precursor.column is renamed to feature.column, qty.column to intensity.column, and extra.columns to annotation.columns. New arguments filter.columns and censor.value give more flexibility over filtering.

  • New function readSpectronautRunInfo(), which is called by readSpectronaut() to include run (sample) information in the targets component of the output.

  • New function plotAveVsMis() to plot average observed log-intensity per row vs the number of missing values.

  • dpc() has been replaced by a new function that combines the functionalities of dpcON() and dpcCN(), with the CN method as the default. The original dpc() function has been renamed to dpcLegacy().

  • dpcCN() now uses a systematic rather than a random sample of rows. Amongst other things, this ensures that the result does not change if the rows of y are reordered. The default value for subset is increased to 2000 and the default value for verbose is now FALSE.

  • The upper limit of the y-axis in the plot from plotDPC() is now extended slightly to allow for jittering of the detection proportions. Previously some of the jittered proportions above 1 were not shown on the plot.

  • New argument show.start for plotDPC() to control whether the starting curve from dpc() is shown on the plot as well as the final plot. Default is now FALSE, whereas previously the starting curve was always shown.

  • dpcImpute() renamed to dpcQuantByRow() (although old function name will continue to work for backward compatibility).

  • When operating on an EList, dpcQuant() now removes the protein ID annotation column from the output object so that the IDs appear only as row.names. dpcQuant() also stores the DPC and the hyperparameters in the output EList object.

  • New function filterByDetection(), to choose proteins detected in at least a specified number of samples.

  • Axis labels produced by plotPeptides() and plotProtein() are now user-settable. plotPeptides() now plots sample names, in the same style as plotProtein(), and the y-axis is now labelled “Log-intensities” instead of “Log-expression”.

  • New argument las for plotProtein() and plotPeptides() to allow vertical orientation of sample names on x-axis.

  • readFragPipe() and readMaxQuant() are now mentioned in the vignette.

  • Acknowledgement section added to vignette.

  • A number of programming efficiencies have been introduced to various functions.

LimROTS

                   Changes in version 1.3.24

  • Added differential expression analysis for repeated measures using the dream linear mixed model.

                     Changes in version 1.3.22

  • Incorporating repeated measurement analysis.

                     Changes in version 1.3.17

  • Add survival analysis functionality with support for Cox proportional hazards models and competing risks regression.

                     Changes in version 1.3.13

  • Add copyright statements to R project files.

                     Changes in version 1.3.10

  • Change the license from Artistic-2.0 to GPL-2.0-or-later.

                      Changes in version 1.3.6

  • Adding Citation and Disclaimer Information.

lncRna

             Changes in version 0.99.3 (2026-03-11)
  • Initial Acceptance to Bioconductor

LRDE

                   Changes in version 0.99.7

  • Initial Bioconductor submission of LRDE.

  • Implements a hurdle negative binomial (Hurdle-NB) model for differential expression analysis of long-read RNA-seq data.

  • Includes:
    • Data preparation (prepareDGE)
    • Size factor estimation (sizeFactorsEst)
    • Tag-wise dispersion estimation (tagwiseEst)
    • Differential expression testing via:
    • Likelihood Ratio Test (hurdle_LRT)
    • Wald Test (hurdle_Wald_Test)
  • Supports matrix, data.frame, and SummarizedExperiment inputs.

maaslin3

                    Changes in version 3.0.1

  • Changed data augmentation for logistic models

  • Replaced iterative renormalization with median comparisons

  • Replaced group, OMP, and GOMP models with contrast tests and ANOVA-style comparisons

                      Changes in version 3.0.0

  • Updated dependencies

  • Modularized previous code

  • Added prevalence/logistic models

  • Added data augmentation for logistic models

  • Added iterative renormalization for compositionally

  • Added spike-in references for compositionally

  • Added group, OMP, and GOMP models

MAPFX

             Changes in version 1.7.1 (2025-12-20)
  • Corrected the version number in the inst/NEWS file (0.99.9 to 1.7.1).

markeR

                    Changes in version 1.1.2

Minor Changes

  • Moved Python bridge scripts from inst/python/ to a top-level python/ directory, as these are supplementary scripts not part of the R package itself.
  • Added requirements.txt to the python/ directory listing all needed Python dependencies (rpy2, pandas, numpy, and optionally ipython and jupyter) for easier environment setup.

  • Removed redundant code snippets from the Python bridge scripts.

                      Changes in version 1.1.1
  • Added p.adjust.method parameter across all functions performing or depending on multiple testing correction, allowing users to specify any correction method supported by stats::p.adjust(), beyond the default Benjamini-Hochberg FDR.
  • Added Python bridge scripts in inst/python/ for users who wish to call markeR from a Python environment via rpy2. Includes a tutorial workflow script and a generic command-line wrapper capable of invoking any exported markeR function. See inst/python/README.md for installation and usage.

mastR

                   Changes in version 1.11.2

  • Fix the problems caused by SeuratObject v5.

                     Changes in version 1.11.1

  • Fix the problems caused by Seurat v5 and added a new vignette.

matter

                   Changes in version 2.13.5

BUG FIXES

  • Remove ‘rescale_ref()’ outside domain limits error

                     Changes in version 2.13.4

SIGNIFICANT USER-VISIBLE CHANGES

  • Removes character vector support from ‘bsearch()’

BUG FIXES

  • Remove ‘STRING_PTR’ usage from C/C++ code

                     Changes in version 2.13.3

BUG FIXES

  • Backport ‘DATAPTR()’ support for older R versions

                     Changes in version 2.13.2

BUG FIXES

  • Remove ‘DATAPTR()’ usage from C/C++ code

                     Changes in version 2.13.1

SIGNIFICANT USER-VISIBLE CHANGES

  • Add argument for passing list of vectors to ‘chunk_mapply()’

  • Add argument for passing list of vectors to ‘chunked_list()’

MDSvis

                   Changes in version 0.99.0
  • Initial Acceptance to Bioconductor

MeLSI

                   Changes in version 0.99.0

Initial Bioconductor Submission

  • Initial submission of MeLSI (Metric Learning for Statistical Inference) to Bioconductor
  • Novel machine learning method for microbiome beta diversity analysis
  • Learns optimal distance metrics to improve statistical power in detecting group differences
  • Comprehensive validation against standard methods (Bray-Curtis, Euclidean, Jaccard)
  • Robust ensemble learning approach with conservative pre-filtering
  • Validated on real microbiome datasets with proper Type I error control
  • Provides feature importance weights for biological interpretability
  • Includes helper functions for CLR transformation and visualization (VIP plots, PCoA)
  • Full integration with Bioconductor ecosystem (phyloseq, microbiome packages)

memes

                   Changes in version 1.19.1
  • Removes ggseqlogo dependency as it is being archived from CRAN, standardizes on universalmotif::view_logo for any internals that did not already use it (thanks @bjmt for the implementation hint)
  • @karawoo fixed a CI bug

meshes

                   Changes in version 1.37.1
  • use ‘enrichit’ as engine for enrichment analysis (2025-12-07, Sun)

metabinR

                    Changes in version 2.0.0

Breaking changes

  • The three binning entry points — abundance_based_binning(), composition_based_binning(), hierarchical_binning() — now return a MetabinResult S4 object instead of a plain data.frame. The v1.x tabular layout is available via as.data.frame(result).
  • The Java backend no longer exposes a command-line interface; the shaded JAR dropped the commons-cli dependency. R is the only supported entry point.
  • Minimum Java runtime is now 17 (previously 8).

New features

  • New MetabinResult class with accessors assignments(), nClusters(), parameters(), algorithm(), plus show() and as.data.frame() methods.
  • Binning functions accept, in addition to file paths, Biostrings::DNAStringSet, Biostrings::QualityScaledDNAStringSet, and ShortRead::ShortReadQ objects. Non-file inputs are staged to a tempfile before the Java backend runs.
  • numOfThreads defaults to BiocParallel::bpworkers().
  • metabinR_jvm_options() and the metabinR.jvm.flags option let users customise JVM flags at load time without losing the default G1GC + string-deduplication tuning.
  • Parameter validation is centralised via checkmate; errors surface through cli::cli_abort() with classed conditions (metabinR_error_*).

Internal

  • Java sources build via Maven (java/metabinR/pom.xml, tools/build-jar.sh); the shaded JAR is reproducible (project.build.outputTimestamp pinned).
  • Typed JNI entry points on MTxAB, MTxCB, MTxABxCB return tab-separated assignments directly to R, removing the previous round-trip through on-disk CLI output.

MetaboAnnotation

                    Changes in version 1.15

Changes in 1.15.3

  • Use Spectra::rbindlistWithRownames() to expand on the changes introduced in version 1.15.2 supporting also data.frames with row names.

Changes in 1.15.2

  • Use data.table::rbindlist() for merging lists of data.frame’s to improve performance.

Changes in 1.15.1

  • Remove dependency on the msdata package: get test data from MsDataHub.

MetaboAnnotatoR

                   Changes in version 0.99.14
  • Initial Acceptance to Bioconductor

MetaboCoreUtils

                    Changes in version 1.19

Changes in 1.19.3

  • Add functionality to translate between naming schemes used by different software.

Changes in 1.19.2

  • Add beta_values() function for chromatographic peak quality assessment.

Changes in 1.19.1

  • Update unit tests to replace deprecated functions.

MetaboDynamics

                   Changes in version 2.1.104

  • bug fix in estimates_dynamics

                     Changes in version 2.1.103

  • bug fix in estimates_dynamics

                     Changes in version 2.1.101
  • bug fix in fit_dynamics_model()

  • new message in diagnostics_dynamics

                     Changes in version 2.1.100
  • bug fix in plot_PPC for raw_plus_counts_model

  • estimates_dynamics does not return ‘sigma’ or ‘lambda’ anymore

                     Changes in version 2.1.99

  • added model_option in fit_dynamics_model(): either “sd_per_time_point” (only option before) or “sd_per_condition” (less sigmas, more robust with few replicates)

                      Changes in version 2.1.2

  • bug fix in plot_cluster: correct sorting of time points

                      Changes in version 2.1.1
  • cluster_dynamics bug fix: can handle all metabolite names

metabom8

                   Changes in version 0.99.10
  • Initial Acceptance to Bioconductor

MetaProViz

            Changes in version 3.99.40 (2026-02-18)
  • New cluster_pk() function for clustering prior knowledge terms
  • New viz_graph() function for network graph visualization
  • SummarizedExperiment support extended to viz_superplot()
  • Bug fixes in processing(), viz_volcano(), dma(), and ORA functions
  • NA handling improvements for correlation analysis
  • License changed from GPLv3 to BSD 3-clause
  • Code quality improvements for Bioconductor compliance
  • Added ggraph dependency

  • Updated documentation and argument descriptions

              Changes in version 3.99.10 (2025-10-28)
  • SummarizedExperiment support as default input and output

  • First candidate for Bioconductor submission

               Changes in version 3.99.1 (2025-10-08)
  • Fixed Bioconductor timeout issues

  • Code refactoring to meet Bioconductor quality standards

               Changes in version 3.99.0 (2025-09-30)
  • General refactoring to meet Bioconductor checks
  • RCMD check improvements
  • Updated GitHub actions workflows

metaseqR2

             Changes in version 1.23.1 (2026-03-04)

NEW FEATURES

  • None.

BUG FIXES

  • Moved several js libraries locally because of policy changes in highcharts

methyLImp2

             Changes in version 1.7.1 (2025-11-12)
  • Removing documentation of internal functions from the manual.

MetMashR

                    Changes in version 1.5.1
  • Rebuild documentation
  • move cowplot to Suggests
  • add ggplot2 to namespace imports

mia

                    Changes in version 1.19

  • Fixed a bug related to agglomerateByPrevalence and referenceSeq agglomeration (2025-12-08)

  • Use ecodive in UniFrac (1.19.2, 2025-12-09)

  • Added binning transformation (1.19.3, 2026-02-23)

  • Added support for reducedDim in clustering (1.19.5, 2026-03-06)

miaViz

                    Changes in version 1.19

  • plotRDA: Now plotting works with interaction term (2025-11-09)

  • plotBoxplot: Added option to add p-values (2026-01-07)

microbiome

             Changes in version 1.32.2 (2025-07-17)
  • Fixed NEWS file

MicrobiomeProfiler

                   Changes in version 1.17.1
  • use ‘enrichit’ as engine for enrichment analysis (2025-12-07, Sun)

MicrobiotaProcess

                   Changes in version 1.23.1

  • fixed the issue of mp_import_qiime2 due to the new biomformat. (2026-04-02, Thu)

                     Changes in version 1.23.0

  • Bioconductor 3.22 released, and Bioconductor 3.23 (devel) bump. (2025-10-31, Fri)

MIRit

                    Changes in version 1.7.4

This new release of MIRit fixes the rendering of the vignette and updates the documentation website. GitHub worflows have also been updated.

                    Changes in version 1.7.3

This version fixes some minor bugs in the integration analysis, and adds references to the new manuscript in the documentation, README, CITATION, and vignette. A new setTargets() function has also been included.

miRSM

                    Changes in version 2.7.1
  • Update miRSM.R <2026-01-15, Thus>

miRspongeR

                   Changes in version 2.15.2

  • Update moduleDEA.Rd <2026-01-11, Sun>.

                     Changes in version 2.15.1

  • Update miRspongeR.Rmd <2025-12-23, Tues>.

mobileRNA

                    Changes in version 1.7.0
  • Added Namespace dependency to DESCRIPTION Imports/Depends entries: ‘Seqinfo’

monaLisa

                   Changes in version 1.17.1
  • clarifications of supported families for the stability selection

Moonlight2R

                    Changes in version 1.9.4

Summary

  • Made p-value tests for FEA(method=’fgsea’) more qualitative to address low reproducibility of gfsea()

                      Changes in version 1.9.3

Summary

  • Fixed tests for FEA with “fgsea” as method and added new parameter (‘seed’) to the FEA() function for setting random seed and control stochastic perumation-based fgsea scores and p-values.

                      Changes in version 1.9.2

Summary

  • Added new dataset for proteomics data and implemented fgsea method in the FEA function

                      Changes in version 1.9.1

Summary

  • Removed hotfix in GSEA() module

                      Changes in version 1.9.0

Summary

  • Updated version for BioC release

MotifPeeker

                    Changes in version 1.3.3

Miscellaneous

  • Add unsupported platform to DESCRIPTION.

                      Changes in version 1.3.2

Bug Fixes

  • Bound maximum bootstrapping population size.

Misclaneous

  • Update CITATION: MotifPeeker is now published on Bioinformatics Advances!

                      Changes in version 1.3.1

Section Rework

  • Motif-summit distances
  • Remove distances by peak count.
  • Reword descriptions
  • [NEW] Add bootstrapping to visualise the distribution of motif-summit distances.

New Features

  • Add support for directly importing “mm10” and “mm39” mouse genome builds.
  • read_motif_file can now accept an universalmotif object, returns the same object.
  • Input datasets section now reports datasets in a tabular form.

Documentation

  • Improve instructions for importing genome builds.
  • Improve instructions for importing motifs.

motifTestR

                    Changes in version 1.7.2
  • Changed default for min_score to 50% instead of 80%

MouseFM

             Changes in version 1.21.1 (2026-03-22)

  • Improved handling of Ensembl BioMart host and version mismatches

  • Added more informative error messages for BioMart connection and genome version issues

  • Prevented online example execution during package checks

msa

                   Changes in version 1.43.1
  • fix of bug that deleted sequence names if the sequences were read from FASTA file (all three alignment algorithms)

MsBackendMassbank

                    Changes in version 1.19

Changes in 1.19.3

  • Use rbindlistWithRownames() for faster concatenation of results.

Changes in 1.19.2

  • Refactor metaDataBlocks() adding parameters for the individual metadata blocks simplifying configuration of data import.
  • Fix importing issues of individual optional blocks. Import was validated using MassBank releases 2025.05.1 and 2025.10. Several fields/spectra variables now return a list to support records with multiple values per field. These are: “name”, “chrom_solvent”, “comment”, “data_processing_comment”, “sample”, “data_processing_reanalyze”, “data_processing_whole”.
  • Map field MS$DATA_PROCESSING: FIND_PEAK to a spectra variable with name “data_processing_find_peak” (was “data_processing_find”).

Changes in 1.19.1

  • Avoid error when “N/A” is reported as retention time.
  • Performance improvement: use data.table::rbindlist() for merging and importing records from files in MassBank format.

MsBackendMetaboLights

                    Changes in version 1.5.3
  • Use MsCoreUtils::retry() instead of the internal implementation.

  • Improve fail-safe mechanism when caching MS data from MetaboLights.

                      Changes in version 1.5.2

  • Add helper functions mtbls_assay_data(), mtbls_sample_data() and mtbls_metadata().

                      Changes in version 1.5.1
  • Increase number of download retries and increase waiting time in between.

  • Export the retry() function.

                       Changes in version 1.5

MsBackendMgf

                    Changes in version 1.19

Changes in 1.19.1

  • Use data.table::rbindlist() instead of MsCoreUtils::rbindFill() to combine individual spectra’s data.frames into a single one. This can have performance improvements, in particular for large MGF files.

MsBackendMsp

                    Changes in version 1.15

Changes in 1.15.1

  • Use data.table::rbindlist() to combine individual spectra into one resulting data.frame/DataFrame in readMsp(). This improves the performance of readMsp() as well as backendInitialize() in particular for large MGF files.

Changes in 1.11.1

  • Complete unit test coverage.

MsBackendSql

                    Changes in version 1.11

Changes in 1.11.3

  • Remove dependency from the msdata package: load test data from the MsDataHub package.

Changes in 1.11.2

  • Small update to the internal function to extract the spectra data: avoid fmatch() call if not needed.
  • Pass sorted spectra IDs to the SQL query, which can result in a tiny performance gain.

Changes in 1.11.1

  • For storage mode of peaks data in long form (i.e., one row per peak), create a incremental (unique) peak_id_ database column if the database requires that (e.g. for DuckDb).
  • longForm() on a database requiring peak_id_ (e.g. DuckDb) order results based on the peak_id_ column.

MsCoreUtils

                    Changes in version 1.23

MsCoreUtils 1.23.10

  • Fix partial argument match warnings.
  • Fix bug in impute_mixed() and allow for two MARGINs for mixed imputation.
  • Remove the … in impute_mixed()`.

MsCoreUtils 1.23.9

  • Handle all type of error in retry(), not only simpleError.

MsCoreUtils 1.23.8

  • Add parameters warningsAsErrors and verbose to retry().

MsCoreUtils 1.23.7

  • Add retry() function.

MsCoreUtils 1.23.6

  • Fix unsupported Unicode characters in documentation.
  • Fix join_gnps() to support also type being different from “outer”.

MsCoreUtils 1.23.5

  • rbindFill(): improve performance when joining only matrices.

MsCoreUtils 1.23.4

  • gnps() and join_gnps() use C implementations for modified cosine similarity calculation. The original R implementations are available as gnps_r() and join_gnps_r(). See issue #131 for discussion and performance comparison.
  • FastCosine spectral similarity calculation implementation: gnps_chain_dp().

MsCoreUtils 1.23.3

  • Add parameter matchedPeaksCount to spectra similarity/distance functions to report, in addition to the similarity, also the number of matched peaks.

MsCoreUtils 1.23.2

  • Fix Found non-API call to R: ‘SETLENGTH’ in C_reduce, C_join_inner, and C_join_outer by using lengthgets() instead (see issue 136).
  • Use Rf_ prefix for R API functions and set R_NO_REMAP to avoid use of accidentially using non-Rf_ prefixed functions in future.

MsCoreUtils 1.23.1

  • Fix RF imputation, that now needs dimnames.

MsCoreUtils 1.23.0

  • New devel version

MsDataHub

                   Changes in version 1.11.5

  • Fix metadata

                     Changes in version 1.11.4
  • Add DDA and DIA proteomics data to illustrate QFeatures::readQFeatures().

  • Various fixes.

                     Changes in version 1.11.3
  • Add Boekweg et al. (2022) SCP and bulk mzML files, and Sage identification TSV files (see ?Boekweg2022)

  • Added Guillaume Deflandre as contributor.

                     Changes in version 1.11.2

  • Add MS3TMT data files.

                     Changes in version 1.11.1
  • Add CE-MS test data files (see PR #11).

  • Add description of the data sets to the package vignette.

                      Changes in version 1.11

MsExperiment

                    Changes in version 1.13

Changes in 1.13.1

  • Load test data from MsDataHub and remove dependency on the msdata package

MSnbase

                    Changes in version 2.37

2.37.3

  • Bump version to make sure the latest updates get published on Bioc.

2.37.2

  • Fixing vignette (see #613)
  • use MsDataHub for TMT and PestMix1_DDA data.

2.37.1

  • Fixing tests

2.37.1

  • Remove rols dependency.
  • Remove pryr dependency.

msPurity

                   Changes in version 1.37.3

  • Update within the tests only (not within the R code base): library database path for lvl spectral matching testing (required after removal of the local SQLite database from msPurityData).

                     Changes in version 1.37.2

  • Bug fix for subsetting the grouped data frame in the average_xcms_grouped_msms_indiv function

                     Changes in version 1.37.1

  • Removed library_spectra.db direct reference from msPurityData package (too large for Bioconductor)

  • spectralMatching() now downloads default library database from Zenodo (https://zenodo.org/records/18700802) and uses BiocFileCache with MD5 verification

  • spectral_matching() (deprecated function) now requires explicit library_db_pth parameter; default library no longer available

  • Added BiocFileCache to Imports for automatic caching of remote databases

msqrob2

                    Changes in version 1.19

msqrob 1.19.1

  • Add functions to calculate log-normalisation factors that can be used with sweep function
  • Add function msqrobCollect to collect results tables
  • Add function plotVolcano to make volcanoplots for hypothesisTest tables
  • Add function createPairwiseContrasts to generate contrasts for all pairwise comparisons
  • Illustrate these new functionalities in the vignettes
  • New Vignettes for DIA (DIA-NN and Spectronaut)

msqrob2 1.19.2

  • Update cptac vignette (fread with argument check.names = TRUE)

msqrob2 1.19.3

  • Update vignettes (arguments fread check.names = TRUE and integer64 = “double”) to avoid issues with readQFeatures
  • Update README to point to msqrob2book

MsQuality

                    Changes in version 1.11

1.11.3 (2026-03-10)

  • Implementation of per-chromatogram metrics for Chromatograms objects: maxIntensity, intensityMean, intensitySd, intensityQuartiles, intensityRange, peakCount, baselineIntensity, signalToNoiseRatio, xicFwhm, peakBoundary, peakWidth, gaussianSimilarity, peakProminence
  • Shared functions (chromatographyDuration, rtAcquisitionRange, rtIqr, areaUnderTic, areaUnderTicRtQuantiles, ticQuantileRtFraction, msSignal10xChange, medianTicRtIqr, numberEmptyScans, calculateMetrics) now support both Spectra and Chromatograms
  • msSignal10xChange gains minIntensity parameter for noise robustness.
  • Renamed argument filterEmptySpectra to filterEmptyObject
  • Fixed calculateMetrics() data.frame output
  • Fixed shinyMsQuality() documentation example

Changes in version 1.11.2 (2026-03-02)

  • replace msdata by MsDataHub package (issue #19)
  • adjust all examples, unit tests and vignette to the MsDataHub package

Changes in version 1.11.1 (2026-02-17)

  • added conversion to uri from local file to the export function in transformIntoMzQC (contribution by Helge Hecht, PR #20)

Changes in version 1.11.0 (2025-10-29)

  • bump version to 1.11.0

MSstatsConvert

                   Changes in version 1.22.0

Protein Turnover Support

  • DIA-NN: DIANNtoMSstatsFormat now accepts a labeledAminoAcids parameter to enable protein turnover workflows. Provide the single-letter amino acid codes that carry the SILAC label (e.g. c(“K”) or c(“K”, “R”)). The converter automatically distinguishes heavy and light peptide forms — either from a Channel column in DIA-NN 2.x exports, or by parsing SILAC modification tags (e.g. (SILAC-K-H)) in DIA-NN 1.x exports — and populates the IsotopeLabelType column required by MSstats downstream.

  • Spectronaut: SpectronauttoMSstatsFormat now accepts a heavyLabels parameter to classify peptides in protein turnover experiments. Supply the label names as they appear in square brackets in the peptide sequence (e.g. c(“Lys6”) or c(“Lys6”, “Arg10”)). Peptides are automatically assigned as heavy (H), light (L), or unlabeled. Any novel label name reported by Spectronaut (e.g. “Leu6”, “Phe10”) is supported.

  • Spectronaut: A new peptideSequenceColumn parameter lets you specify which column in your Spectronaut export contains the peptide sequence. This is especially useful for protein turnover reports, which may use a different column layout than a standard Spectronaut output.

  • Spectronaut: Protein turnover reports that lack fragment-level columns (e.g. FFrgLossType, FFrgIon) are now handled automatically — previously these required manual pre-processing before import.

  • Fraction selection: The algorithm that selects the best fraction for each peptide feature now correctly accounts for heavy and light isotope channels in protein turnover data, ensuring that light-channel coverage is prioritized when choosing fractions. When multiple fractions have identical coverage, the fraction with the highest mean intensity is chosen.

DIA-NN Quality Control: Anomaly Detection

  • DIANNtoMSstatsFormat now supports automated data quality scoring via an isolation-forest anomaly detection model (calculateAnomalyScores = TRUE). When enabled, each precursor-level feature receives an anomaly score that can be used downstream in MSstats to down-weight measurements that look like outliers. Users supply the quality metric columns to use as model features (anomalyModelFeatures) and, optionally, a run order table (runOrder) to engineer temporal trend features that detect gradual instrument drift across an experiment.

Spectronaut: MS1 Quantification

  • SpectronauttoMSstatsFormat now accepts “FG.MS1Quantity” (and other raw Spectronaut column names) as the intensity argument, in addition to the existing “PeakArea” and “NormalizedPeakArea” options.

MultiAssayExperiment

                   Changes in version 1.38.0

Bug fixes and minor improvements

  • Fixed bug in getWithColData when colData from i object did not align with sampleMap(mae) colname order (@aboyoun / James Bonaffini, #346)

MungeSumstats

                   Changes in version 1.19.4

Bug fix

  • convert p-values from 0 to 1e-300 when imputing z-score

                     Changes in version 1.19.3

Bug fix

  • Add more documentation for chr checks

                     Changes in version 1.19.2

Bug fix

  • liftover() couldn’t previously handle CHR outside of 1-22, added functionality following the same logic as format_sumstats()

                     Changes in version 1.19.1

Bug fix

  • Update approach to download from ieugwasr.

muscat

                   Changes in version 1.25.4

  • update Gilis et al. citation for DD

  • remove ‘cowplot’ in favor of ‘patchwork’

  • move ‘IHW’, ‘DESeq2’ and ‘sctransform’ to ‘Suggests:’

  • omit ‘data.table’ and ‘purrr’ everywhere and remove from ‘Imports:’

  • #102 fix: use correct CPM values in ‘resDS’ when ‘method=limma-voom’

                     Changes in version 1.25.3

  • up R version dependency to ≥ 4.6

  • rename ‘edgeR::calcNormFactors’ to ‘normLibSizes’

                     Changes in version 1.25.2

  • bug fix in ‘.mm_dream’ (underlying ‘mmDS’ methods ‘poisson’ and ‘nbinom’): transform size factors from linear- to log-scale before being used as offset

                     Changes in version 1.25.1

  • fix #146: support for sparse matrices by ‘pbDS’

  • updated Germain et al. citation for BBHW

MutSeqR

             Changes in version 0.99.4 (2025-12-09)

Preparing for Bioconductor release. We address comments from Bioconductor reviewers. Major changes include parameter validation and vectoriation of functions. filter_mut() “snv_in_germ_mnv” parameter was fixed such that it now only filters out overlapping snvs if their variation matches that of the germline mnv (previously it was blanket removing all snvs that overlap with germline mnvs). plot_lollipop() can now colour the plot by different subtype resolutions (previously just base_6). Fixed plot_spectra() axes labels after clustering (previously not showing labels).

             Changes in version 0.99.3 (2025-10-10)

Fix dependencies for Bioconductor release.

             Changes in version 0.99.2 (2025-09-15)

Preparing for Bioconductor release. This change removes bmd_toxicR from the package. ToxicR dependency is not supported by Bioconductor. See ToxicR_archive branch for bmd_toxicr function. Modifies signature_fitting() to use SigProfilerMatrixGenerator python dependency rather than R dependency.

             Changes in version 0.99.1 (2025-08-13)

Preparing for Bioconductor release. This change adds MutSeqRData to suggests, and alters how the examples are run (now depends on the ExperimentHub accessions).

             Changes in version 0.99.0 (2025-06-19)

Initial public version.

Major changes

  • Added filter_mut() to workflow: germline identification via vaf_cutoff, region filtering, and depth correction now occur here instead of the import functions.
  • calculate_mut_freq() is renamed to calculate_mf().
  • calculate_mf() no longer requires depth; users may:
    1. calculate depth from mutation data,
    2. supply a separate depth table, or
    3. omit depth entirely (only mutation counts returned).
  • correct_depth option moved to calculate_mf().
  • plot_spectra(), plot_trinucleotide(), and spectra_comparison() now use mf_data instead of raw mutations.
  • Output options added: VCF, FASTA, SigProfiler-compatible format, Excel workbook.
  • Example dataset (~44MB) added.

New features

  • render_report() added for standardized summary reporting.

Other

  • Removed custom_regions parameter; replaced by generalized regions argument.
  • Public release 🎉
  • See the vignette for details.

mzR

                   Changes in version 2.45.1

  • Load test files from the MsDataHub package and remove dependency on the msdata package.

  • Catch error in spectrum ID parsing.

  • Remove support for C++11 and C++14 from R-devel (see issue #315)

NanoMethViz

                    Changes in version 3.8.0
  • Addes sorting to the heatmap so reads appear from most to least methylated. This is done by calculating the average methylation across the region for each read and sorting by this value.

netboost

             Changes in version 2.19.3 (2026-02-12)

  • Consensus network calling.

               Changes in version 2.19.2 (2026-02-11)

  • Speed up of filter calculation.

NormalyzerDE

                   Changes in version 1.29.2
  • Update maintainer list, adding Måns Zamore as an author

notame

                    Changes in version 1.1.0

New features

  • All feature data columns that differ between batches are now retained when merging batches: the most common flag value across batches is included in the “Flag” column in the merged object

  • Added function read_from_msdial() which reads MS-DIAL output files (tab-separated .txt files) into a SummarizedExperiment object

  • Improved type conversion when importing data with notame functions

Bug fixes

  • Fixed an issue where metadata was not properly retained when joining new data with join_rowData() and join_colData()

notameViz

                    Changes in version 1.1.0

New features

  • plot_injection_lm() now utilizes limma for p-value calculation, resulting in improved performance (instant plotting)

  • Merging QC plots in save_QC_plots() does not require external software in Windows/Linux

Bug fixes

  • save_QC_plots() now correctly uses “QC” as default color option

  • Fixed an issue that prevented using custom color scale in plot_effect_heatmap()

OmnipathR

                    Changes in version 4.0.0

Features

  • ID translation ambiguity analysis
  • KEGG REST API client
  • New metabolomics resources: HMDB, RaMP, Chalmers Sysbio GEMs, STITCH,
  • Metabolite-protein interactions from MetalinksDB
  • Metabolite ID translation using RaMP and HMDB data

Technical

  • Rewritten and improved parameter processing for OmniPath queries
  • Rewritten downloaders based on curl and httr2
  • Fine control over curl handlers
  • Detailed log messages about HTTP requests
  • Diagnostic log messages: session info, libraries, versions, platform info, curl options, HTTP timings, headers
  • Option to include curl debug log in the log file
  • Robust TCP keep-alive parameters that hopefully fix rest.uniprot.org dowloads

omXplore

                    Changes in version 1.5.1

  • 1.5.1 - Replaced highcharter by plotly

  • This is the first release of omXplore.

OncoSimulR

             Changes in version 4.13.4 (2026-04-16)

  • Fixed miscell minor notes and warnings from r-universe.

               Changes in version 4.13.3 (2026-04-14)

  • Upgraded exprtk to version from 2025-01-01, commit cebb369.

  • And proper use of all.equal with check.attributes = FALSE!

               Changes in version 4.13.2 (2026-04-14)

  • Fixed the “More than one VignetteEngine specified” error in r-universe.

  • Added unexported complete_fitness_landscape function.

  • Added a few magellan epistasis tests.

  • Removed an equality comparison of floats.

               Changes in version 4.13.1 (2026-01-31)

  • Fixed NOTES in “R CMD check –as-cran”

orthogene

                   Changes in version 1.17.4

Bug fixes

  • run_benchmark_once(): replace message(e) with message(conditionMessage(e)) inside the tryCatch error handlers. Passing a condition object to message() re-signals it, and under testthat’s calling handlers an error condition signaled this way escapes the tryCatch and is reported as a test failure — even though tryCatch did catch it. This caused test-run_benchmark to fail on GitHub Actions whenever the g:Profiler API returned malformed JSON, even though run_benchmark_once() was supposed to record NA and move on.

                     Changes in version 1.17.3

Bug fixes

  • Make examples of convert_orthologs(), map_orthologs(), and all_genes() use method = “homologene” so they don’t depend on the g:Profiler API. The remote g:Profiler service has been intermittently returning JSON with literal NaN tokens, which jsonlite cannot parse, causing the Bioconductor R CMD check for examples to fail.
  • Tests that incidentally exercised the default g:Profiler path (test-aggregate_mapped_genes, test-convert_orthologs, test-infer_species) now request method = “homologene” explicitly.
  • Tests that intentionally cover the g:Profiler backend (test-all_genes_gprofiler, the method = “gprofiler” block in test-convert_orthologs) now skip gracefully with a clear message when the API is unavailable, rather than halting the whole suite.
  • test-run_benchmark: aggregate mean() checks now use na.rm = TRUE so a transient g:Profiler failure doesn’t NA-poison the benchmark assertions.

  • test-infer_species: tolerate ties in top_match so that when two species are equally well-matched (e.g. human and monkey via babelgene), the test passes as long as the expected species is among them.

                     Changes in version 1.17.2

New features

  • all_genes: enable method/species-specific caching.
  • run_benchmark_once: enable caching
  • cache_dir(): new function for consistency
  • map_orthologs_gprofiler: BIG upgrade! Can now rapidly query large gene lists via batching and parallelzation without server-side timeout errors.
  • Improve test coverage.

OUTRIDER

                   Changes in version 1.28.1
  • Adapt to new testthat behaviour (#87)

parati

             Changes in version 0.99.8 (2026-04-12)
  • Initial Acceptance to Bioconductor

pcaExplorer

                    Changes in version 3.6.0

Other notes

  • pcaplot() labels now all samples with a segment connector in grey to increase its visibility on a bw/classic theme

Pedixplorer

                    Changes in version 1.7.1
  • Fix slices in circfun()
  • Add contributing guidelines
  • Replace dplyr pipe %>% by >

phantasus

                   Changes in version 1.31.1

  • dedicated docker server script to reduce memory usage

  • fixes in annotation parsing

philr

                   Changes in version 1.37.1

USER-VISIBLE CHANGES

  • Updating documentation (and vignette) to make input format for philr function clearer.

PIUMA

                    Changes in version 1.8.0
  • PIUMA now identifies clusters and can be easily integrated in the Seurat workflow

plaid

                   Changes in version 0.99.0

INITIAL RELEASE

  • plaid: ultra-fast single-sample enrichment scoring using rank-based statistics

  • replaid methods: fast implementations of popular enrichment methods (ssGSEA, GSVA, singscore, UCell, AUCell, scSE)

  • dualGSEA: statistical testing for differential enrichment with dualGSEA

  • Full Bioconductor integration with SummarizedExperiment, SingleCellExperiment, and BiocSet support

  • GMT utilities for reading, writing, and converting gene set files

  • Performance optimizations including sparse matrix support and parallel processing

PlinkMatrix

                   Changes in version 0.99.5
  • Initial version

PLSDAbatch

                   Changes in version 1.99.1
  • Date: 2026-01-06
  • Text: Fix the figure display issue

  • Details: Fix the issue where Figures 2 and 3 are not shown in the vignette.

                     Changes in version 1.99.0
  • Date: 2025-12-26
  • Text: improve usability
  • Details:
  • Added a mode argument to PLSDA_batch().
  • Added a criterion argument to linear_regres() to select P-values from the optimal model based on the specified criterion.
  • Added a return.model arugument to linear_regres() to reduce memory usage when set to FALSE.
  • Extended Scatter_Density() to support any multivariate method that returns component scores, including PCA and PLS, with corresponding arguments updated.
  • Added lighten() and darken() functions for enhanced color generation.
  • Refined multiple functions to improve usability.
  • Updated the vignette accordingly.

plyranges

                   Changes in version 1.32.0
  • added new functionality for slice_*, as in dplyr, including head, tail, max, min and sample. These include the dplyr arguments such as n, prop, and weight_by (for sampling).
  • added join_mcols_left(x,y) for GRanges x and tabular y

  • added distance=TRUE option for join_overlap_*

                     Changes in version 1.31.5
  • added distance=TRUE option for join_overlap_*
  • added join_mcols_left(x,y) for GRanges x and tabular y

pmp

                   Changes in version 1.23.1
  • fix broken test due to changes in RF imputation

posDemux

                   Changes in version 0.99.9
  • Initial Acceptance to Bioconductor

postNet

                   Changes in version 0.99.9
  • Initial submission to Bioconductor

pRoloc

                    Changes in version 1.51

Changes in version 1.51.1

  • Bump version for Bioc devel

Changes in version 1.51.0

  • New version for devel

pRolocGUI

                   Changes in version 2.21.2

  • New version for Bioc release

                     Changes in version 2.21.1

  • Fix bug in explore app

                      Changes in version 2.21                         

                 Changes in version 2.21.0

  • New version for Bioc devel 3.23

psichomics

                   Changes in version 1.36.1
  • GTEx data loading (loadGtexData()):
  • Support for loading GTEx V10 data
  • Documentation:
  • Remove confusing instructions on launching psichomics from README
  • Improve Docker instructions on README
  • Update external function documentation
  • Update license copyright years
  • Update email contact
  • Bug fixes:
  • Fix interface not loading for collapse panels
  • Fix eBayes error on graphical interface
  • Fix unit tests when testing shiny buttons

PSMatch

                    Changes in version 1.15

PSMatch 1.15.3

  • Adjusted documentation on addCarbamidomethyl = TRUE in calculateFragments() set by default.
  • Corrected plotSpectraPTM() relative PTMods dependencies, identifications are highlighted in bold in the USI. Added parameters to call addFixed and addVariable within plotSpectraPTM().
  • Add PTMods dependency and thus positional modifications in calculateFragments() (see issue 38)

PSMatch 1.15.2

  • Use MsDataHub instead of msdata.

PSMatch 1.15.1

  • Fix minor check notes (Rd link and IRanges import)

PSMatch 1.15.0

  • New devel version

PTMods

                    Changes in version 0.99
  • Initial Acceptance to Bioconductor

QFeatures

                    Changes in version 1.21

QFeatures 1.21.4

  • Add new readQFeautres vignette.

QFeatures 1.21.3

  • Add readQFeaturesFromDIANN(multiplexing = ‘dimethyl’) example.
  • New replaceColnames() function (see Issue 258)

QFeatures 1.21.2

  • Add support for dimethyl multiplexing to readQFeaturesFromDIANN() (see PR #249), contributed by Karolína Kryštofová.
  • Aggregate redundant messages in aggregateFeatures() (PR #255).
  • Add a progress bar to aggregateFeatures() and readQFeatures() (PR #255).

QFeatures 1.21.1

  • Link to RforMS contribution guide.

QFeatures 1.21.0

  • New devel version

qPLEXanalyzer

                   Changes in version 1.29.3

  • Update maVolPlot man page

                     Changes in version 1.29.2

  • Update to getContrasts man page example to account for changes in limma::topTable

                     Changes in version 1.29.1

  • Update to getContrasts to account for changes in limma::topTable

  • Update to maVolPlot to account fo changes in limma::topTable

QTLExperiment

             Changes in version 2.3.1 (2026-01-06)
  • Updated documentation for sumstats2qtle() to remove warning.

QUBIC

                   Changes in version 1.39.0
  • Runtime dependency on biclust is removed

queeems

                   Changes in version 0.99.5
  • Initial Acceptance to Bioconductor

RankMap

                   Changes in version 0.99.1

Initial submission to Bioconductor

New Features

  • Fast, robust, and scalable reference-based cell type annotation using multinomial regression on ranked expression matrices.
  • Supports both single-cell and spatial transcriptomics data.
  • Compatible with Seurat, SingleCellExperiment, and SpatialExperiment objects.
  • Core function RankMap() provides a streamlined pipeline for preprocessing, model training, and prediction.
  • Customizable preprocessing: top-K gene masking, optional binning, expression weighting, and scaling.
  • Additional functions:
  • computeRankedMatrix() – generate ranked matrices
  • trainRankModel() – train multinomial GLM
  • predictRankModel() – apply trained model to query data
  • evaluatePredictionPerformance() – assess accuracy
  • Optimized for large datasets with significantly faster runtime than SingleR, Azimuth, and RCTD.

Rarr

                    Changes in version 1.99

Breaking changes

  • The DelayedArray backend (writeZarrArray() and ZarrArray() functions) has been migrated to a separate, dedicated package. This reduces the number of dependencies from 37 to 24. This also greatly improves performance in for the standard case (when the DelayedArray backend is not used).
  • write_zarr_array() now writes Zarr v3 by default. Writing Zarr v2 is still possible by explicitly setting the argument zarr_version = 2.

New features

  • Zarr v3 arrays with data types and codecs that already existed in v2 can now be read via read_zarr_array(), and written via write_zarr_array().
  • Zarr v3 consolidated metadata is now returned by zarr_overview(), the same way it was already previously done for v2 consolidated metadata.
  • More data types are available when writing Zarr arrays:
  • boolean / logical
  • int8
  • int16
  • int64 (up to values that can be represented as R integers)
  • uint8
  • uint16
  • uint32 (up to values that can be represented as R integers)
  • uint64 (up to values that can be represented as R integers)
  • float32 / single
  • Scalar arrays (i.e., arrays with zero dimensions) can now be read. Thanks to Artür Manukyan for the bug report.
  • Zarr attributes can now be read by passing an s3 URL directly as the first argument of read_zarr_attributes(). This makes read_zarr_attributes() consistent with read_zarr_array() and zarr_overview().
  • “Simple” structured data types (i.e., only one level of nesting and no arrays) can now be read from Zarr v2 arrays.
  • simplifyVector = FALSE is added to fromJSON in read_zarr_attributes(), thus attributes of both local and s3 zarr stores are read identically.
  • The dimension_names optional field is support in both v2 (not strictly part of the spec) and v3. It is mapped to names(dimnames(.)) in R.
  • NA_real_ is now an allowed fill value in write_zarr_array() when writing numeric arrays, following a request from Hervé Pagès.
  • Fill values stored as their byte representation are now understood when reading Zarr arrays.
  • write_zarr_array() now supports writing NA_character_, which means it is possible to preserve NAs when roundtriping an R character array, based on a request from Hervé Pagès.

Minor improvements

  • There is now a dedicated vignette describing the supported Zarr features in Rarr, available at https://huber-group-embl.github.io/Rarr/articles/features.html. This makes it more easily discoverable on the Bioconductor landing page.
  • Rarr initializes empty/missing chunks only once per read operation, which significantly improves performance when reading arrays with many missing chunks.
  • Reading fixed-length string and unicode arrays is now ~20% faster.
  • The shape and chunks fields in v2 metadata are now always encoded as JSON arrays, even when they contain a single element. This makes Rarr more compatible with other Zarr implementations. Thanks to Artür Manukyan for the bug report and pull request.
  • Empty zarr arrays (i.e., arrays with shape and chunks equal zero) can now be written.
  • Compression for writing Zarr arrays now default to zstd rather than zlib. zstd achieves similar or better compression levels while being much faster at compressing (= writing Zarr arrays) and decompressing (= reading Zarr arrays). This matches the default used by Zarr Python implementation.
  • write_zarr_array() now fails early with an explicit error message when x is not an array.

Bug fixes

  • Rarr is now fully compatible with big endian platforms.
  • ZSTD decompression now also works in case where we cannot guess a priori the buffer size from the data type, such as when using variable length strings. Thanks to Artür Manukyan for the bug report and test data.
  • zarr_overview() no longer fails on consolidated metadata containing uncompressed arrays. This was introduced in https://github.com/Huber-group-EMBL/Rarr/pull/45. Thanks to Sharla Gelfand for reporting the issue and providing test data.
  • the fill_value is now correctly interpreted when reading Zarr v2 string or unicode arrays. This is visible for example when trying to read missing chunks from such arrays. Thanks to Artür Manukyan for the bug report.

Internal changes

  • Some internal changes are preparing the transition to support Zarr v3:
  • “C” and “F” fill orders are now handled via a codec mechanism, which also supports a wider range of transpose operations.
  • The endian configuration is now handled via a codec.
  • A GitHub Actions workflow has been added to occasionally test this package on a big endian platform.
  • Bundled libraries have been updated:
  • blosc 1.20.1 -> 1.21.6
  • snappy 1.1.1 -> 1.2.2
  • zstd 1.5.5 -> 1.5.7
  • lz4 1.9.2 -> 1.10.0
  • Resizable vector in C code for compression now uses the official exported R C API, instead of internal R functions.
  • The const qualifier is used where appropriate in the C code.

RBedMethyl

                   Changes in version 0.99.0
  • Initial Bioconductor submission with core functionality:
  • Disk-backed import of modkit bedMethyl files via readBedMethyl() with HDF5Array storage.
  • Field discovery with bedMethylFields().
  • Per-site methylation fraction via beta().
  • Assay-based filtering with subsetBy() and filterByCoverage().
  • Genomic subsetting by interval and GRanges with subsetByRegion() and [.
  • Region-level summaries with summarizeByRegion().
  • Coercion to RangedSummarizedExperiment and optional BSseq.
  • Vignette and runnable examples.

Rbwa

                   Changes in version 1.15.3

  • Added Config field in DESCRIPTION file for newest BioC deployment

                     Changes in version 1.15.1

  • Changed DFLAGS to LDFLAGS in Makefile.

RCX

             Changes in version 1.14.2 (2026-03-19)

  • Fix: Previously, toIgraph required the RCX object to contain an edges aspect, making it impossible to convert node-only networks to igraph. The function now handles edgeless networks.

               Changes in version 1.14.1 (2026-01-20)

  • Fix: cyGroups follows a different naming structure in the JSON export. Updated the export function accordingly. Also the CyGroup ids have to be present in RCX object, a check for those references has been added.

ReactomeGSA

             Changes in version 1.25.1 (2026-01-28)
  • Adapted code due to changes in Seurat V5

ReactomePA

                   Changes in version 1.55.1
  • use ‘enrichit’ as engine for enrichment analysis (2025-12-07, Sun)

recount3

                   Changes in version 1.21.1

BUG FIXES

  • Switched from pryr to lobstr. This was done by @gpertea.

RedisParam

                   Changes in version 1.14.0
  • (1.13.1) Use ‘logger’ rather than ‘futile.logger’.

Rega

                   Changes in version 0.99.3
  • Initial public release.
  • Provides excel template for filling in submission data
  • Implements the core workflow:
  • default_parser() – Parses submission data from excel template
  • create_client() - Creates API client based on specification
  • new_submission() – Submits parsed data to EGA through created API client
  • Provides methods for data validation default_validator()
  • Includes vignette for basic usage

RFGeneRank

                   Changes in version 0.99.4
  • Initial Acceptance to Bioconductor

rGREAT

                   Changes in version 2.13.1
  • fix docs

rhdf5

                   Changes in version 2.56.0

Breaking changes

  • The default value for the bit64conversion argument in H5Aread() and H5Dread() has been set explicitly to "int". Relying on a missing value or "default" results in a warning and will be disallowed in the next release cycle. Users should either specify bit64conversion="int" explicitly, or omit this argument entirely if they wish to use the provided default.

  • The native argument to H5Pcreate() now triggers an explicit deprecation warning and will be removed in the next release cycle. This argument was already documented as defunct (without warning) in Bioconductor 3.10.

  • This package now uses HDF5 version 1.14.6 via Rhdf5lib 1.33.3.

Bug fixes

  • The value ordering (row-major vs column-major) is not correct when reading unsigned integers with native=TRUE. Thanks to Jared Lumpe for the report and detailed reproducible example: https://github.com/Huber-group-EMBL/rhdf5/issues/157.

  • Minor memory protection issues identified by rchk has been resolved. This might prevent some rare crashes.

  • Subsetting and assignment via [ and [<-` operators using a variable to define the indices now works as expected. This was due to an issue in the timing of evaluation of the index arguments. Thanks to Michael Schubert and Malcolm Perry for the report and reproducible example: https://github.com/Huber-group-EMBL/rhdf5/issues/69.

  • Subsetting with drop=FALSE no longer errors. Thanks to Michael Schubert for the report: https://github.com/Huber-group-EMBL/rhdf5/issues/68.

Minor changes

  • Documentation for the name argument as well as the error message when trying to work on a non-existing object now include a hint to use h5ls() to list the objects in a file. Inspired from a suggestion from Frederik Ziebell.

  • A warning about void pointer arithmetic in H5Aread_helper_ENUM (C code) has been resolved. This increases portability across different compilers.

  • The H5type argument in h5createAttribute() and h5createDataset() now behaves more consistently across both functions. Both functions now accept either a HDF5 data type id as a string, or the output of H5Tcopy(). Thanks to Luke Zappia for the report: https://github.com/Huber-group-EMBL/rhdf5/issues/162.

  • h5version() now also reports the version of the Rhdf5lib package.

Internal changes

  • Code coverage reports via codecov have been restored.

  • The pkgdown documentation website for this package have been restored.

  • Static analysis via the lintr package is now continuously changed on every changes via GitHub Actions.

  • Number of skipped tests (when testing, e.g., features only available in certain situations) is now explicitly reported.

  • GitHub Actions now run on ARM64 versions of all operating systems.

  • rchk is now part of our continuous integration setup to detect potential memory issues in the C code.

rhdf5filters

                   Changes in version 1.24.0

BUG FIXES

  • This package now compiles on -std=c23. This was an issue in the bundled blosc library. Thanks to Alexander Bontempo for reporting the issue.
  • A R CMD check NOTE about bashims has been resolved.

MINOR CHANGES

  • This package no longer bundles the bzip2 compression library, and uses the system version instead. bzip2 is required by R itself so it is expected to be available on all systems.

Rhdf5lib

                     Changes in version 2.0

Breaking changes

  • Build system has been changed from Make to CMake, via the biocmake Bioconductor package. Thanks to Aaron Lun (@LTLA) for the initial work on the migration.

  • The HDF5 version bundled by Rhdf5lib has been upgraded from 1.10.7 to 1.14.6.

rhinotypeR

           Changes in version 2025-10-21 (2025-10-21)

Fixed

  • Example and test errors related to internal helpers (compareAndColorSequences(), compute_cache()) now handled safely using \dontrun{} and updated documentation.
  • Removed outdated License stub issue and corrected DESCRIPTION metadata formatting.
  • Corrected internal tests referencing deprecated testthat::local_null_device().

Improved

  • CountSNPs() re-implementation: directly computes pairwise SNP counts without relying on model-based rounding (e.g., from MSA2dist). No rounding artifacts

             Changes in version 2025-10-01 (2025-10-01)

Added

  • New function: alignToRefs(), which aligns user sequences to the packaged rhinovirus prototype references using msa::msa() (ClustalW, ClustalOmega, or MUSCLE), with an option to trim alignments to the non-gap span of a chosen reference.

Improved

  • SNPeek() and plotAA(): now support zooming to specific genomic regions and highlighting individual sequences of interest.
  • assignTypes(): now reports the genetic distance to the nearest prototype even when the query is “unassigned”.
  • Distance calculation: switched to using MSA2dist for pairwise distance computation. This provides broader model support — access to all substitution models in ape::dist.dna, in addition to the “IUPAC” model.
  • Data access: prototype and example datasets are now exported as packaged objects (rhinovirusVP4, rhinovirusPrototypesVP4) instead of being accessed via system.file(), simplifying workflows.
  • Improved documentation:
  • Improved explanations and runnable examples added where feasible.
  • Visualization functions return results invisibly to avoid console clutter, while still allowing advanced users to capture outputs.
  • Code style and formatting improved (e.g.,consistent internal helpers).

RNAshapeQC

                   Changes in version 0.99.10
  • Initial Acceptance to Bioconductor

rols

                    Changes in version 3.7.1

  • Fix bug in rols::Ontologies() (see #48)

                       Changes in version 3.7

SAIGEgds

                   Changes in version 2.12.0
  • fix a C++ error that ‘span’ is ambiguous

scAnnotatR

             Changes in version 1.17.1 (2026-01-15)
  • Adapted to address changes in Seurat object structure.

SCArray

                   Changes in version 1.20.0
  • fix the package anchors for all Rd \link{}

SCArray.sat

                   Changes in version 1.12.0
  • update according to Seurat v5

scConform

                   Changes in version 0.99.1
  • New package scConform, for uncertainty quantification for cell type annotation using conformal inference

scDiagnostics

                    Changes in version 1.6.0
  • Renamed gene shift function for consistency (previously calculateTopLoadingGeneShifts())
  • Added gene specification parameter to calculateGeneShifts()
  • Improved calculateGeneShifts() function, plot method, and color scheme

scECODA

                   Changes in version 0.99.7
  • Adopted SummarizedExperiment data structure

scider

             Changes in version 1.10.0 (2026-04-25)
  • Update help pages
  • New function getHVG() to find top HVGs
  • New function plotLISAscatter() to generate a LISA scatter plot
  • New functions readVisium(), readVisiumHD(), readXenium(), readProseg() for reading in data of different types
  • Use Matrix package for matrix operations
  • Update gridDensity() to handle different types of input
  • Speed up hexDensity computation

scifer

                   Changes in version 1.12.1
  • fix minor bug that crashed quality_report when some sequences had problematic quality and had NA or Inf values
  • this affects summarise_quality and summarise_abi_file

scLANE

                    Changes in version 1.1.2

  • Trying to fix Seurat slot vs. layer deprecation error once again.

                      Changes in version 1.1.1

  • Fixed a deprecation error in geneProgramScoring().

scLang

             Changes in version 0.99.0 (2025-12-27)
  • Submitted to Bioconductor

scoup

                    Changes in version 1.5.1

  • Extended the vignettes/exData folder to incorporate reviewers suggestions.

  • Updated the paper, inst and vignettes folders in response to editor’s queries.

  • Fine-tuned paper and necessary files as part of final JOSS requirements.

  • Updated citation.

scp

                    Changes in version 1.21

scp 1.21.1

  • Update Chris’ email address.

scp 1.21.0

  • New Bioconductor devel

scPassport

                   Changes in version 0.99.0

New Features

  • Initial Bioconductor submission version.
  • seuratPassport(): interactive Shiny gadget to stamp a Seurat object with a persistent metadata passport stored in @misc$passport.
  • read_passport(): prints the full passport and processing log to console.
  • log_step(): appends a processing step entry to @misc$processing_log.
  • Core passport and log logic implemented in C++ via Rcpp for performance.
  • Lineage tracking: parent/child relationships propagated automatically when parent argument is supplied to seuratPassport().
  • Custom fields: any extra key-value metadata can be added through the Shiny popup and persists inside the .rds file.

scran

                    Changes in version 1.40

  • Bugfix for the AUC calculations in pairwiseWilcox() and scoreMarkers(), to avoid integer overflow with large numbers of ties.

  • Deprecate many historical functions in favor of their replacements in the scrapper package.

scrapper

                    Changes in version 1.6.0

  • Multiple changes to clusterGraph():

    • Updates to use the latest version of the igraph library.

    • method=”leiden” now supports the ER objective function in leiden.objective=.

    • Non-zero status are now directly reported as errors, status is removed from the output.

  • Multiple additions to scoreMarkers():

    • Support use of quantiles to average statistics across blocks, via the new block.average.policy= and block.quantile= arguments.

    • Allow calculation of arbitrary quantiles as a summary statistic for the effect sizes of each group, via the new compute.summary.quantiles= argument.

    • Output now contains the number of rows, row names and group IDs for easier interpretation by downstream functions.

    • Added top.index.only= argument to report only the indices of the top genes when all.pairwise= is an integer.

  • Added arguments to summarizeEffects() to disable calculation of certain summary statistics, e.g., by setting compute.summary.median=FALSE. Also support calculation of arbitrary quantiles as described for scoreMarkers().

  • suggestQcThresholds() functions now return a block.ids field that preserves the type of block=. This enables easier matching in the corresponding filterQcMetrics() function.

  • Multiple changes to modelGeneVariances():

    • Allow the use of quantiles to average statistics across blocks via the new block.average.policy= and block.quantile= arguments.

    • Return a block.ids field that preserves the type of block= for easier matching.

  • Multiple changes to runPca():

    • Added a subset= argument that performs a PCA on a subset of features but still reports the full rotation matrix for all features.

    • Return a block.ids field that preserves the type of block= for easier matching.

  • clusterKmeans() now emits a warning upon convergence failure. This can be disabled by setting warn=FALSE.

  • Simplified the automatic naming performed by combineFactors() when factors is unnamed.

  • Added SummarizedExperiment-compatible wrappers for all functions. These can be identified by their *.se suffix, e.g., aggregateAcrossCells.se(). Some functions execute multiple steps for convenience, e.g., quickRnaQc.se() runs all of the RNA-related QC functions.

  • Added analyze.se() to replace the analyze() function. The former is more convenient it stores most outputs in a SingleCellExperiment and formats the marker tables correctly. The latter is now deprecated.

  • compute*QcMetrics() functions now return a DataFrame for more convenient inspection and manipulation.

  • All functions that previously returned a base data.frame will now return a DataFrame from S4Vectors. This is a little prettier and we already load S4Vectors anyway.

  • Removed checks on num.neighbors= when pre-computed neighbor search results are supplied in runUmap(), buildSnnGraph() and subsampleByNeighbors(). Any differences between num.neighbors= and the number of neighbors in the pre-computed results are now ignored.

  • Implemented the LogNormalizedMatrix class for delayed log-transformation. Modified normalizeCounts() to return instances of this class when log=TRUE and delayed=TRUE. This allows downstream C++ code to use a more efficient normalization wrapper via initializeCpp(). Note that there are some very minor differences in the log-normalized values when computed in R via extract_array() and those in C++ via tatami extraction.

  • Added the countGroupsByBlock() function to count the number of cells within each combination of group and block. This is primarily intended for diagnosing batch effects.

  • Added options to control which statistics are computed in aggregateAcrossCells(). Also added bindings to compute the per-group medians via the compute.median= option.

scRepertoire

                    Changes in version 2.7.3

BUG FIXES

  • Fixed combineBCR() assigning the same group.by value to all cells instead of per-barcode values.
  • Fixed clonalCluster() failing when group.by produces a single group by correcting the condition for adding the group column to the edge list.

  • Fixed test for CTstrict clustering pattern to match the new default chain = “IGH” behavior in combineBCR().

                      Changes in version 2.7.2

NEW FEATURES

  • New clonalBin() function to bin clones by frequency or proportion without requiring a single-cell object. Adds clonalFrequency, clonalProportion, and cloneSize columns to the output of combineTCR(), combineBCR(), or combineExpression(). Supports custom bin thresholds, optional grouping by metadata variable, and chain filtering.
  • New vizCirclize() function for quick chord diagram visualization without manual circlize code. Supports directional arrows, custom colors, and sector annotations.
  • getCirclize() major enhancements:
  • Multi-level hierarchical grouping via group.by accepting a vector of columns
  • New method parameter: “unique”, “abundance”, “jaccard”, “overlap”
  • New symmetric parameter for directional flow analysis
  • New include.metadata parameter returning sector statistics
  • New filtering options: min.shared, top.links, filter.sectors
  • Built-in color palette generation with palette parameter
  • alluvialClones() major enhancements:
  • New top.clones, min.freq, highlight.clones, and highlight.color parameters
  • Visual customization: stratum.width, flow.alpha, show.labels, label.size
  • New order.strata parameter for controlling level ordering within each stratum
  • Enhanced export.table output now includes freq, prop, and rank columns
  • combineBCR() defaults the clustering call to “IGH” instead of “both”

API CHANGES

  • Soft-deprecated camelCase arguments across all exported functions in favor of dot.notation (e.g., cloneCall to clone.call, exportTable to export.table, cloneSize to clone.size, filterNA to filter.na, addLabel to add.label, clonalSplit to clonal.split). All deprecated arguments will continue to work with a deprecation warning until version 3.0.0.

BUG FIXES

  • Fixed combineExpression() failing with “undefined columns selected” when input data already contained clonalFrequency/clonalProportion columns from a prior clonalBin() call.

                      Changes in version 2.6.2

UNDERLYING CHANGES

  • Expanded functionality in combineBCR() and clonalCluster():
  • New metrics beyond normalized Levenshtein edit distances
  • Support for raw and normalized-based calculations
  • Support for distance matrices to allow for alignment
  • Added support for declaring chains = “IGL”, “IGK”, or “Light” to get all light chains in downstream quantification.

BUG FIXES

  • Fixed handling of multiple chains in combineBCR(), specifically in formatting CTstrict.

                      Changes in version 2.6.1

Update to match Bioconductor Release 3.22 on 2025/10/30.

BUG FIXES

  • Fixed order.by issue in positionalProperty().
  • Fixed individual chain call for combineExpression().
  • Fixed issue with removing kmer with “;” in percentKmer().

scRNAseqApp

                   Changes in version 1.11.26

  • Add datasets available date.

                     Changes in version 1.11.25

  • Add search link for species.

                     Changes in version 1.11.24

  • Add ‘download’ button for webstats.

                     Changes in version 1.11.23

  • Add ‘add’ and ‘delete’ method for lasso.

                     Changes in version 1.11.22

  • Add desity plot for sunburst and deconvolution.

                     Changes in version 1.11.21

  • Fix the issue for idconv.

                     Changes in version 1.11.20

  • Add cell deconvolution plot.

                     Changes in version 1.11.19

  • Fix a bug in molecule plot for discrete_scale.

                     Changes in version 1.11.17

  • Using coord_cartesian but not xlim/ylim.

                     Changes in version 1.11.16

  • Add molecule module.

                     Changes in version 1.11.15

  • Fix the bugs in database links.

                     Changes in version 1.11.14

  • Add pan controler and resizable divider.

                     Changes in version 1.11.13

  • fix a bug for double click events in the user mode.

                     Changes in version 1.11.12

  • save cell segmentation for Seurat object.

                     Changes in version 1.11.11

  • add help function addCellBorders, addCellLinks and addBackgroundImage.

                     Changes in version 1.11.10

  • add background plot.

                     Changes in version 1.11.9

  • add cell segmentaion plot.

                     Changes in version 1.11.8

  • remove the force gene symbol table update.

                     Changes in version 1.11.7

  • fix the bug when subset the cells by percentage.

                     Changes in version 1.11.6

  • Add xlim and ylim for cellinfo and gene exprs plot give the possibility of cross dataset comparison.

                     Changes in version 1.11.5

  • replace ‘size’ by ‘linewidth’ for element_line in theme.

                     Changes in version 1.11.4

  • Keep the height controler for interactive plot in explorer.

  • Add perentage filter for cell info plot.

                     Changes in version 1.11.3

  • Add apply lasso selection for explorer.

                     Changes in version 1.11.2

  • Add group B for reduction in explorer.

                     Changes in version 1.11.1

  • Add download function for lasso.

scToppR

                   Changes in version 0.99.5
  • Initial Acceptance to Bioconductor

scTypeEval

            Changes in version 0.99.21 (2024-01-27)

New Features

  • Initial Bioconductor submission with ground-truth-agnostic cell type evaluation framework
  • Support for multiple input formats: Seurat, SingleCellExperiment, and count matrices
  • Multiple dissimilarity methods:
  • Pseudobulk-based distances (Euclidean, Cosine, Pearson)
  • Wasserstein distance on single-cell distributions
  • Reciprocal classification approaches
  • Comprehensive internal validation metrics:
  • Silhouette scores
  • Neighborhood Purity
  • Ward’s clustering consistency
  • Orbital medoid distances
  • Average similarity measures
  • 2-label silhouette analysis
  • Gene selection methods:
  • Highly variable genes (HVG) detection
  • Cell-type-specific marker identification
  • Custom gene list support
  • Dimensional reduction support (PCA, pre-computed embeddings)
  • Cross-sample and cross-study benchmarking capabilities
  • Customizable visualization tools (heatmaps, MDS, PCA plots)
  • Hierarchical clustering analysis

Improvements

  • Comprehensive documentation with vignettes
  • Examples for all 19 exported functions
  • Support for optional dependencies (transformGamPoi, glmGamPoi)
  • Efficient euclidean distance computation with custom C implementation
  • Parallel processing support via BiocParallel

Bug Fixes

  • Proper handling of sparse matrix formats
  • Robust batch effect handling
  • Consistent results across different label granularities

Documentation

  • Main vignette: comprehensive tutorial with real-world examples
  • Quick start guide: minimal workflow for rapid evaluation
  • Full API documentation for all exported functions

scuttle

                    Changes in version 1.22

  • Improved the efficiency of the downsampling algorithm in downsampleMatrix(), which will change the results slightly. In addition, new options are added to control the output type (integer/double) and class (dense matrix or SVT_SparseMatrix).

  • Removed “median” from the default statistics= in summarizeAssayByGroup(). This enables default use of the fast code path for improved performance.

  • Deprecate all functions that have more efficient counterparts in scrapper.

SEMPLR

                   Changes in version 0.99.0

  • Ready for Bioconductor

  • Your bug fixes. See more details at http://bioconductor.org/developers/package-guidelines/#news.

SeqArray

                   Changes in version 1.52.0

NEW FEATURES

  • new ‘header’ in seqGDS2VCF() to specify whether exporting the metadata header to a VCF file or not

  • set ‘nosample=TRUE’ in seqGDS2VCF() to exclude the sample-level data

  • new ‘verbose.progress’ in seqGDS2VCF() to control the progress display

  • seqGet2bGeno() allows a GDS file name in the first argument

  • new ‘parallel’ in seqGet2bGeno() for parallel loading

  • new ‘SeqArray:::process_block_index’ and ‘SeqArray:::process_block_count’ used in children processes when balancing work

  • new ‘ploidy’ in seqVCF2GDS() and seqBCF2GDS()

UTILITIES

  • Reduce memory usage in seqParallel() by avoiding the transfer of unused data during work balancing in parallel

  • minor fix in seqAsVCF() when loading VariantAnnotation

  • fix the package anchors for all Rd \link{}

  • Updated seqSetFilterPos() is significantly faster than the old version

BUG FIXES

  • fix seqApply(..., margin="by.sample") dimension mismatch error when multiallelic variants are present

                     Changes in version 1.50.1

UTILITIES

  • Reduce memory usage in seqMerge() when there are many INFO variables

Seqtometry

  • Initial Acceptance to Bioconductor

sfi

                   Changes in version 0.99.5
  • Initial Acceptance to Bioconductor

SingleCellExperiment

                   Changes in version 1.34.0
  • counts(), logcounts() and other named getters/setters will now raise a warning if i= is specified, rather than silently treating it as the next argument to assay() (usually withDimnames=).

singleCellTK

                   Changes in version 2.21.1
  • Updated depreciated parameters in Seurat function calls

SingleR

                   Changes in version 2.14.0

  • Added hint.sce= to trainSingleR() to nudge users towards setting a more appropriate de.method= for single-cell references. Similarly, suggest the use of aggr.ref=TRUE for large single-cell references.

  • Added a warning when names of results= and trained= are different in combineRecomputedResults().

  • Updated to the latest version of singlepp, which provides direct support for sparse test/reference matrices. This also eliminates the need for BiocNeighbors so all BNPARAM= arguments are now soft-deprecated.

  • Added score.args= to configureMarkerHeatmap() to pass along to scoreMarkers(), mainly for block= and threshold= options.

  • Added center= and average= options to plotMarkerHeatmap(), for centering of genes and averaging of labels, respectively. Also pass along score.args=.

  • Support block= in getClassicMarkers() to define a blocking factor within a single reference matrix. This serves as an alternative to supplying multiple reference matrices.

smartid

                    Changes in version 1.7.3
  • Major memory and performance optimization for cal_score() and top_markers(). On a 20,000 gene x 100,000 cell sparse input peak memory drops from roughly 100 GB to a few GB, and top_markers() with the default gaussian() family runs in seconds instead of hours.
  • Breaking change: cal_score() no longer stores the intermediate tf, idf and iae matrices in metadata() by default. Callers that relied on metadata(se)$tf / $idf / $iae (introduced in v1.1.1) must now pass return.intermediate = TRUE. When the flag is TRUE, the stored idf / iae for labelled methods (prob, rf) are now compact G x K matrices (columns = unique labels); expand with md$idf[, as.character(label)] to recover the legacy per-cell form.
  • Internal refactor: labelled idf_prob, idf_rf, iae_prob and iae_rf helpers now return a compact G x K matrix. cal_score() composes the final score through per-group column-block multiplication, avoiding the materialisation of full G x N intermediates.
  • cal_score() no longer forces dense conversion of dgCMatrix inputs; the score assay stays sparse throughout the pipeline when the input is sparse.
  • tf(), idf_hdb(), iae_hdb() and all IAE helpers now preserve dgCMatrix sparsity by routing column scaling through Matrix::Diagonal and replacing the densifying x[x < 0] <- 0 pattern with pmax0_offset().
  • top_markers_glm() has a vectorised closed-form least-squares fast path for the default gaussian() + identity link; non-gaussian families or rank-deficient designs automatically fall back to the legacy per-gene glm() loop with no behaviour change.
  • top_markers_abs() aggregates directly on the scored matrix via sparseMatrixStats::rowMeans2 / rowMedians / rowMads, removing the intermediate wide data.frame that previously reached tens of GB.
  • scale_mgm() caches per-group column indices and collapses the two-step (expr - mgm) / (sds + 1e-8) into a single broadcast.
  • The multi = TRUE branch of the labelled IDF/IAE helpers switched from an O(G * K^2) apply() to an O(G * K) top-1 + top-2 trick via the new rowwise_notin_max() helper.
  • New inst/bench/benchmark_smartid.R micro-benchmark script; new tests/testthat/test-numerical-equivalence.R pins cal_score() and top_markers() outputs to a frozen pre-refactor snapshot at 1e-10 tolerance.

  • No new dependencies; the refactor relies entirely on Matrix, sparseMatrixStats and base R.

                      Changes in version 1.7.2

  • Fix dplyr defunct.

                      Changes in version 1.7.1
  • Add bioRxiv citation.

smoppix

                    Changes in version 1.2.3

  • Switch to mgcv::scasm for monotonically decreasing p-splines

                      Changes in version 1.2.2

  • Adapt code for negative hypergeometric from the orphaned extraDistr package and take it in-house

                      Changes in version 1.2.1

  • Anticipate coming changes to lme4

SMTrackR

                   Changes in version 0.99.8
  • Initial Acceptance to Bioconductor

SNPRelate

                   Changes in version 1.46.0

UTILITIES

  • fix the package anchors for all Rd \link{}

sosta

                    Changes in version 1.3.4

  • removed non working GitHub actions

                      Changes in version 1.3.3
  • clarified difference between shapeMetric and totalShapeMetrics.

  • updated FOV border characterization in vignette.

                      Changes in version 1.3.2
  • changed minBoundaryDistances to allow for distance to FOV border characterization

  • added “Structure boundary vs FOV boundary” section to vignette.

                      Changes in version 1.3.1
  • added argument to simulate noise in createPointPatternTissue
  • improved intensity value threshold estimation for reconstruction in .intensityThreshold

SpaceTrooper

                    Changes in version 1.1.7

  • fixing author name typo

                      Changes in version 1.1.6

  • adding new vignette about SpaceTrooper utilities

                      Changes in version 1.1.5
  • minor enhancement of cosmx input reading, polygonsCol added
  • minor documentation clarification on QCScore computation

  • cleaned LICENSE stub and creating LICENSE.md file

                      Changes in version 1.1.4
  • updating documentation along multiple functions
  • adding graphical abstract
  • updating README

  • updating Vignettes and providing better data examples

                      Changes in version 1.1.3

  • fixing verbose message in QC functions.

                      Changes in version 1.1.2
  • adding volume instead of area for MERFISH.
  • refactoring log2CountArea to log2DensitySignal
  • added size and alpha arguments to plotCellsFovs

  • added scaleBar argument to plotCellsFovs, plotCentroids, plotPolygons and plotZoomFovsMap

                      Changes in version 1.0.1
  • fixing minor bugs in AspectRatio internal computation for technology missing it.
  • fixing merfish reading where colData where not properly sorted and sync with assay cells.

SpatialArtifacts

                   Changes in version 0.99.10
  • Initial Acceptance to Bioconductor

SpatialDecon

             Changes in version 1.20.1 (2025-12-22)
  • Bug fix in vignette Seurat creation

spatialFDA

                    Changes in version 1.3.3
  • rewrote summary.functionalGam and added a new coef.functionalGam to have no breaking changes in spatialFDA due to changes in refund::pffr naming.

  • this makes spatialFDA again compatible with the OSTA chapter.

                      Changes in version 1.3.2
  • covariance matrices are now corrected for cluster-correlations along the domain $r$ with sandwich-estimators by default - thank you @fabianscheipl for implementing this in refund::pffr
  • models can now also be fit with gamm4

  • Experimental: implemented an AR(1) penalty along the domain $r$ in bam fits. This is to some extent already adressed by the cluster-robust sandwich estimators so might be removed in the future.

                      Changes in version 1.3.1
  • option to square-root transform the weights in the functional Gam
  • changes to cutoff calculations at the saturating end of $G$ functions
  • fix as.formula calls by passing an empty.env call
  • cleaned up spatialInference from exploratory code.

Spectra

                    Changes in version 1.21

Change 1.21.7

  • Add parameter direction to shiftPeaks() allowing to define whether peaks should be shifted left or right (default).

Change 1.21.6

  • Add shiftPeaks() function.
  • Add parameter onlyCore = FALSE to dropNaSpectraVariables().

Change 1.21.5

  • Fix potential issue by introducing concatenation of data.frames with data.table::rbindlist() in version 1.21.3: new function rbindlistWithRownames() added which uses rbindlist() but preserves also the row names of the data.frames.
  • Fix unit tests for joinPeaksGnps() to follow recent updates in MsCoreUtils.

Change 1.21.4

  • Refactor compareSpectra() to support spectra similarity functions returning the similarity score and the number of peak pairs on which the score was calculated. This allows to correctly report the number of peak pairs used by e.g. the modified cosine (GNPS) similarity score. See also issue #350.

Change 1.21.3

  • Use data.table::rbindlist() for merging of MsBackendMemory instances and for backendInitialize() for MsBackendMzR. This adds data.table as a dependency but improves performance for the above mentioned functionality.
  • Fix bug in fragmentGroupIndex() that would return the indices in a wrong order.

Change 1.21.2

  • Replace msdata with MsDataHub package.

Change 1.21.1

  • Fix precursorPurity() for empty spectra.

SpectraQL

                     Changes in version 1.5

Changes in 1.5.1

  • Load test and example files from MsDataHub dropping the dependency from msdata.

SpectriPy

                     Changes in version 1.1

Changes in 1.1.8

  • Implement pyspec_copy_on_replace() to enable copying/cloning the MS data in Python for any data replacement operation performed in R (issue #91).

Changes in 1.1.7

  • Improved $<- operation: only replace the values for the selected spectra variable.
  • Improved peaksData<-, mz<- and intensity<- implementations: only replace the respective data, but not the full spectra data (including metadata).
  • Improved lengths() implementation: retrieves the number of peaks directly in Python.
  • Documentation updates.

Changes in 1.1.6

  • Automatic renaming and remapping of upper case or camelCase spectra variables to snake_case metadata fields in backendInitialize(), spectraData<- and $<-.
  • Full support of the Spectra test suite.
  • Add spectraNames<- method for MsBackendPy and support getting/setting spectrum names. They are stored in a metadata field (spectra variable) spectrum_name.

Changes in 1.1.5

  • Fix $<-, spectraData()<- and related replacement methods for Spectra/MsBackendPy of length 1.

Changes in 1.1.4

  • Implement a setBackend() method for MsBackendPy with a parameter applyProcessing to allow applying the processing queue and storing the modified peaks data to Python.

Changes in 1.1.3

  • Introduce new ModifiedCosineHungarian() and ModifiedCosineGreedy() parameters to match changes in matchms version 0.32.

Changes in 1.1.2

  • Use matchms 0.31.

SpiecEasi

                   Changes in version 1.99.5

BUG FIXES

  • Fixed vignette rebuild error with pulsar >= 0.3.13: resolve the estimation function before passing to pulsar() - this avoids lazy match.fun evaluation that fails on PSOCK cluster workers.

INFRASTRUCTURE

  • Removed obsolete CXX_STD = CXX11 from src/Makevars (R >= 4.6 defaults to C++20)

  • Fixed .Rbuildignore to exclude leftover vignettes/figure directory from knitr

                     Changes in version 1.99.4

BUG FIXES

  • Fixed vignette build failure caused by makeCluster(4, type = “SOCK”) requiring unavailable snow package
  • Replaced broken snow cluster example with reference to batch.pulsar with conffile=’snow’

  • Set batch mode vignette chunks to eval=FALSE to avoid build failures on systems without batchtools infrastructure

                     Changes in version 1.99.3

BUG FIXES

  • Fixed BugReports URL in DESCRIPTION (removed double slash)
  • Replaced sapply with vapply in R/fitdistr.R for improved type stability
  • Fixed incomplete final line in .Rbuildignore file

IMPROVEMENTS

  • Added BiocManager installation instructions to main vignette
  • Added runnable examples to man pages for getOptInd, robustPCA, stars.roc, and triu functions
  • Cleaned up promotional language in NEWS entries
  • Removed unused inst/extdata files to reduce package size

INFRASTRUCTURE

  • Added .registration = TRUE to useDynLib in NAMESPACE
  • Updated package version to 0.99.2 for Bioconductor submission

  • Verified vignette runtime compliance with Bioconductor guidelines

                     Changes in version 1.99.2

NEW FEATURES

  • Added comprehensive Bioconductor package infrastructure
  • Added automated GitHub Actions workflow for Bioconductor continuous integration
  • Added test coverage reporting and automated testing
  • Added Bioconductor-style vignettes and documentation
  • Added biocViews categorization: Software, Microbiome, Metagenomics, GraphAndNetwork, NetworkInference
  • Added comprehensive support documentation and issue templates
  • Implemented proper code of conduct and contribution guidelines

INFRASTRUCTURE IMPROVEMENTS

  • Added Bioconductor-specific GitHub Actions workflow (check-bioc.yml)
  • Implemented automated R CMD check with Bioconductor standards
  • Added BiocCheck integration for package validation
  • Enhanced test coverage with automated reporting
  • Added lifecycle badge indicating stable package status

BUG FIXES

  • Resolved compliance issues identified during BiocCheck
  • Enhanced error handling and package robustness

splatter

             Changes in version 1.36.0 (2026-04-29)

  • Replace deprecated scuttle functions with scrapper

  • Deprecate mfa simulation functions as the mfa package is deprecated

  • Adjust help messages in warnings

  • Adjust failing lun2Estimate tests

SpliceImpactR

                   Changes in version 0.99.4
  • Initial Acceptance to Bioconductor

splicelogic

                   Changes in version 0.99.0

Submit to Bioconductor 3.23

SpNeigh

                   Changes in version 0.99.0

Initial Bioconductor submission

New Features

  • Introduced the RunSpatialDE() function for spatial differential expression using spatial weights.
  • Added ComputeSpatialEnrichmentIndex() for enrichment quantification.
  • Implemented GetBoundary(), GetRingRegion(), and RemoveOutliers() for spatial region detection.
  • Added PlotSpatialExpression() and other visualization tools.

StatescopeR

                  Changes in version 26-7-2025
  • Initial Acceptance to Bioconductor

statTarget

                     Changes in version 2.0

NEW FEATURES

  • New GUI o Mouse Hover for help information o .log file

  • New Signal correction o Combat for QC-free Signal correction o QC-RFSC methods for metabolomics and proteomics data

  • New feature slection o Random Forest and the Permutation based variable importance measures o new MDSplot for Random Forest o P-value based importance plot

  • New data preprocessing o PQN/SUM/none normalization o center/none Scaling method

struct

                   Changes in version 1.23.2

  • remove stato classes; these were deprecated since 1.5.2 and are no longer used.

  • ontology is still available via ontology slots.

  • rols package is deprecated; using internal functions instead.

  • replaced ontology cache with online/offline mode

  • added ontology output for model sequences

structToolbox

                   Changes in version 1.23.2

  • remove deprecated stato classes; use ontology slots instead

                     Changes in version 1.23.1

  • general maintenance

  • fix PLSDA probability calculation

SVP

                    Changes in version 1.3.1
  • Bioconductor 3.22 release, and Bioconductor 3.23 (devel) bump. (2025-10-31, Fri)

TargetSearch

                   Changes in version 2.14.0

DOCUMENTATION

  • Fix typo in ri_plot_peak man page.

TaxSEA

                    Changes in version 1.3.3

  • Add ssTaxSEA() function for single sample enrichment testing and documentation

                      Changes in version 1.3.2
  • Add taxon_rank_sets() helper with documentation and tests
  • Add functionality to interact with tse objects

tidyexposomics

                   Changes in version 0.99.16

Initial Bioconductor submission.

  • Implements a full exposome-omics pipeline including:
  • Quality control
  • Association analysis
  • Differential abundance analysis
  • Multi-omics integration analysis
  • Functional enrichment analysis
  • Vizualization

TileDBArray

                   Changes in version 1.22.0
  • Workaround for TileDBRealizationSink to properly write higher-dimensional dense arrays.

topdownr

                    Changes in version 1.33

Changes in version 1.33.1

  • Adapt to changes in ggplot2.
  • Adapt .calculateFragments to changes in PSMatch::calculateFragments introduced in PSMatch:PR41.

toppgene

             Changes in version 0.99.2 (2026-02-16)
  • Initial Acceptance to Bioconductor

TPP

                   Changes in version 3.39.1

  • Avoid deprecated dplyr::tbl_df() calls in biobroom::tidy.ExpressionSet() by changing output to data.frame for compatibility with dplyr ≥ 1.0.0.

  • Deprecated parallelization and nCores parameter in fitting and plotting functions to improve maintainability and robustness to dependency changes.

  • Fixed ggplot2 deprecation warning to maintain compatibility with recent ggplot2 versions

trackViewer

                   Changes in version 1.47.1
  • Fix the mis-match y-axis for dandelion.plot when max score is smaller than 1.

transcriptR

                   Changes in version 1.39.4

  • Fixed a failing unit test caused by an update to the TxDb.Hsapiens.UCSC.hg19.knownGene library. Replaced the external dependency with the internal annot dataset to ensure stability.

  • Moved e1071 from Imports to Suggests

  • Updated the roxygen2 version and rebuilt all manual pages.

  • Fixed incorrect roxygen documentation for internal datasets.

TSAR

                    Changes in version 1.9.3
  • Introduction of cubic spline with beta-knots for smoother curve fitting, completed on December, 2025.

tximeta

                   Changes in version 1.30.0
  • Updates to vignette to mention edgeR’s new function DGEListFromTximeta.

  • Fix the ‘call dbDisconnect() when finished’ message by explicitly doing it on exit. Thanks to Gordon Smyth for noting this.

                     Changes in version 1.29.5

  • Working on updateMetadata, gene_id had issues as CharacterList type. Now downgrading to character.

                     Changes in version 1.29.4

  • Fixing sapply bug in inspectDigests and updateMetadata.

                     Changes in version 1.29.3
  • Fixing github actions workflow re quarto issue.

tximport

                   Changes in version 1.40.0
  • Updates from Gordon Smyth and Pedro Baldoni to the vignette using new functions in edgeR.

UPDhmm

                    Changes in version 1.7.1

NEW FEATURES

  • Added a long-read processing example in a new vignette.

IMPROVEMENTS

  • Refined recurrent annotation in markRecurrentRegions(). Recurrent status is now determined using a minimum overlap fraction between events and recurrent regions, preventing marginal overlaps from being annotated as recurrent.

  • More precise recurrent region definition in identifyRecurrentRegions(). Replaced direct interval merging with an overlap-aware, chromosome-wise agglomerative hierarchical clustering approach. Recurrent regions are now defined based on overlap similarity between events, with configurable clustering stringency.

BUG FIXES

  • Corrected collapsed event size calculation in collapseEvents(). The total size of collapsed events is now computed as the true genomic span of the region rather than the sum of individual event sizes.

velociraptor

                   Changes in version 1.21.3

  • Update dependencies for MacOSXArm (again).

                     Changes in version 1.21.2

  • Update dependencies for MacOSXArm.

                     Changes in version 1.21.1

  • Pin version of all dependencies.

VisiumIO

                    Changes in version 1.8.0

Bug fixes and minor improvements

  • Fixed issue when using sample_id parameter in TENxVisiumHD (@michaelplynch, #17)
  • Allow spacerangerOut inputs in TENxVisium to have an outs folder and optionally check for the spatial subfolder within it (@estellad, #18).

VISTA

  • Initial Acceptance to Bioconductor

vsn

                   Changes in version 3.79.1

  • The deprecated ggplot2::aes_string() used in meanSdPlot() has been replaced with ggplot2::aes().

  • The error message when reference@mu doesn’t have the expected length in vsnMatrix() no longer says “too few arguments” and now reports the actual and expected lengths.

wavClusteR

                   Changes in version 2.45.1
  • Fixed imports following migration of supportedUCSCtables() and makeTxDbFromUCSC() to {txdbmaker}

wavFeatExt

                   Changes in version 0.99.14
  • Initial Acceptance to Bioconductor

XAItest

                    Changes in version 1.3.1
  • Add package citation metadata for the Bioconductor landing page.
  • Document exported helper functions and sync the XAI.test() manual.

  • Import stats::runif in genScenario() to address package check notes.

  • Remove obsolete vignette; bump to 1.1.1

xcms

                     Changes in version 4.9

Changes in version 4.9.4

  • Improve performance for some functions by using Spectra::rbindlistWithRownames() to merge data.frames.
  • Replace the msdata package for test data files with MsDatahub.

Changes in version 4.9.3

  • Fix title of plotPrecursorIons() plot.
  • Add parameter rtCenterFun to PeakDensityParam() to support specifying the function to calculate the reported retention time of a feature (“rtmed”).

Changes in version 4.9.2

  • Fix issue with refineChromPeaks() and MergeNeighboringPeaksParam where in certain cases completely overlapping peaks were not merged (issue #825).

Changes in version 4.9.1

  • Add the citation and reference for the new 2025 xcms paper

zellkonverter

                   Changes in version 1.22.0

Minor changes

  • Minor fixes to tests and documentation

NEWS from existing Data Experiment Packages

curatedCRCData

                   Changes in version 2.43.1

  • Updated package maintainer to Levi Waldron (lwaldron.research@gmail.com).

  • Refactored DESCRIPTION to use standard Authors@R fields, including maintainer ORCID and funding info (NCI 5U24CA180996).

  • Fixed invalid biocViews categories to strictly use acceptable ExperimentData terms.

  • Replaced the unnecessary affy dependency with Biobase in the package Suggests and the vignette.

  • Added a new CITATION file pointing to the 2018 Genome Biology meta-analysis paper (PMID: 30253799).

  • Initialized Git LFS to properly track .rda and .RData files.

  • Removed deprecated zzz.R warning.

  • Converted the vignette to RMarkdown (.Rmd).

dominatRData

                   Changes in version 0.99.1

  • Modification of the Description

  • Modification of the vignettes!

                     Changes in version 0.99.0

  • Initial Bioconductor submission.

DoReMiTra

                    Changes in version 1.2.0

  • adding a new function to list metadata values

  • filtering by author name

  • adding Tissue field in the metadata

EMTscoreData

                   Changes in version 0.99.0
  • submitted to bioconductor

gDRtestData

          Changes in version 22023-05-15 (2023-05-15)

  • fix related with data.table

             Changes in version 2026-04-13 (2026-04-13)

  • migrate test data files from .qs to .qs2 format

             Changes in version 2025-10-30 (2025-10-30)

  • synchronize Bioconductor and GitHub versioning

             Changes in version 2025-08-12 (2025-08-12)

  • fix usage of ifelse

             Changes in version 2025-07-29 (2025-07-29)

  • update test data

             Changes in version 2025-04-16 (2025-04-16)

MetaScope

                    Changes in version 3.23

Bug fixes

  • fixed the metascope_id() function to export the location of the id file

  • Made significant improvements in memory usage in Metascope_id

                      Changes in version 3.22

Bug Fixes

  • Fixed filter compression to take a pre-formatted character string in csv format

  • Fixed minor issues in convert_animalcules() when non-linked taxonomy IDs are present

  • Updated convert_animalcules to correct a bug in the final consolidation of reads, where more read counts were being added than in the original sample

msdata

                   Changes in version 0.51.2

  • remove TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz, available in MsDataHub.

  • remove TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01.mzML.gz.

  • remove PestMix1_DDA.mzML, available in MsDataHub.

  • remove PestMix1_SWATH.mzML, available in MsDataHub.

                     Changes in version 0.51.1

  • Add deprecation startup message

spatialLIBD

                   Changes in version 1.23.2

NEW FEATURES

  • gene_set_enrichment() now returns a $GeneList as implemented by @lahuuki. See details at https://github.com/LieberInstitute/spatialLIBD/pull/119.

                     Changes in version 1.23.1

NEW FEATURES

  • fetch_data() now provides access to all LFF_spatial_ERC project files associated with the preprint at https://doi.org/10.1101/2025.11.20.689483. @lahuuki added this information as part of https://github.com/LieberInstitute/spatialLIBD/pull/118.

Deprecated and Defunct Packages

SOFTWARE:

Thirty seven software packages were removed from this release (after being deprecated in Bioc 3.22):

  • bgx, BiGGR, biodbHmdb, biodbNcbi, biodbNci, biodbUniprot, ccmap, CellScore, CINdex, cisPath, DEP, gpuMagic, Harshlight, hiAnnotator, hiReadsProcessor, interactiveDisplay, interactiveDisplayBase, lapmix, LinTInd, lute, MADSEQ, oppti, PhenStat, qckitfastq, ReactomeGraph4R, Repitools, rGADEM, rRDP, SARC, seqArchR, seqArchRplus, seqTools, Streamer, TitanCNA, TransView, traviz, XNAString

Previously announced deprecated packages were fixed and restored to Bioconductor 3.23:

  • hypeR, netZooR, Rfastp

Fifty two software packages are deprecated in this release and will be removed in Bioc 3.24:

  • APAlyzer, ballgown, bamsignals, barcodetrackR, basecallQC, biobroom, biodbChebi, BiRewire, BPRMeth, BubbleTree, ccrepe, CelliD, ChIPQC, cummeRbund, CuratedAtlasQueryR, debCAM, DeconRNASeq, geneXtendeR, GEOexplorer, GNET2, granulator, hca, hmdbQuery, IMAS, IONiseR, Melissa, MetaNeighbor, MethReg, mfa, microSTASIS, MineICA, motifcounter, MSPrep, nearBynding, netprioR, normr, Organism.dplyr, partCNV, RcisTarget, receptLoss, RgnTX, RiboProfiling, rols, RTCGA, scviR, SGCP, SigFuge, soGGi, spatzie, SQLDataFrame, supersigs, tLOH

EXPERIMENT DATA:

Four experimental data packages were removed from this release (after being deprecated in BioC 3.22):

  • AneuFinderData, chromstaRData, curatedCRCData, RGMQLlib, rRDPData

Previously announced deprecated package was fixed and restored to Bioconductor 3.23:

  • curatedCRCData

Two experimental data packages are deprecated in this release and will be removed in Bioc 3.24:

  • curatedBreastData, Fletcher2013b

ANNOTATION DATA:

No annotation annotation packages were removed from this release (after being deprecated in Bioc 3.22).

Four annotation packages are deprecated in this release and will be removed in Bioc 3.24:

  • hpAnnot, humanCHRLOC, mouseCHRLOC, ratCHRLOC

We will also be removing seven out-dated TxDb packages from Bioc 3.24:

  • TxDb.Mmusculus.UCSC.mm10.ensGene, TxDb.Athaliana.BioMart.plantsmart22, TxDb.Athaliana.BioMart.plantsmart25, TxDb.Cfamiliaris.UCSC.canFam3.refGene, TxDb.Rnorvegicus.UCSC.rn4.ensGene, TxDb.Hsapiens.BioMart.igis, TxDb.Rnorvegicus.BioMart.igis

WORKFLOWS:

One workflow package was removed from this release (after being deprecated in Bioc 3.22).

  • spicyWorkflow

No workflow packages have been deprecated in this release.

BOOKS:

No books were removed from this release.

No books were deprecated in this release.