Registration Open for Bioc2024 July 24-26

October 30, 2019


We are pleased to announce Bioconductor 3.10, consisting of 1823 software packages, 384 experiment data packages, 953 annotation packages, and 27 workflows.

There are 94 new software packages, 15 new data experiment packages, 3 new annotation packages, and many updates and improvements to existing packages; Bioconductor 3.10 is compatible with R 3.6.1, and is supported on Linux, 32- and 64-bit Windows, and Mac OS X. This release will include an updated Bioconductor Amazon Machine Image and Docker containers.

Thank you to everyone for your contribution to Bioconductor

Visit Bioconductor BiocViews for details and downloads.


Getting Started with Bioconductor 3.10

To update to or install Bioconductor 3.10:

  1. Install R >=3.6.1. Bioconductor 3.10 has been designed expressly for this version of R.

  2. Follow the instructions at Installing Bioconductor.

New Software Packages

There are 93 new software packages in this release of Bioconductor.

  • AlphaBeta AlphaBeta is a computational method for estimating epimutation rates and spectra from high-throughput DNA methylation data in plants. The method has been specifically designed to: 1. analyze ‘germline’ epimutations in the context of multi-generational mutation accumulation lines (MA-lines). 2. analyze ‘somatic’ epimutations in the context of plant development and aging.

  • ALPS The package provides analysis and publication quality visualization routines for genome-wide epigenomics data such as histone modification or transcription factor ChIP-seq, ATAC-seq, DNase-seq etc. The functions in the package can be used with any type of data that can be represented with bigwig files at any resolution. The goal of the ALPS is to provide analysis tools for most downstream analysis without leaving the R environment and most tools in the package require a minimal input that can be prepared with basic R, unix or excel skills.

  • APAlyzer Perform 3’UTR APA, Intronic APA and gene expression analysis using RNA-seq data.

  • ASpediaFI This package provides functionalities for a systematic and integrative analysis of alternative splicing events and their functional interactions.

  • Autotuner This package is designed to help faciliate data processing in untargeted metabolomics. To do this, the algorithm contained within the package performs statistical inference on raw data to come up with the best set of parameters to process the raw data.

  • AWFisher Implementation of the adaptively weighted fisher’s method, including fast p-value computing, variability index, and meta-pattern.

  • BiocSet BiocSet displays different biological sets in a triple tibble format. These three tibbles are element, set, and elementset. The user has the abilty to activate one of these three tibbles to perform common functions from the dplyr package. Mapping functionality and accessing web references for elements/sets are also available in BiocSet.

  • BioTIP Adopting tipping-point theory to transcriptome profiles to unravel disease regulatory trajectory.

  • biscuiteer A test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.

  • blacksheepr Blacksheep is a tool designed for outlier analysis in the context of pairwise comparisons in an effort to find distinguishing characteristics from two groups. This tool was designed to be applied for biological applications such as phosphoproteomics or transcriptomics, but it can be used for any data that can be represented by a 2D table, and has two sub populations within the table to compare.

  • brainflowprobes Use these functions to characterize genomic regions for BrainFlow target probe design.

  • brendaDb R interface for importing and analyzing enzyme information from the BRENDA database.

  • BUSpaRse The kallisto | bustools pipeline is a fast and modular set of tools to convert single cell RNA-seq reads in fastq files into gene count or transcript compatibility counts (TCC) matrices for downstream analysis. Central to this pipeline is the barcode, UMI, and set (BUS) file format. This package serves the following purposes: First, this package allows users to manipulate BUS format files as data frames in R and then convert them into gene count or TCC matrices. Furthermore, since R and Rcpp code is easier to handle than pure C++ code, users are encouraged to tweak the source code of this package to experiment with new uses of BUS format and different ways to convert the BUS file into gene count matrix. Second, this package can conveniently generate files required to generate gene count matrices for spliced and unspliced transcripts for RNA velocity. Third, this package implements utility functions to get transcripts and associated genes required to convert BUS files to gene count matrices, to write the transcript to gene information in the format required by bustools, and to read output of bustools into R as sparses matrices.

  • calm Statistical methods for multiple testing with covariate information. Traditional multiple testing methods only consider a list of test statistics, such as p-values. Our methods incorporate the auxiliary information, such as the lengths of gene coding regions or the minor allele frequencies of SNPs, to improve power.

  • circRNAprofiler R-based computational framework for a comprehensive in silico analysis of circRNAs. This computational framework allows to combine and analyze circRNAs previously detected by multiple publicly available annotation-based circRNA detection tools. It covers different aspects of circRNAs analysis from differential expression analysis, evolutionary conservation, biogenesis to functional analysis.

  • cliqueMS Annotates data from liquid chromatography coupled to mass spectrometry (LC/MS) metabolomics experiments. Based on a network algorithm (O.Senan, A. Aguilar- Mogas, M. Navarro, O. Yanes, R.Guimerà and M. Sales-Pardo, Metabolomics Conference (2016), Dublin), ‘CliqueMS’ builds a weighted similarity network where nodes are features and edges are weighted according to the similarity of this features. Then it searches for the most plausible division of the similarity network into cliques (fully connected components). Finally it annotates metabolites within each clique, obtaining for each annotated metabolite the neutral mass and their features, corresponding to isotopes, ionization adducts and fragmentation adducts of that metabolite.

  • CNVfilteR CNVfilteR identifies those CNVs that can be discarded by using the single nucleotide variant (SNV) calls that are usually obtained in common NGS pipelines.

  • CrossICC CrossICC utilizes an iterative strategy to derive the optimal gene set and cluster number from consensus similarity matrix generated by consensus clustering and it is able to deal with multiple cross platform datasets so that requires no between-dataset normalizations. This package also provides abundant functions for visualization and identifying subtypes of cancer. Specially, many cancer-related analysis methods are embedded to facilitate the clinical translation of the identified cancer subtypes.

  • debCAM An R package for fully unsupervised deconvolution of complex tissues. It provides basic functions to perform unsupervised deconvolution on mixture expression profiles by Convex Analysis of Mixtures (CAM) and some auxiliary functions to help understand the subpopulation-specific results. It also implements functions to perform supervised deconvolution based on prior knowledge of molecular markers, S matrix or A matrix. Combining molecular markers from CAM and from prior knowledge can achieve semi-supervised deconvolution of mixtures.

  • deltaCaptureC This package discovers meso-scale chromatin remodelling from 3C data. 3C data is local in nature. It givens interaction counts between restriction enzyme digestion fragments and a preferred ‘viewpoint’ region. By binning this data and using permutation testing, this package can test whether there are statistically significant changes in the interaction counts between the data from two cell types or two treatments.

  • DEWSeq Differential expression analysis of windows for next-generation sequencing data like eCLIP or iCLIP data.

  • DMCFB DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.

  • fcoex The fcoex package implements an easy-to use interface to co-expression analysisbased on the FCBF (Fast Correlation-Based Filter) algorithm. it was implemented especifically to deal with single-cell data. The modules found can be used to redefine cell populations, unrevel novel gene associations and predict gene function by guilt-by-association. The package structure is based on the CEMiTool package.

  • fcScan This package is used to detect combination of genomic coordinates falling within a user defined window size along with user defined overlap between identified neighboring clusters. It can be used for genomic data where the clusters are built on a specific chromosome or specific strand. Clustering can be performed with a “greedy” option allowing thus the presence of additional sites within the allowed window size.

  • flowSpecs This package is intended to fill the role of conventional cytometry pre-processing software, for spectral decomposition, transformation, visualization and cleanup, and to aid further downstream analyses, such as with DepecheR, by enabling transformation of flowFrames and flowSets to dataframes. Functions for flowCore-compliant automatic 1D-gating/filtering are in the pipe line. The package name has been chosen both as it will deal with spectral cytometry and as it will hopefully give the user a nice pair of spectacles through which to view their data.

  • flowSpy A trajectory inference and visualization toolkit for flow and mass cytometry data. flowSpy offers complete analyzing workflow for flow and mass cytometry data. flowSpy can be a valuable tool for application ranging from clustering and dimensionality reduction to trajectory reconstruction and pseudotime estimation for flow and mass cytometry data.

  • GCSscore For differential expression analysis of 3’IVT and WT-style microarrays from Affymetrix/Thermo-Fisher. Based on S-score algorithm originally described by Zhang et al 2002.

  • gemini GEMINI uses log-fold changes to model sample-dependent and independent effects, and uses a variational Bayes approach to infer these effects. The inferred effects are used to score and identify genetic interactions, such as lethality and recovery. More details can be found in Zamanighomi et al. 2019 (in press).

  • GenomicOZone The package clusters gene activity along chromosome into zones, detects differential zones as outstanding, and visualizes maps of outstanding zones across the genome. The method guarantees cluster optimality, linear runtime to sample size, and reproducibility. It enables new characterization of effects due to genome reorganization, structural variation, and epigenome alteration.

  • GmicR This package uses bayesian network learning to detect relationships between Gene Modules detected by WGCNA and immune cell signatures defined by xCell. It is a hypothesis generating tool.

  • gramm4R Generalized Correlation Analysis for Metabolome and Microbiome (GRaMM), for inter-correlation pairs discovery among metabolome and microbiome.

  • gscreend Package for the analysis of pooled genetic screens (e.g. CRISPR-KO). The analysis of such screens is based on the comparison of gRNA abundances before and after a cell proliferation phase. The gscreend packages takes gRNA counts as input and allows detection of genes whose knockout decreases or increases cell proliferation.

  • HCAExplorer Search, browse, reference, and download resources from the Human Cell Atlas data portal. Development of this package is supported through funds from the Chan / Zuckerberg initiative.

  • HiLDA A package built under the Bayesian framework of applying hierarchical latent Dirichlet allocation to statistically test whether the mutational exposures of mutational signatures (Shiraishi-model signatures) are different between two groups.

  • idr2d A tool to measure reproducibility between genomic experiments that produce two-dimensional peaks (interactions between peaks), such as ChIA-PET, HiChIP, and HiC. idr2d is an extension of the original idr package, which is intended for (one-dimensional) ChIP-seq peaks.

  • IgGeneUsage Decoding the properties of immune repertoires is key in understanding the response of adaptive immunity to challenges such as viral infection. One important task in immune repertoire profiling is the detection of biases in Ig gene usage between biological conditions. IgGeneUsage is a computational tool for the analysis of differential gene usage in immune repertoires. It employs Bayesian hierarchical models to fit complex gene usage data from immune repertoire sequencing experiments and quantifies Ig gene usage biases as probabilities.

  • KnowSeq KnowSeq proposes a whole pipeline that comprises the most relevant steps in the RNA-seq gene expression analysis, with the main goal of extracting biological knowledge from raw data (Differential Expressed Genes, Gene Ontology enrichment, pathway visualization and related diseases). In this sense, KnowSeq allows aligning raw data from the original fastq or sra files, by using the most renowned aligners such as tophat2, hisat2, salmon and kallisto. Nowadays, there is no package that only from the information of the samples to align -included in a text file-, automatically performs the download and alignment of all of the samples. Furthermore, the package includes functions to: calculate the gene expression values; remove batch effect; calculate the Differentially Expressed Genes (DEGs); plot different graphs; and perform the DEGs enrichment with the GO information, pathways visualization and related diseases information retrieval. Moreover, KnowSeq is the only package that allows applying both a machine learning and DEGs enrichment processes just after the DEGs extraction. This idea emerged with the aim of proposing a complete tool to the research community containing all the necessary steps to carry out complete studies in a simple and fast way.

  • LinkHD Here we present Link-HD, an approach to integrate heterogeneous datasets, as a generalization of STATIS-ACT (“Structuration des Tableaux A Trois Indices de la Statistique–Analyse Conjointe de Tableaux”), a family of methods to join and compare information from multiple subspaces. However, STATIS-ACT has some drawbacks since it only allows continuous data and it is unable to establish relationships between samples and features. In order to tackle these constraints, we incorporate multiple distance options and a linear regression based Biplot model in order to stablish relationships between observations and variable and perform variable selection.

  • lionessR LIONESS, or Linear Interpolation to Obtain Network Estimates for Single Samples, can be used to reconstruct single-sample networks ( This code implements the LIONESS equation in the lioness function in R to reconstruct single-sample networks. The default network reconstruction method we use is based on Pearson correlation. However, lionessR can run on any network reconstruction algorithms that returns a complete, weighted adjacency matrix. lionessR works for both unipartite and bipartite networks.

  • Maaslin2 MaAsLin2 is comprehensive R package for efficiently determining multivariable association between clinical metadata and microbial meta’omic features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods. MaAsLin2 is the next generation of MaAsLin.

  • MACSQuantifyR Automatically process the metadata of MACSQuantify FACS sorter. It runs multiple modules: i) imports of raw file and graphical selection of duplicates in well plate, ii) computates statistics on data and iii) can compute combination index.

  • MBQN Modified quantile normalization for omics or other matrix-like data distorted in location and scale.

  • MEB Identifying differential expression genes between the same or different species is an urgent demand for biological research. In most of cases, normalization is the first step to solve this problem, then by employing the hypothesis testing, we could detect statistically significant genes. With the development of machine learning, it gives us a new perspective on discrimination between differential expression (DE) and non-differential expression (non-DE) genes. Provided a set of training data, the procedure of distinguishing genes could be simplified as a classification problem. However, in reality, it is hard for us to get the information from both DE and non-DE genes. To solve this problem, we try to identify differential cases only in the domain of non-DE genes, and transform the problem to an outlier detection in machine learning. Given that non-DE genes have some similarities in features, we build a Minimum Enclosing Ball (MEB) to cover those non-DE genes in feature space, then those DE genes, which are enormously different from non-DE genes, being regarded as outliers and rejected outside the ball. Compared with existing methods, it is no need for the MEB method to normalize data in advance. Besides, the MEB method could be easily applied to the same or different species data and without changing too much.

  • MetaVolcanoR This package combines differential gene expression results. It implements three strategies to summarize differential gene expression from different studies. i) Random Effects Model (REM) approach, ii) a p-value combining-approach, and iii) a naive vote-counting approach. In all cases, MetaVolcano exploits the Volcano plot reasoning to visualize the gene expression meta-analysis results.

  • MethCP MethCP is a differentially methylated region (DMR) detecting method for whole-genome bisulfite sequencing (WGBS) data, which is applicable for a wide range of experimental designs beyond the two-group comparisons, such as time-course data. MethCP identifies DMRs based on change point detection, which naturally segments the genome and provides region-level differential analysis.

  • methrix Bedgraph files generated by Bisulfite pipelines often come in various flavors. Critical downstream step requires summarization of these files into methylation/coverage matrices. This step of data aggregation is done by Methrix, including many other useful downstream functions.

  • methylCC A tool to estimate the cell composition of DNA methylation whole blood sample measured on any platform technology (microarray and sequencing).

  • microbiomeDASim A toolkit for simulating differential microbiome data designed for longitudinal analyses. Several functional forms may be specified for the mean trend. Observations are drawn from a multivariate normal model. The objective of this package is to be able to simulate data in order to accurately compare different longitudinal methods for differential abundance.

  • MMAPPR2 MMAPPR2 maps mutations resulting from pooled RNA-seq data from the F2 cross of forward genetic screens. Its predecessor is described in a paper published in Genome Research (Hill et al. 2013). MMAPPR2 accepts aligned BAM files as well as a reference genome as input, identifies loci of high sequence disparity between the control and mutant RNA sequences, predicts variant effects using Ensembl’s Variant Effect Predictor, and outputs a ranked list of candidate mutations.

  • MMUPHin MMUPHin is an R package for meta-analysis tasks of microbiome cohorts. It has function interfaces for: a) covariate-controlled batch- and cohort effect adjustment, b) meta-analysis differential abundance testing, c) meta-analysis unsupervised discrete structure (clustering) discovery, and d) meta-analysis unsupervised continuous structure discovery.

  • MOSim MOSim package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.

  • MSstatsSampleSize The packages estimates the variance in the input protein abundance data and simulates data with predefined number of biological replicates based on the variance estimation. It reports the mean predictive accuracy of the classifier and mean protein importance over multiple iterations of the simulation.

  • muscat muscat provides various methods and visualization tools for DS analysis in multi-sample, multi-group, multi-(cell-)subpopulation scRNA-seq data, including cell-level mixed models and methods based on aggregated “pseudobulk” data, as well as a flexible simulation platform that mimics both single and multi-sample scRNA-seq data.

  • ncGTW The purpose of ncGTW is to help XCMS for LC-MS data alignment. Currently, ncGTW can detect the misaligned feature groups by XCMS, and the user can choose to realign these feature groups by ncGTW or not.

  • OmnipathR Import data from webservice. It also includes functions to transform and print this data.

  • oppti The aim of oppti is to analyze protein (and phosphosite) expressions to find outlying markers for each sample in the given cohort(s) for the discovery of personalized actionable targets.

  • peakPantheR An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files.

  • PERFect PERFect is a novel permutation filtering approach designed to address two unsolved problems in microbiome data processing: (i) define and quantify loss due to filtering by implementing thresholds, and (ii) introduce and evaluate a permutation test for filtering loss to provide a measure of excessive filtering.

  • PhyloProfile PhyloProfile is a tool for exploring complex phylogenetic profiles. Phylogenetic profiles, presence/absence patterns of genes over a set of species, are commonly used to trace the functional and evolutionary history of genes across species and time. With PhyloProfile we can enrich regular phylogenetic profiles with further data like sequence/structure similarity, to make phylogenetic profiling more meaningful. Besides the interactive visualisation powered by R-Shiny, the package offers a set of further analysis features to gain insights like the gene age estimation or core gene identification.

  • proDA Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.

  • pulsedSilac This package provides several tools for pulsed-SILAC data analysis. Functions are provided to organize the data, calculate isotope ratios, isotope fractions, model protein turnover, compare turnover models, estimate cell growth and estimate isotope recycling. Several visualization tools are also included to do basic data exploration, quality control, condition comparison, individual model inspection and model comparison.

  • pwrEWAS pwrEWAS is a user-friendly tool to assists researchers in the design and planning of EWAS to help circumvent under- and overpowered studies.

  • Qtlizer This R package provides access to the Qtlizer web server. Qtlizer annotates lists of common small variants (mainly SNPs) and genes in humans with associated changes in gene expression using the most comprehensive database of published quantitative trait loci (QTLs).

  • ReactomeGSA The ReactomeGSA packages uses Reactome’s online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME’s powerful webapplication. Since Reactome’s analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.

  • RNAmodR RNAmodR provides classes and workflows for loading/aggregation data from high througput sequencing aimed at detecting post-transcriptional modifications through analysis of specific patterns. In addition, utilities are provided to validate and visualize the results. The RNAmodR package provides a core functionality from which specific analysis strategies can be easily implemented as a seperate package.

  • RNAmodR.AlkAnilineSeq RNAmodR.AlkAnilineSeq implements the detection of m7G, m3C and D modifications on RNA from experimental data generated with the AlkAnilineSeq protocol. The package builds on the core functionality of the RNAmodR package to detect specific patterns of the modifications in high throughput sequencing data.

  • RNAmodR.ML RNAmodR.ML extend the functionality of the RNAmodR package and classical detection strategies towards detection through machine learning models. RNAmodR.ML provides classes, functions and an example workflow to establish a detection stratedy, which can be packaged.

  • RNAmodR.RiboMethSeq RNAmodR.RiboMethSeq implements the detection of 2’-O methylations on RNA from experimental data generated with the RiboMethSeq protocol. The package builds on the core functionality of the RNAmodR package to detect specific patterns of the modifications in high throughput sequencing data.

  • RNAsense RNA-sense tool compares RNA-seq time curves in two experimental conditions, i.e. wild-type and mutant, and works in three steps. At Step 1, it builds expression profile for each transcript in one condition (i.e. wild-type) and tests if the transcript abundance grows or decays significantly. Dynamic transcripts are then sorted to non-overlapping groups (time profiles) by the time point of switch up or down. At Step 2, RNA-sense outputs the groups of differentially expressed transcripts, which are up- or downregulated in the mutant compared to the wild-type at each time point. At Step 3, Correlations (Fisher’s exact test) between the outputs of Step 1 (switch up- and switch down- time profile groups) and the outputs of Step2 (differentially expressed transcript groups) are calculated. The results of the correlation analysis are printed as two-dimensional color plot, with time profiles and differential expression groups at y- and x-axis, respectively, and facilitates the biological interpretation of the data.

  • SAIGEgds Scalable implementation of generalized mixed models with highly optimized C++ implementation and integration with Genomic Data Structure (GDS) files. It is designed for single variant tests in large-scale phenome-wide association studies (PheWAS) with millions of variants and samples, controlling for sample structure and case-control imbalance. The implementation is based on the original SAIGE R package (v0.29.4.4). SAIGEgds also implements some of the SPAtest functions in C to speed up the calculation of Saddlepoint approximation. Benchmarks show that SAIGEgds is 5 to 6 times faster than the original SAIGE R package.

  • SBGNview SBGNview is an R package for visualizing omics data on SBGN pathway maps. Given omics data and a SBGN-ML file with layout information, SBGNview can display omics data as colors on glyphs and output image files. SBGNview provides extensive options to control glyph and edge features (e.g. color, line width etc.). To facilitate pathway based analysis, SBGNview also provides functions to extract molecule sets from SBGN-ML files. SBGNview can map a large collection of gene, protein and compound ID typs to glyphs.

  • SCANVIS SCANVIS is a set of annotation-dependent tools for analyzing splice junctions and their read support as predetermined by an alignment tool of choice (for example, STAR aligner). SCANVIS assesses each junction’s relative read support (RRS) by relating to the context of local split reads aligning to annotated transcripts. SCANVIS also annotates each splice junction by indicating whether the junction is supported by annotation or not, and if not, what type of junction it is (e.g. exon skipping, alternative 5’ or 3’ events, Novel Exons). Unannotated junctions are also futher annotated by indicating whether it induces a frame shift or not. SCANVIS includes a visualization function to generate static sashimi-style plots depicting relative read support and number of split reads using arc thickness and arc heights, making it easy for users to spot well-supported junctions. These plots also clearly delineate unannotated junctions from annotated ones using designated color schemes, and users can also highlight splice junctions of choice. Variants and/or a read profile are also incoroporated into the plot if the user supplies variants in bed format and/or the BAM file. One further feature of the visualization function is that users can submit multiple samples of a certain disease or cohort to generate a single plot - this occurs via a “merge” function wherein junction details over multiple samples are merged to generate a single sashimi plot, which is useful when contrasting cohorots (eg. disease vs control).

  • scBFA This package is designed to model gene detection pattern of scRNA-seq through a binary factor analysis model. This model allows user to pass into a cell level covariate matrix X and gene level covariate matrix Q to account for nuisance variance(e.g batch effect), and it will output a low dimensional embedding matrix for downstream analysis.

  • scDblFinder Efficient identification of doublets in single-cell RNAseq directly from counts using overclustering-based generation of artifical doublets.

  • scGPS The package implements two main algorithms to answer two key questions: a SCORE (Stable Clustering at Optimal REsolution) to find subpopulations, followed by scGPS to investigate the relationships between subpopulations.

  • schex Builds hexbin plots for variables and dimension reduction stored in single cell omics data such as SingleCellExperiment and SeuratObject. The ideas used in this package are based on the excellent work of Dan Carr, Nicholas Lewin-Koh, Martin Maechler and Thomas Lumley.

  • scPCA A toolbox for sparse contrastive principal component analysis (scPCA) of high-dimensional biological data. scPCA combines the stability and interpretability of sparse PCA with contrastive PCA’s ability to disentangle biological signal from techical noise through the use of control data. Also implements and extends cPCA.

  • scTGIF scTGIF connects the cells and the related gene functions without cell type label.

  • SEtools This includes a set of tools for working with the SummarizedExperiment class, including handy merging and plotting functions.

  • SharedObject This package is developed for facilitating parallel computing in R. It is capable to create an R object in the shared memory space and share the data across multiple R processes. It avoids the overhead of memory dulplication and data transfer, which make sharing big data object across many clusters possible.

  • signatureSearch This package implements algorithms and data structures for performing gene expression signature (GES) searches, and subsequently interpreting the results functionally with specialized enrichment methods.

  • SigsPack Single sample estimation of exposure to mutational signatures. Exposures to known mutational signatures are estimated for single samples, based on quadratic programming algorithms. Bootstrapping the input mutational catalogues provides estimations on the stability of these exposures. The effect of the sequence composition of mutational context can be taken into account by normalising the catalogues.

  • SingleR Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

  • sojourner Single molecule tracking has evolved as a novel new approach complementing genomic sequencing, it reports live biophysical properties of molecules being investigated besides properties relating their coding sequence; here we provided “sojourner” package, to address statistical and bioinformatic needs related to the analysis and comprehension of high throughput single molecule tracking data.

  • Spaniel Spaniel includes a series of tools to aid the quality control and analysis of Spatial Transcriptomics data. The package contains functions to create either a Seurat object or SingleCellExperiment from a count matrix and spatial barcode file and provides a method of loading a histologial image into R. The spanielPlot function allows visualisation of metrics contained within the S4 object overlaid onto the image of the tissue.

  • SQLDataFrame SQLDataFrame is developed to lazily represent and efficiently analyze SQL-based tables in R. SQLDataFrame supports common and familiar ‘DataFrame’ operations such as ‘[’ subsetting, rbind, cbind, etc.. The internal implementation is based on the widely adopted dplyr grammar and SQL commands. In-memory datasets or plain text files (.txt, .csv, etc.) could also be easily converted into SQLDataFrames objects (which generates a new database on-disk).

  • ssPATHS This package generates pathway scores from expression data for single samples after training on a reference cohort. The score is generated by taking the expression of a gene set (pathway) from a reference cohort and performing linear discriminant analysis to distinguish samples in the cohort that have the pathway augmented and not. The separating hyperplane is then used to score new samples.

  • target Implement the BETA algorithm for infering direct target genes from DNA-binding and perturbation expression data Wang et al. (2013) <doi: 10.1038/nprot.2013.150>. Extend the algorithm to predict the combined function of two DNA-binding elements from comprable binding and expression data.

  • TOAST This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include 1. detect cell-type specific or cross-cell type differential signals 2. improve variable selection in reference-free deconvolution.

  • tradeSeq tradeSeq provides a flexible method for finding genes that are differentially expressed along one or multiple trajectories, using a variety of tests suited to answer questions of interest, e.g. the discovery of genes that whose expression is associated with pseudotime, or who are differentially expressed (in a specific region) along the trajectory. It fits a generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

  • VariantExperiment VariantExperiment is a Bioconductor package for saving data in VCF/GDS format into RangedSummarizedExperiment object. The high-throughput genetic/genomic data are saved in GDSArray objects. The annotation data for features/samples are saved in DelayedDataFrame format with mono-dimensional GDSArray in each column. The on-disk representation of both assay data and annotation data achieves on-disk reading and processing and saves memory space significantly. The interface of RangedSummarizedExperiment data format enables easy and common manipulations for high-throughput genetic/genomic data with common SummarizedExperiment metaphor in R and Bioconductor.

  • ViSEAGO The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations, which are retrieved from one of NCBI EntrezGene, Ensembl or Uniprot databases for several species. Using available R packages and novel developments, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility.

  • waddR Wasserstein distance based statistical test for detecting and describing differential distributions in one-dimensional data. Functions for wasserstein distance calculation, differential distribution testing, and a specialized test for differential expression in scRNA data are provided.

  • XCIR Models and tools for subject level analysis of X chromosome inactivation (XCI) and XCI-escape inference.

New Data Experiment Packages

There are 15 new data experiment packages in this release of Bioconductor.

  • benchmarkfdrData2019 Benchmarking results for experimental and simulated data sets used in Korthauer and Kimes et al. (2019) to compare methods for controlling the false discovery rate.

  • biscuiteerData Contains default datasets used by the Bioconductor package biscuiteer.

  • depmap The depmap package is a data package that accesses datsets from the Broad Institute DepMap cancer dependency study using ExperimentHub. Datasets from the most current release are available, including RNAI and CRISPR-Cas9 gene knockout screens quantifying the genetic dependency for select cancer cell lines. Additional datasets are also available pertaining to the log copy number of genes for select cell lines, protein expression of cell lines as measured by reverse phase protein lysate microarray (RPPA), ‘Transcript Per Million’ (TPM) data, as well as supplementary datasets which contain metadata and mutation calls for the other datasets found in the current release. The 19Q3 release adds the drug_dependency dataset, that contains cancer cell line dependency data with respect to drug and drug-candidate compounds. This package will be updated on a quarterly basis to incorporate the latest Broad Institute DepMap Public cancer dependency datasets. All data made available in this package was generated by the Broad Institute DepMap for research purposes and not intended for clinical use. This data is distributed under the Creative Commons license (Attribution 4.0 International (CC BY 4.0)).

  • HMP2Data HMP2Data is a Bioconductor package of the Human Microbiome Project 2 (HMP2) 16S rRNA sequencing data. Processed data is provided as phyloseq, SummarizedExperiment, and MultiAssayExperiment class objects. Individual matrices and data.frames used for building these S4 class objects are also provided in the package.

  • MMAPPR2data Contains data for illustration purposes in the MMAPPR2 package, namely simulated BAM files containing RNA-Seq data for a mutation in the slc24a5 gene, taken from the GRCz11 genome. Also contains reference sequence and annotation files for the region.

  • MouseGastrulationData Provides processed and raw count matrices for single-cell RNA sequencing data from a timecourse of mouse gastrulation and early organogenesis.

  • muscData Data package containing a collection of multi-sample multi-group scRNA-seq datasets in SingleCellExperiment Bioconductor object format.

  • PhyloProfileData Two experimental datasets to illustrate running and analysing phylogenetic profiles with PhyloProfile package.

  • This package provides reference data required for pwrEWAS. pwrEWAS is a user-friendly tool to estimate power in EWAS as a function of sample and effect size for two-group comparisons of DNAm (e.g., case vs control, exposed vs non-exposed, etc.).

  • Companion data sets to showcase the functionality of the ReactomeGSA package. This package contains proteomics and RNA-seq data of the melanoma B-cell induction study by Griss et al.

  • RNAmodR.Data RNAmodR.Data contains example data, which is used for vignettes and example workflows in the RNAmodR and dependent packages.

  • This package contains: 1. A microarray gene expression dataset from a human breast cancer study. 2. A RNA-Seq gene expression dataset from a mouse study on IFNG knockout. 3. ID mapping tables between gene IDs and SBGN-ML file glyph IDs. 4. Percent of orthologs detected in other species of the genes in a pathway. Cutoffs of this percentage for defining if a pathway exists in another species. 5. XML text of SBGN-ML files for all pre-collected pathways.

  • signatureSearchData CMAP/LINCS hdf5 databases and other annotations used for signatureSearch software package.

  • tartare provides raw files (size=278MBytes) recorded on different Liquid Chromatography Mass Spectrometry (LC-MS) instruments. All included MS instruments are manufactured by Thermo Fisher Scientific and belong to the Orbitrap Tribrid or Q Exactive Orbitrap family of instruments. Despite their common origin and shared hardware components (e.g. Orbitrap mass analyser), the above instruments tend to write data in different “dialects” in a shared binary file format (.raw). The intention behind tartare is to provide complex but slim real-world files that can be used to make code robust with respect to this diversity. In other words, it is intended for enhanced unit testing. The package is considered to be used with the rawDiag package (Trachsel, 2018 <doi:10.1021/acs.jproteome.8b00173>) and the Spectra MsBackends.

  • TENxBUSData Download Barcode, UMI, and Set (BUS) format of 10x datasets from within R. This package accompanies the package BUSpaRse, which can load BUS format into R as a sparse matrix, and which has utility functions related to using the C++ command line package bustools.

New Annotation Packages

There are 3 new annotation packages in this release of Bioconductor.

NEWS from new and existing Software Packages


Changes in version 1.3.7


  • Package vignette has been updated to address the new features


  • For each fold, for each gene for which a GReX could be imputed, the following values are now returned

  • Squared correlation of the model’s predictions with training data

  • P-value of the model

  • Corrected p-value of the model with benjamini-hochberg procedure

  • Correlation of the model’s predictions with validation data

  • Squared correlation of the model’s predictions with validation data

  • P-value of the correlation test of the model’s predictions with validation data

Changes in version 1.3.5


  • P-value of the cor.test() between predicted GReX and real expression values of genes is returned in when performing cross-validation

  • When using affiXcanTrain in cross-validation mode, three main values for each gene are therefore returned: rho and rho squared (see changes in v 1.3.1), and the p-value of cor.test()

Changes in version 1.3.3


  • Formatting of functions documentation has been improved

  • Important: vignette is still outdated (AffiXcan 1.2.0)

Changes in version 1.3.2


  • Providing population structure covariates is now not mandatory to perform models training

Changes in version 1.3.1


  • ANOVA p-value < 0.05 to assess prediction significance is not used anymore; instead:

  • A k-fold cross-validation on the training dataset may be performed; k can be defined by the user

  • Pearson correlation coefficients (R) and determination coefficients (R^2) between predicted GReX and real expression values of genes are computed

  • In literature, GReX of genes for which the mean of the R^2 is above 0.01 are considered non-randomly predicted, according to the new benchmarking standards [ref]


Changes in version 1.1

  • Added ability to process output from Salmon v0.14 or later


Changes in version 0.99.2 (2019-08-15)

  • Fixed bugs.

  • Made the following significant changes o Using BiocParallel for parallel evaulation. o Updated documentation file.


Changes in version 0.99.8

  • Bioc review fixes

Changes in version 0.99.7

  • Bioc review fixes

Changes in version 0.99.0



Changes in version 1.12.1


  • Moved ggplot2 from Imports to Depends. This was necessary because cowplot doesn’t call ggplot2 explicitly anymore.


Changes in version 1.28.0


  • (version 1.27.1) makeOrgPackage() supports GO ontologies.


Changes in version 2.17.0


  • (2.17.6) remove debugging message of loading resource (AH: 1)

  • (2.17.5) system environment variable to control localHub option for creating hub based only on previously downloaded resources

  • (2.17.9) Allow force redownload of Hub sqlite file with refreshHub

  • (2.17.12) Only display download message when something to download.

  • (2.17.13) The output list of files is the AH/EH id not AHid:resourceid


  • (2.17.4) Fix localHub when no internet connection. The internal use of isDevel was preventing Hub creation when no internet connection. Fixed by checking connection. This code pretained to orgDb filters

  • (2.17.8) On chance of very first download of hub failure, next call to construtor will redownload

  • (2.17.10) Fix ability to use hubs when offline

  • (2.17.11) Add BiocVersion to Imports. Fixes bug with R CMD check when testing if library can be loaded off search path. BiocManager doesn’t Import BiocVersions and this is needed to get the correct BiocManager version of the snapshot date.


Changes in version 1.15.0


  • 1.15.13 Added “BLOB” as a valid source type

  • 1.15.7 Added “MTX” as a valid source type

  • 1.15.6 Expanded documentation to clarify that data can be hosted publically not strictly Bioconductor AWS

  • 1.15.4 Added “XLS/XLSX” as valid source type


  • 1.15.11 updated GencodeGFF recipes for potential future use (still would revisit this with another update to do like ensembl on the fly)

  • 1.15.5 remove validity check that is wrong/outdated

  • 1.15.1 needToRerunNonStandardOrgDb added as helper function for when generating non standard org dbs. 1.15.3 added try catch in case aws buckets unreachable.


Changes in version 0.99.2 (2019-08-18)

  • Revise formats to consistent with Bioconductor coding styles.

  • Added unit tests

Changes in version 0.99.1 (2019-07-14)

  • Submitted to Bioconductor


Changes in version 1.8.0

  • Bringing in Josh Zitovsky’s work on fast beta binomial GLM fitting in C++.


Changes in version 3.15.1 (2019-08-28)


  • wpca() for matrices had a ‘length > 1 in coercion to logical’ bug.

Changes in version 3.15.0 (2019-05-02)

  • The version number was bumped for the Bioconductor devel version, which is now BioC 3.10 for R (>= 3.6.0).


Changes in version 0.99.10 (2019-10-25)

  • Fixed issue from quantifying RI and ALSS

Changes in version 0.99.9 (2019-10-22)

  • Fixed issue from quantifying single-end reads

Changes in version 0.99.8 (2019-10-17)

  • Made additional changes to conform to Bioconductor guidelines

Changes in version 0.99.7 (2019-10-17)

  • Made changes to conform to Bioconductor guidelines

Changes in version 0.99.6 (2019-10-16)

  • Replaced “1:” with “seq_len”.

Changes in version 0.99.5 (2019-10-15)

  • Implemented S4 class instead of reference class.

Changes in version 0.99.4 (2019-10-01)

  • Fixed vignette issue.

Changes in version 0.99.3 (2019-10-01)

  • Fixed package loading issue.

Changes in version 0.99.2 (2019-10-01)

  • Removed .Rproj file

Changes in version 0.99.1 (2019-10-01)

  • Added NEWS file.

Changes in version 0.99.0 (2019-10-01)

  • Submitted to Bioconductor.


Changes in version 1.3.1 (2019-10-22)

  • Data for six new strains, S. pyogenes AP1, E. coli BW25113, S. aureus HG001, L. lactis MG1363, B. subtilis NCIB 3610, and L. monocytogenes 10403S, have been added to AssessORFData

  • CITATION file added as corresponding paper has now been published

  • Updated MapAssessmentData such that verbose output is cleaner and more informative # AssessORF 1.1


Changes in version 1.9.9

  • export prepareBindingSitesList function. - Add rownames for footprintsScanner counts data.

Changes in version 1.9.8

  • Add error message for vPlot when no paired reads in bam file.

Changes in version 1.9.7

  • Fix the bug that gscore changed the output for splitGAlignmentsByCut.

Changes in version 1.9.6

  • Try to decrease the memory cost for splitGAlignmentsByCut.

Changes in version 1.9.5

  • Try to decrease the memory cost for splitGAlignmentsByCut.

Changes in version 1.9.4

  • Add the error handle if not enough mononucleosome reads for splitGAlignmentsByCut.

Changes in version 1.9.3

  • Try to decrease the memory cost for splitGAlignmentsByCut.

Changes in version 1.9.2

  • Fix the bug if the bam file containsupplementary alignments.

Changes in version 1.9.1

  • Fix the bug if the bam file contain mix of single ends and paired ends.


Changes in version 1.7

  • Added function cbind()


Changes in version 1.0.1 (2019-07-06)

  • Added DOI to cite code through zenodo.

Changes in version 1.0.0 (2019-07-06)

  • Introduced first official release of AutoTuner.

Changes in version 0.99.9 (2019-08-06)

  • Added changes to satisfy second round of bioc review o Fixed source path for mzDb data object o Removed redundant table of contents o Removed non used redundant data object eicParamEsts.rds

Changes in version 0.99.8 (2019-08-02)

  • Added changes to fix warnings o Replaced class == to is(). o Added corrections to dependencies regarding xcms.

Changes in version 0.99.7 (2019-08-02)

  • Introduced changes as part of bioconductor review process. o Added Author info to vignette. o Added installation instructions for package. o Removed mention of mmetspData in favor of test data package mtbls2. o Added table of contents to vignette. o Removed png within vignette folder that was not being used. o Changed dimensions of image returned from TIC plot in vignette. o Removed “-“ from documentation. o Fixed source paths on files using internal data for examples o Removed peak_table and peak_difference from data/ dir o Added documentation for eicParamsEsts object used in testing o swapped sapplys for vapplys o switched 1:.. to seq_len or seq_along o Added and implemented accessor and setter functions for Autotuner slots o Added unit tests for accessor functions.


Changes in version 0.99.2 (2019-06-14)

  • Submitted to Bioconductor


Changes in version 1.17.3

  • DESCRIPTION updated

  • Fixed WARNING: bamsignals.cpp:521:9: warning: ignoring return value of function declared with ‘warn_unused_result’ attribute [-Wunused-result] bamsignals.cpp:516:5: warning: ignoring return value of function declared with ‘warn_unused_result’ attribute [-Wunused-result] bamsignals.cpp:530:5: warning: ignoring return value of function declared with ‘warn_unused_result’ attribute [-Wunused-result]

Changes in version 1.17.2

  • Maintainer E-mail adress updated


Changes in version 1.2.0

  • Added mean and standard deviation estimates of the precision parameter

  • Allow estimation of parameters (without testing) when 1 group only is provided

  • Added 1 section of the vignette for inference with 1 group only

  • Added reference to BANDITS manuscript


Changes in version 1.7.20 (2019-10-17)

  • Bumps version number to trigger new build.

Changes in version 1.7.19 (2019-10-08)

  • BASiCS_TestDE now checks to ensure that both input chains have been run with Regression = FALSE or both with Regression = TRUE.

  • Remove duplicated text from BASiCS_Chain’s show method.

Changes in version 1.7.18 (2019-10-06)

  • Refactor HVG/LVG plots code to use ggplot2. When calling BASiCS_DetectHVG or BASiCS_DetectLVG, the plots are now stored in the returned list in the named element Plots. The vignette has been updated to show the usage of this functionality.

  • In all unit tests: use expect_equal(foo, bar) instead of expect_true(all.equal(foo, bar)). This gives better printing (ie, if it’s not true it tells by what margin)

  • Rename some functions for consistency in capitalisation. For example, BASiCS_showFit has been deprecated and renamed to BASiCS_ShowFit.

  • Add a Smooth argument to BASiCS_DiagPlot.

  • BASiCS_TestDE is now explicit about requiring the same number of samples in both chains. Previously it would fail due to arrays of non-conformable dimensions.

  • Add some internal utility functions.

  • Remove exportPattern(“^[^\Hidden]”) meaning functions must be explicitly exported using roxygen tags.

Changes in version 1.7.17 (2019-10-04)

  • Minor change in newBASiCS_Data to avoid missing colnames when adding colData

  • New unit test to verify that colnames are not lost

Changes in version 1.7.16 (2019-10-04)

  • Minor changes to NAMESPACE to pass R CMD Check

Changes in version 1.7.15 (2019-09-30)

  • Swtich from matrixStats dependency to Matrix as it supports more general input classes (including sparse matrices)

  • newBASiCS_Data now requires input counts to be a matrix.

Changes in version 1.7.14 (2019-09-27)

  • Changed internal functions from matrixStats to Matrix to support more classes of matrix (eg, dgCMatrix). BASiCS_MCMC now supports DelayedArray, dgEMatrix, dgCMatrix objects and likely more.

Changes in version 1.7.13 (2019-09-25)

  • Updated unit tests to account for new default choice for min.mean parameter in scran::computeSumFactors

  • New unit test to check for changes in scran::computeSumFactors

Changes in version 1.7.12 (2019-09-15)

  • changes maintainer’s email address

Changes in version 1.7.11 (2019-09-15)

  • Uncertainty parameter added to BASiCS_showFit. This enables optional inclusion of uncertainty measure around the regression trend.

  • Re-ordering of parameter in c++ MCMC samplers (does not affect output)

  • Avoid unnecessary transformations between NumericMatrix/Vector and arma::

  • Removes isSpike usage in BASiCS_Sim documentation

  • Removes isSpike call from the vignette

  • Adds missing parameters to the documentation of BASiCS_CorrectOffset

Changes in version 1.7.10

  • metadata(Data)$SpikeInput is now required to be a data.frame. This allows us to verify the correct order in spike-in inputs when the user manually modifies an existing SingleCellExperiment object.

  • Additional changes in newBASiCS_Data, HiddenBASiCS_MCMC_InputCheck, HiddenChecksBASiCS_Data to avoid errors.

  • HiddenBASiCS_MCMC_Start, HiddenBASiCS_MCMC_GlobalParams, BASiCS_DenoisedCounts and BASiCS_DenoisedRates modified to replace isSpike by altExp

  • Some unit tests adapted accordingly

Changes in version 1.7.9 (2019-09-05)

  • newBASiCS_Data, HiddenBASiCS_MCMC_InputCheck, HiddenChecksBASiCS_Data and BASiCS_MCMC modified to replace isSpike by altExp

  • WIP - unit test do not pass

Changes in version 1.7.8 (2019-08-20)

  • min.mean parameter exposed in BASiCS_CorrectOffset and BASiCS_TestDE

Changes in version 1.7.7 (2019-08-20)

  • Preliminary version of BASiCS_CorrectOffset has been added. This includes a trimmed option for the offset calculation that excludes lowly expressed genes. This is similar to what is implemented in `scran:::.rescale_clusters

Changes in version 1.7.6 (2019-08-19)

  • Offset correction within BASiCS_TestDE modified to use rowMedians instead of rowSums2. This makes it more robust to outlier genes.

  • Unit tests updated accordingly.

Changes in version 1.7.5 (2019-07-30)

  • Returns to original updates for X (fixed after burn-in)

Changes in version 1.7.4 (2019-07-30)

  • Show method for regression objects now correctly shows number of cells.

  • HiddenBASiCS_MCMCcppReg and HiddenBASiCS_MCMCcppRegNoSpikes (C++ code) modified to update design matrix throughout MCMC (GRBF locations remain fixed after the burn-in period is over)

  • Unit tests updated accordingly.

Changes in version 1.7.3 (2019-07-29)

  • Minor typo fixed in BASiCS_MCMC.

Changes in version 1.7.2 (2019-07-28)

  • Specific minimum tolerance thresholds (e.g. 1e-3 for mu updates) replaced by global parameters (e.g. mintol_mu). Optional parameters; internal use only. Incorporated within HiddenBASiCS_MCMC_ExtraArgs.

  • General clean up to remove code redundancy in BASiCS_MCMC

  • HiddenBASiCS_MCMC_GlobalParams created to facilitate clean-up above

Changes in version 1.7.1 (2019-07-27)

  • is_true deprecated in testthat. Unit tests updated to use expect_true


Changes in version 1.2.0

  • Deprecated rotate.all= in favour of get.all.genes= in multiBatchPCA().

  • Switched BSPARAM= to use IrlbaParam(deferred=TRUE) by default in fastMNN(), so that the default behaviour is actually fast.

  • Deprecated auto.order= in favor of merge.order= and auto.merge= in fastMNN() and mnnCorrect(). Automatic merging now detects potential tree-based merges. Merge trees can also be specified as input.

  • Added the correctExperiments() function to cbind the original assays alongside the merged values.

  • Added the subset.row= argument to cosineNorm() for in-place subsetting.

  • Added batch= and preserve.single= arguments to multiBatchNorm(). Standardized behavior of subset.row= by adding a normalize.all= argument.

  • Added the regressBatches() function for correction via standard linear regression.

  • Added the prop.k= argument in all MNN-related functions, to allow the value of k to adapt asymmetrically to the size of each batch.


Changes in version 1.7.1

  • using array back structure for the library to speed up the mapping process

  • depending on the configuration of the mechine, the alignment may speed up

  • to a factor as much as 3.


Changes in version 2.1.4 (2019-05-17)

  • minor changes

Changes in version 2.1.3 (2019-05-13)

  • Performance improvments o regarding function calcSummary o and calcScore

Changes in version 2.1.2 (2019-05-10)

  • New feature o y-axis in boxplot function can now be logged

Changes in version 2.1.1 (2019-05-09)

  • New feature o Implementation of outlier detection


Changes in version 1.4.0

  • Allow memory-efficient retrieval of the distance to the furthest neighbors.

  • Added a warn.ties= argument to turn off tie-related warnings in the KMKNN and VP tree algorithms.

  • Return neighbor counts in rangeFind() and rangeQuery() functions when get.index=FALSE and get.distance=FALSE.


Changes in version 1.10.1

  • Added a pkgdown website

Changes in version 1.8.1

  • Exported inverseList function

  • Improved spelling

  • Corrected a bug related to logical coercion of length greater than 1.


Changes in version 1.20


  • (v 1.19.2) Improve efficiency of MulticoreParam() when state does not persist across calls to bplapply().


Changes in version 1.2.0

  • Added the ResidualMatrix class for computing PCA on residuals efficiently.

  • Fixed runIrlba() to avoid errors at the limit of available PCs.

  • Added the FastAutoParam class to automatically choose a fast SVD depending on the matrix representation.

  • Added the bsparam() function to quickly set or get a global default algorithm choice.


Changes in version 2.42.0


  • The results of queries will now be cached, and if repeated queries are detected the results are loaded from disk.


  • Ensembl users will be redirected to their closest mirror unless the host argument is explicitly provided. In this case the defined value will be enforced.

  • Unused argument ‘ssl.verifypeer’ removed from listMarts() and useMarts().

  • RCurl removed from package dependecies.


  • Improvements made to selecting the correct port when using http vs https

  • Results that contain unescaped new line characters are now returned successfully.


Changes in version 1.1.10

  • updated tutorial: added circular plot

Changes in version 1.1.9

  • updated tutorial: updated description for two parallel computing; cirPlot4pathway() example added; seeds added

  • updated plotRankedFeature().

Changes in version 1.1.8

  • updated tutorial: fixed typo ‘param1’ to ‘param2’

  • added a new function cirPlot4pathway()

Changes in version 1.1.7

  • updated tutorial

Changes in version 1.1.6

  • improved plotVarExplained() and plotRankedFeature()

  • renamed R functions for getDataAfterFS, BioMMreconData, BioMMstage1pca

  • updated installation approaches (including R 3.5 from Github)

  • updated tutorial to adapt the usage of the parallel package installed from Github

Changes in version 1.1.5

  • updated BioMM(); ‘dataMode’ added.

  • fixed roc() in getMetrics()

Changes in version 1.1.4

  • removed the examples with omcis2chrlist()

  • updated the omics2pathlist()

Changes in version 1.1.3

  • added required package pROC for getMetrics()

  • updated NAMESPACE and Rd file.

Changes in version 1.1.2

  • added the library pROC in the tutorial.

Changes in version 1.1.1

  • updated functions getMetrics(), plotVarExplained() and plotRankedFeature(); to focus on pathway based result report.

  • updated BioMMtutorial.Rmd

Changes in version 1.1.0

  • removed gene and chromosome based stratification methods.

  • updated feature selection method based on filtering getDataAfterFS().

  • updated BioMM() function to focus on pathway based machine learning.

  • updated BioMMtutorial.Rmd


Changes in version 1.13.1

  • Functions to manipulate GmtList objects are considerably expanded

  • All documents and namespaces are now managed by roxygen2

  • readGmt by default read unique genes from GMT files


Changes in version 1.13.20


  • plot.biosignMultiDataSet correction to include all plots in the .pdf file

Changes in version 1.13.18


  • Minor correction in the plot.biosignMultiDataSet documentation

Changes in version 1.13.16


  • Minor correction in the biosignMultiDataSet class documentation

Changes in version 1.13.14


  • Minor correction in the biosignMultiDataSet class documentation

Changes in version 1.13.12


  • Minor internal modification

Changes in version 1.13.10


  • Minor internal modification

Changes in version 1.13.8


  • final call to warnings() omitted

Changes in version 1.13.6


  • seedI argument now available (set to 123 by default)

  • biosign can now be applied to MultiDataSet objects (getMset method to get the updated MultiDataSet back)

Changes in version 1.13.4


  • minor internal modification

Changes in version 1.13.2


  • info.txtC and fig.pdfC argument values NULL and NA replaced by ‘none’ and ‘interactive’, respectively


Changes in version 0.99.13 (2019-10-11)

  • Final Clean up of code

  • Added normalization helper function

Changes in version 0.99.9 (2019-09-30)

  • Major rewrite to functionalize outlier_analysis and reduce redundant code

  • Fixed Reviewer suggestions o changed assigner symbol o renamed vignette o changed getwd() -> tempdir()

Changes in version 0.99.7 (2019-09-10)

  • Submitted to Bioconductor

  • Fixed Reviewer suggestions o Got rid of lazydata loading in DESCRIPTION o properly formetted NEWS object


Changes in version 1.2.1

  • Added new genotyping method based on binomial probabilities see parameter genoT = ‘fisher’ or ‘binom’; default: ‘fisher’


Changes in version 0.99.21 (2019-10-17)

  • Fix: BiocycPathwayGenes now deals with finding multiple Ensembl IDs

Changes in version 0.99.20 (2019-08-16)

  • Feature: function to extract field information from brenda.entries objects

  • Feature: DownloadBrenda now utilizes BiocFileCache

  • Performance: ReadBrenda is now 50% faster

Changes in version 0.99.10 (2019-08-12)

  • Doc: updated the vignette, readme and package help page

  • Doc: added documentation for data file acronyms.RData

Changes in version 0.99.0 (2019-07-22)

  • Submitted to Bioconductor


Changes in version 0.99.25 (2019-09-11)

  • Added message to indicate when get_velocity_files is extracting exon-exon junctions. - Restored “separate” to be default isoform_action in get_velocity_files.

Changes in version 0.99.24 (2019-09-06)

  • When sorting tr2g from file, now the file must be formatted in ways required by bustools.

Changes in version 0.99.23 (2019-09-06)

  • Previous two version bumps did not accompany changes; those were used to trigger rebuilds on Bioconductor. - Added the functionality to use L-1 (L is read length) bases around exon-exon junction to better distinguish between spliced and unspliced transcripts for RNA velocity. - Fixed serious problem with get_velocity_file that counted reads mapping to exons of length between L-1 and 2(L-1) as from unspliced transcript. This was done by an reimplementation of the method to get flanked intronic ranges. - Changed default isoform_action to “collapse”. - Make sure that all transcripts in tr2g.tsv from get_velocity_files are in the transcriptome.

Changes in version 0.99.20 (2019-08-26)

  • Addressed Bioconductor review.

Changes in version 0.99.19 (2019-07-23)

  • Finished get_velocity_files to generate files required for kallisto | bustools RNA velocity.

Changes in version 0.99.0 (2019-06-21)

  • Submitted package to Bioconductor for review


Changes in version 1.5.3

  • Added citation to BMC Bioinformatics paper.

Changes in version 1.5

  • Added new functions for spatial analysis of clusters: findLinks finds nearby pairs of clusters (for example TSSs and enhancers) and calculates the correlation of expression between them. findStretches find stretches along the genome where clusters are within a certain distance of eachother (for example groups of enhancer forming a super enhancer) and calculates the average pairwise correlation between members.

  • Changed the way clustering works: CAGEfightR uses coverage() to calculate genome-wide signals and now rounds the resulting signal to a certain number of digits (this can be modified via the CAGEfightR.round option), to prevent small positive or negative values due to floating point errors. This makes clustering more stable meaning the tuneTagClustering function is now deprecated. This should also increase the speed of most functions.

  • CAGEfightR now uses GPos instead of GRanges for storing CTSSs, this should result in improved memory performance.

  • Several changes to clusterBidirectionality: Balance is now calculated using the midpoint as well (preventing some rare cases where the midpoint could mask a single highly expressed CTSS), the pooled CTSS signal is now prefiltered for bidirectionality to increase speed and custom balance function can be provided (Bhattacharyya coefficient and Andersson’s D are included).

  • Added new check-functions to make it easier to check if objects are formatted correctly


Changes in version 1.28.0


  • The CTSS objects are now based on the UnstitchedGPos class instead of the parent GPos class. Existing CAGEexp objects might give errors after package upgrade.


  • Depends on MultiAssayExperiemnt instead of previously Importing it. No need to load it by hand (nor SummaryExperiment) anymore.


  • Correct strand in .remove.added.G private function (PR#26).


Changes in version 0.99.0 (2019-07-18)

  • Submitted to Bioconductor


Changes in version 1.41.1


  • allow findAdducts alternative intval (thanks to Sunil Dhakad)


Changes in version 1.19.05

  • move vignette to inst/doc

Changes in version 1.19.04

  • omit GSEAlm dependency

  • include used functions from gsealm to canceR package in gsealm.R file.

Changes in version 1.19.03

  • compress RData files to RDS and move them from /data to /extdata/rdata

  • update running examples

Changes in version 1.19.02

  • remove /extdata/gct_cls

  • do not import grDevices::quartz

  • add empty line in test functions

Changes in version 1.19.01

  • remove .txt file from /data.

  • import grDevices package

  • Adjust the vignetteEngine package


Changes in version 2.3.18 (2019-10-27)


  • Processing in ‘crossValidate()’ now allows processing unprocessed data by performing peak-picking on the mean spectra of the training sets


  • Fixed some errors in user messages during peak processing

Changes in version 2.3.17 (2019-10-25)


  • Default for ‘peakBin()’ argument ‘type’ is now “area”

  • In ‘peakBin()’, peak boundaries should be calculated more accurately now, and general speed improvements

  • In ‘peakAlign()’, peak centers are now calculated as weighted average mass rather than the highest point

Changes in version 2.3.16 (2019-10-14)


  • New class ‘ImagingSummary’ with sub-classes including ‘SparseImagingSummary’ and ‘MSImagingSummary’ with appropriate ‘plot()’ and ‘image()’ methods


  • The ‘summarize()’ method for ‘SparseImagingExperiment’ now returns a ‘SparseImagingSummary’, to more closely reflect “tidy” data principles by returning an object of a similar class; the previous behavior can be reproduced by specifying ‘.as=”DataFrame”’

Changes in version 2.3.15 (2019-10-13)


  • For methods requiring ‘resolution’ or ‘tolerance’, the default arguments have been updated to automatically guess based on the data

Changes in version 2.3.14


  • Add spectraData() as an alias for ‘imageData()’ for ‘MSImagingExperiment’ sub-classes

  • Formalize ‘mzData()’ and ‘intensityData()’ getters and setters for ‘MSProcessedImagingExperiment’

  • Add ‘peaks()’ and ‘peakData()’ methods for extracting peak matrices and/or peak information

  • Add ‘isCentroided()’ method for guessing whether spectra are centroided (without using the @centroided slot)


  • Allow ‘NA’ for @centroided slot for ‘MSImagingExperiment’

  • ‘mzBin()’ method now sets centroided = NA

  • Update ‘mzFilter()’ with parameter defaults so that ‘thresh.max = NA’ and new arg ‘ = TRUE’

  • Log more pre-processing information (e.g., method name)

Changes in version 2.3.13


  • Try using ‘parent.frame(1)’ instead of ‘parent.frame(2)’ to fix NSE methods when used in LHS of a maggritr pipe

  • Fix weird ‘iData()<-‘ missing argument ‘i’ bug

Changes in version 2.3.12


  • Changed default ‘peakPick()’ method to ‘mad’

  • In ‘peakPick()’ method ‘mad’, change the default number of blocks to 1 (no adaptive smoothing)

  • In ‘peakPick()’ method ‘mad’, update w/ new arguments w/ new defaults ‘fun=median’ and ‘tform=diff’


  • In ‘peakPick()’ methods ‘simple’ and ‘adaptive’, warn if kurtosis cannot be estimated and try to recover

  • In ‘normalize()’ method ‘reference’, provide a warning if the reference value is 0 for a pixel

Changes in version 2.3.11


  • Improved speed in ‘spatialFastmap()’

  • Improved speed in ‘spatialShrunkenCentroids()’

  • New dissimilarity metrics for ‘spatialFastmap()’ including a new default metric=’average’


  • Fix error in ‘print()’ for facet plots where lims=NULL

Changes in version 2.3.10


  • Improved speed in ‘spatialDGMM()’, by moving spatial filtering of probabilities to C code, up to 10x faster

  • Linesearch in ‘spatialDGMM()’ now uses ‘optimize()’ rather than ‘optim()’ – results may differ slightly

Changes in version 2.3.9


  • Added ‘Cardinal.history()’ and ‘Cardinal.version()’


  • Removed under-used setter generic function definitions


  • Cleaned up generics to reflect ProtGenerics >= 1.17.2

Changes in version 2.3.8


  • Added boxplot, histogram, and bar chart functionality to the ‘plot()’ method for ‘XDataFrame’

  • Added ‘plot()’ plotting for ‘AnnotatedImageList’

  • Added ‘plot()’ methods for ‘SpatialDGMM’, ‘MeansTest’, and ‘SegmentationTest’ result classes

  • Added ‘image()’ method for ‘MeansTest’ result class


  • Updated ‘plot()’ and ‘image()’ methods for ‘SpatialDGMM’, ‘MeansTest’, and ‘SegmentationTest’ result classes


  • Various bug fixes in object printing and plot auto-layout

Changes in version 2.3.7


  • Added ‘image()’ plotting for ‘AnnotatedImageList’


  • Plotting with ‘add=TRUE’ now respects ‘par(‘usr’)’ coordinates

Changes in version 2.3.6


  • Add ‘AnnotatedImageList’ class for list of ‘AnnotatedImage’ objects

  • Add ‘AnnotatedImagingExperiment’ class for containing data for an optical imaging experiment (e.g., a microscopy experiments)

  • Add ‘image()’ plotting for ‘AnnotatedImagingExperiment’


  • Redefine ‘@featureData’ slot of a ‘SparseImagingExperiment’ to be a ‘DataFrame’ rather than requiring an ‘XDataFrame’


  • Respect ‘layout’ and ‘byrow’ passed through … args to ‘print()’ method on facet plot objects

Changes in version 2.3.5


  • Moved some S4 method definitions from ‘ImagingExperiment’ to ‘SparseImagingExperiment’ so that the former can be more flexible for a wider variety of imaging modalities


  • Pass more … args through to ‘par()’ in plotting functions

Changes in version 2.3.4


  • Added ‘AnnotatedImage’ class for optical images

Changes in version 2.3.3


  • Improved facet plotting when ‘add=TRUE’


  • Better ‘cex.axis’ defaults and user setting for colorkeys

Changes in version 2.3.2


  • Improved ‘writeMSIData()’ for 3D and non-gridded data

Changes in version 2.3.1


  • Output directly to imzML while processing with ‘process()’


  • Improved auto-layout for visualization with multiple runs

  • Added ‘parse.only’ option to ‘readImzML()’ for parsing only

Changes in version 2.2.4


  • Fix large external array offsets in ‘writeImzML’

Changes in version 2.2.3


  • Cleaned up some ‘writeImzML’ mapping validity issues

Changes in version 2.2.2


  • Removed curly braces around UUID when writing imzML

Changes in version 2.2.1


  • Fixed bug in plotting results where ‘column’ argument would get matched before the ‘col’ argument


Changes in version 1.8.0 (2019-10-28)

New Features

  • Optimization has led obtainOneStudy() and obtainMultipleStudies() functions to work faster.

  • If an entered cancer has corrupted data or lacks the requested data type, obtainMultipleStudies() doesn’t return error. That study is automatically omitted from results and its name is printed on console.

  • AvailableData() function now works more accurately but unfortunately, it is generally slower: Due to inconsistancy in the terms that cgdsr uses, AvailableData() has to check the availability of the data at two different levels.


Changes in version 1.5.0


  • Revised default…, cv.max=Inf)

  • Added assignCelltype(…)

Changes in version 1.4.1


  • Added URL to published article.

  • Revised optimal_rank(…) such that Bayes factor criterion is used.

  • Fixed filter_genes(…) for cases with non-expressed genes


Changes in version 1.1.6 (2019-07-16)

  • Add multiclass decision tree

Changes in version 1.1.4 (2019-05-28)

  • Add Alternate headings support for plotDimReduceFeature

Changes in version 1.1.3 (2019-05-14)

  • Add multiclass decision tree (MCDT) cell cluster annotation

Changes in version 1.1.2 (2019-05-14)

  • Fix a bug in celdaHeatmap

Changes in version 1.1.1 (2019-05-09)

  • Default seed setting to maintain reproducibility


Changes in version 1.1.3

Bug Fixes

  • Data loading functions now appear in package index and documentation

Changes in version 1.1.2

Bug Fixes

  • Updated make_combinations to work with tidyr 1.0.0


  • Updated the WritingWrappers vignette. - Added a case study precompiled vignette.

Changes in version 1.1.1

New Features

  • Added any_task_errors() function to check if any tasks failed in benchmark tibble.


Changes in version 1.1.3

  • Add entropy and weighted isi function

  • Add evalIntegration function

  • Replace metric_prefix from plotting functions by metric parameter.


Changes in version 2.15.1

  • Added scree plot into champ.SVD() function.


Version: 1.13 Category: Defaults are now updated based on .npb file header rather than just checking them for consistency with it Text:

Version: 1.13 Category: When using Chicago with four-cutter enzymes, make sure you reduce minFragLen parameter. However, this can now only be done when generating the design files, and not in the R package itself Text:


Changes in version 2.10.0


  • A new test, proxReg(), tests for genomic region binding proximity to either gene transcription start sites or enhancer regions within gene sets. Used as an addendum to any gene set enrichment test, not exclusive to those in this package.


  • Poly-Enrich now uses the likelihood ratio test instead of the Wald test, as LRT is more robust when using a negative binomial GLM.


  • Poly-Enrich Approximate method that uses the score test now uses the correct formula.


Changes in version 3.19.5

  • fix the issue that findOverlapsOfPeaks will connect the peaks in same peak list.

Changes in version 3.19.4

  • add last choice for xget.

Changes in version 3.19.3

  • fix the colnames of addMetadata.

Changes in version 3.19.2

  • fix the issue that seqlevelsStyle(peak) == seqlevelsStyle(annotation) are not all TRUE

Changes in version 3.19.1

  • remove RangedData


Changes in version 1.21.1

  • new implementation of upsetplot (2019-08-29, Thu) - use ggupset, ggimage and ggplotify - subset method for csAnno object (2019-08-27, Tue)


Changes in version 1.11.1


  • Bugfix for error when exporting empty peaks in univariateHMM.


Changes in version 0.1.1 (2019-05-30)

  • First releaase


Changes in version 1.23.1

  • update citation.


Changes in version 2.5.7


  • Fix logical precedence error in C++ code for subsample loop

Changes in version 2.5.3


  • Made “kmeans” the default in subsampling if data type is “X”

  • Set checkDiss=FALSE by default for most all functions (exception is when user defines distance function)

  • Add warnings when forced to calculate a nxn distance matrix

  • Improve generic classification to centroids (used by “pam”) so not calculate unnecessary distances.

  • Added mbkmeans as built-in cluster function


  • Remove bug in built-in cluster function “kmeans” so as to not make unnecessary nxn distance matrix.


Changes in version 1.2.0

  • New function plotRecurrentRegions to visualize the landscape of recurrent CNV regions

  • New function plotEQTL to explore differential expression of genes in the neighborhood of a CNV region

  • Reworked vignette - dedicated section on applicability and scope, - overview of key functions, - extended input data format description,

    • visualizations and dedicated Gviz plots to illustrate key concepts


Changes in version 1.1.2

  • improve documentations

Changes in version 1.1.1

  • add GO_enrichment() and map_to_entrez_id().

  • add ncol()/nrow()/colnames()/rownames()/dim() helper functions.

  • use eulerr::euler() to make the Euler diagram.

  • simplified the rules for deciding the best k


Changes in version 2.1.1

  • Heatmap(): give error when heatmap has empty string as its name.

  • anno_mark(): text positions are correctly calculated now with rotations.

  • The order of legend labels are ordered by either sort or levels.

Changes in version 2.1.0

  • check the length of the clustering objects and the matrix rows/columns

  • anno_oncoprint_barplot(): add ylim argumnet

  • anno_mark(): add labels_rot argument

  • draw_legend(): legends for annotations with the same names are merged

  • densityHeatmap(): ylim works as it is expected.

  • add cluster_row_slices and cluster_column_slices to draw,HeatmapList-method()

  • densityHeatmap(): col can be set as a function

  • add cluster_rows/cluster_columns in oncoPrint()

  • legend labels support symbols

  • Heatmap(): add jitter argument to add tiny random shift to original matrix. It is mainly to solve the problem of “Error: node stack overflow” when there are too many identical rows/columns for plotting the dendrograms.


Changes in version 1.3.4 (2019-09-16)

  • table_means function of multi_de_pairs updated to be n=1 aware

  • add warning when less than two biological replicates

Changes in version 1.3.3 (2019-06-27)

  • norm_method paramter in multi_de_pairs to allow only EDASeq normalisation

Changes in version 1.3.2 (2019-06-21)

  • make character output for annotation

  • remove prior normalisation for RUVr

Changes in version 1.3.1 (2019-06-18)

  • fix buildSummarized bug in detection of minimum paired numbers

  • fix buildSummarized htseq with out of order rownames

  • add parameter to buildSummarized for technical_reps

  • technical_reps merges reads from technical replicates

  • change merged column name from p_max to p_intersect

  • change LogFC of merged results to mean(LogFC) of all methods

  • change AveExpr of merged results to mean(AveExpr) of all methods

  • addition of merged column name p_union (Union)

  • addition of merged column name LogFC_sd (Standard Deviation of FC)

  • updating plotting functions to add weight for LogFC_sd

  • add numbers for each category to legend of plots

  • disabled cooksCutoff for DESeq2 for comparability of all p-value rankings

  • add option gtf_annotate multi_de_pairs for annotation of gene symbols from gtf and combine with tx_db

  • update vignette

  • version 1.3.0 onwards is BioC 3.9


Changes in version 1.8.0

  • New function get.hao.subtypes to predict the tissue of origin of ovarian tumors as either fallopian tube (FT) or ovarian surface epithelium (OSE) based on Hao et al., Clin Cancer Res, 2017


Changes in version 1.25.6

  • added parameter ignore.strand to indidate whether gene annotation should be strand-specific

Changes in version 1.25.5

  • efficacy is calculated only for on-target

Changes in version 1.25.4

  • annotation is now strand-specific

Changes in version 1.25.1


  • added paired.orientation parameteter


Changes in version 0.99.27 (2019-10-22)

  • Use tempdir() in test to avoid using home dir of bioconductor build machine

Changes in version 0.99.26 (2019-09-23)

  • Use tempdir() in examples and vignette to prevent from contaminating Bioc and users’ machine

Changes in version 0.99.24 (2019-09-23)

  • Update source code for robustness

Changes in version 0.99.23 (2019-09-14)

  • Add support for type SummarizedExperiment in function predictor()

  • Fix output directory problem in main function

  • Remove some unused functions

Changes in version 0.99.22 (2019-09-06)

  • Fix bugs by removing lazy load

Changes in version 0.99.21 (2019-09-06)

  • Add overwrite function for main function

  • Optimize packages suggested checking

Changes in version 0.99.20 (2019-07-30)

  • Fix predictor() error by complete cases

Changes in version 0.99.19 (2019-07-29)

  • Fix m.f.s bug when calculating centroid of new matrix

Changes in version 0.99.18 (2019-07-29)

  • Add a choice for using kmeans() for super-clustering

Changes in version 0.99.17 (2019-07-29)

  • Add a parameter allowing keep rows with no variance

  • List for centroid2exp() should not be filtered by variance

Changes in version 0.99.16 (2019-07-29)

  • CrossICC now need R version >= 3.5

  • Update ssGSEA function

Changes in version 0.99.15 (2019-07-28)

  • CrossICC now need R version >= 3.6

  • Fix NAMESPACE bug

Changes in version 0.99.14 (2019-07-28)

  • Update vignette and man pages

Changes in version 0.99.13 (2019-07-28)

  • Update vignette and man pages

Changes in version 0.99.12 (2019-07-28)

  • Fix ssGSEA() bug

  • Remove external shiny calling function

  • CrossICC() can reset working directory to previous one now

Changes in version 0.99.11 (2019-07-28)

  • Add sankey plot to shiny app

  • Optimize the main function

Changes in version 0.99.10 (2019-07-27)

  • Update ssGSEA man page

Changes in version 0.99.9 (2019-07-27)

  • Label ssGSEA examples as donttest

Changes in version 0.99.8 (2019-07-27)

  • Update help page of function CrossICCInput(): example should contain file name pattern

Changes in version 0.99.7 (2019-07-26)

  • Update man pages

Changes in version 0.99.6 (2019-07-26)

  • Use all functions in reloaded MergeMaid code

  • To test all examples in exported function

Changes in version 0.99.5 (2019-07-26)

  • Turn off default shiny calling

Changes in version 0.99.4 (2019-07-26)

  • Update some man pages

Changes in version 0.99.3 (2019-07-26)

  • Update examples for most functions

  • Remove random seed of ConcensusClusterPlus function

Changes in version 0.99.2 (2019-07-25)

  • Fix some mistakes in Rd files

Changes in version 0.99.1 (2019-07-25)

  • Main function CrossICC will not use shiny app by default

  • Add sankey plot

  • Remove some default dependencies (only needed when use shiny)

  • Fix some check error and warnings

Changes in version 0.1.1 (2019-06-25)

  • Update vignette and some man pages for functions

Changes in version 0.1.0 (2019-06-25)

  • The first version of CrossICC

  • Submitted to Bioconductor


Changes in version 1.20.0

  • Removed deprecated functionality in normOffsets(), readParam(), scaledAverage().

  • Added mergeResults(), overlapResults() wrapper functions to simplify getting region-level results.

  • Added mergeWindowsList(), findOverlapsList() functions for consolidating windows from multiple analyses. Deprecated consolidateWindows().

  • Added mergeResultsList(), overlapResultsList() wrapper functions to obtain consolidated region-level results. Deprecated consolidateTests(), consolidateOverlaps().

  • Renamed regions= to ranges= in mergeWindows() for consistency.

  • Added clusterWindowsList() to replace consolidateClusters().

  • Added filterWindowsGlobal(), filterWindowsLocal(), filterWindowsProportion() and filterWindowsControl(). Deprecated filterWindows().

  • Minor renaming of scaleControlInfo() arguments, added and assay.back= arguments.


Changes in version 1.4

New features

  • Predict targeting drugs (predictTargetingDrug()): - Based on expression and drug sensitivity associations derived from NCI60, CTRP and GDSC data (see loadExpressionDrugSensitivityAssociation()) - Compare user-provided differential expression profile with gene expression and drug sensitivity associations to predict targeting drugs and their targeted genes - Compounds are ranked based on their relative targeting potential - Plot candidate targeting drugs against ranked compound perturbations using plotTargetingDrugsVSsimilarPerturbations(), highlighting compounds that selectively select against cells with a similar differential gene expression profile - Analyse drug set enrichment (performDSEA()): - Prepare drug sets based on a table with compound identifiers and respective 2D and 3D molecular descriptors using prepareDrugSets() - Test drug set enrichment on results from rankSimilarPerturbations() (when ranking against compound perturbations) and predictTargetingDrugs() - Convert ENSEMBL identifiers to gene symbols using convertENSEMBLtoGeneSymbols()

Major changes

  • Update the tutorial and function documentation - Remove most L1000 instances, including in function names: - getL1000perturbationTypes() -> getCMapPerturbationTypes() - getL1000conditions() -> getCMapConditions() - downloadL1000data() -> loadCMapData() - filterL1000metadata() -> filterCMapMetadata() - loadL1000perturbations() -> prepareCMapPerturbations() - compareAgainstL1000() -> rankSimilarPerturbations() - plotL1000comparison() -> plot() - Improve loading of ENCODE samples (loadENCODEsamples()): - Rename function from downloadENCODEsamples() to loadENCODEsamples() - Load ENCODE samples regarding multiple cell lines and experiment targets using loadENCODEsamples() - Improve CMap data and metadata retrieval: - By default, do not return control perturbation types when using getCMapPerturbationTypes() (unless if using argument control = TRUE) - Parse CMap identifiers using parseCMapID() - Load CMap’s compound metadata using loadCMapData() - Ask to download CMap perturbations z-scores file for differential expression if not found (avoiding downloading a huge file without user consent) - Improve preparation of CMap perturbations (prepareCMapPerturbations()): - Allow to load CMap metadata directly from files when using file paths as arguments of prepareCMapPerturbations() - Significantly decrease memory required to use cTRAP by loading chunks of z-scores from CMap perturbations on-demand (a slight decrease in time performance is expected), unless prepareCMapPerturbations() is run with argument loadZscores = TRUE - Display summary of loaded perturbations after running prepareCMapPerturbations() - Improve ranking of similar perturbations (rankSimilarPerturbation()): - Redesigned output: long (instead of wide) table - By default, calculate mean across cell lines if there is more than one cell line available; disabled if argument cellLineMean = FALSE - Allow to rank (or not) individual cell line perturbations (argument rankIndividualCellLinePerturbations) when the mean is calculated - Allow to perform multiple comparison methods if desired (by providing a vector of supported methods via the method argument) - Calculate the rank product’s rank to assess ranks across multiple methods - Sort results based on rank product’s rank (or the rank of the only comparison method performed, otherwise) - Include information for calculated means across cell lines in metadata - Include run time as an attribute - Improve metadata display for a similarPerturbations object, obtained after running rankSimilarPerturbations(): - Show further metadata information (including compound data, if available) related with a given perturbation by calling print() with a similarPerturbations object and a specific perturbation identifier - Show a complete table with metadata (and compound information, if available) when calling as.table() with a similarPerturbations object - Improve plotting (plot()): - Plot comparison results against all compared data by calling plot() with the results obtained after running rankSimilarPerturbations() or predictTargetingDrugs(); non-ranked compared data can also be plotted with argument plotNonRankedPerturbations = TRUE - Render scatter and Gene Set Enrichment Analysis (GSEA) plots between differential expression results and a single perturbation by calling plot() with a perturbationChanges object (if an identifier regarding the summary of multiple perturbations scores across cell lines is given, the plots are coloured by cell line) - When displaying GSEA plots, plot results for most up- and down-regulated user-provided differentially expressed genes (by default) - Improve GSEA plot style, including rug plot in enrichment score plot (replacing the gene hit plot)

Bug fixes and minor changes

  • CMap metadata minor improvements: - Improve list returned by getCMapConditions(), including sorting of dose and time points - Correctly set instances of -666 in CMap metadata as missing values and fix specific issues with metadata (such as doses displayed as 300 ng|300 ng) - In compound metadata, fix missing values showing as literal “NA” values - CMap perturbation minor improvements: - Fix error when subsetting a perturbationChanges object with only one row
  • Improve performance when subsetting perturbationChanges objects - Minor improvements to rankSimilarPerturbations(): - Correctly set name of perturbations depending on their type (genes, biological agents or compounds) - Improve performance when correlating against multiple cell lines - Remove cellLine argument (please filter conditions with upstream functions such as filterCMapMetadata()) - Fix incorrect label of first column identifiers - Report run time and settings used - Perform comparisons against perturbations disregarding their cell lines (faster runtime) - Fix error when trying to calculate the mean for cell lines with no intersecting conditions available - Clearly state to the user when no intersecting genes were found between input dataset and CMap data - Minor improvements to plot(): - Improve rendering performance of the GSEA plot - Fix disproportionate height between top and bottom enrichment score panels in GSEA plots - Update demo datasets: - Update the cmapPerturbationsCompounds and cmapPerturbationsKD datasets according to new internal changes and fix their respective code in the documentation - Include license and copyright text for cmapR code

Changes in version 1.23.5

  • add dontrun for prepareProteomeByFTP in case there is net connection issue.

Changes in version 1.23.4

  • return errors when type of getSequence is not correct.

Changes in version 1.23.3

  • Update documentation.

Changes in version 1.23.1

  • Add function prepareProteomeByFTP

  • fix the bug in addScheme


Changes in version 1.3.3 (2019-10-28)

  • Change package name from CAMTHC to debCAM

Changes in version 1.1.1 (2018-12-28)

  • Add reselectMG() to help select markers from all probes

  • Add redoASest() to re-estimate A and S matrix and optionally apply ALS

  • Add option for greedy search by sffsHull() function

  • Add sample.wight option for CAM(), CAMPrep() and add SW for CAMPrepObj class

  • Add generalNMF option which has no sum-to-one constraint

  • Fix bug caused by NMF::.fcnnls() and import more robust function nnls::nnls()

  • Fix bug in space median when dimenion is 2

  • Decrease Kmeans repetition times when input data has too many data points

  • Enhance simplex plot


Changes in version 1.12.2

  • Bar bax plot name fix


Changes in version 1.0.1

  • Release 3.9 Bioconductor

  • Changes in vignette.


Changes in version 2.1.0 (2019-08-18)

  • adapted readAlexandrovSignatures to read the file format used by the COSMIC mutational signatures version 3 (May 2019; Single Base Substitution/SBS signatures only)


Changes in version 1.99.3 (2013-07-25)


  • A few changes to shearwater vignette

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


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

Changes in version 1.99.2 (2013-07-11)


  • Updated CITATION

  • Added verbose option to bam2R to suppress output

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


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

Changes in version 1.99.1 (2013-06-25)


  • Using knitr for prettier vignettes

  • Including shearwater vignette


  • fixed issues with deletions in bf2Vcf()

  • makePrior() adds background on all sites

Changes in version 1.99.0 (2013-04-30)


  • New shearwater algorithm

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


Changes in version 1.21.1

  • Fix: call summary from DESeq2

  • Fix: degPlot to avoid reordering ann vector when checking if they exists.

  • Fix: degSignature to work with new version of melt.

  • Fix: degVolcano doesn’t uses ranges of 0.5 in the x axis anymore

  • Fix: degMA used always raw table, now fixed to use the right one.


Changes in version 0.12.0


  • Add isPristine()

  • Delayed subassignment now accepts a right value with dimensions that are not strictly the same as the dimensions of the selection as long as the “effective dimensions” are the same

  • Small improvement to delayed dimnames setter: atomic vectors or factors in the supplied ‘dimnames’ list are now accepted and passed thru as.character()


  • Improve show() method for DelayedArray objects (see commit 54540856)


  • Setting and getting the dimnames of a DelayedArray object or derivative now preserves the names on the dimnames

  • Some fixes related to DelayedArray objects with list array seeds (see commit 6c94eac7)


Changes in version 1.1.9 (2019-10-06)

  • Two changes making package more BioConductor compliant: o Introduction of a “Installation” and a “Session info” slot in the vinjette o Formatting change of this NEWS file.

Changes in version 1.1.8 (2019-09-12)

  • Bug fixes. True also for last version.

Changes in version 1.1.6 (2019-09-12)

  • Adding export option for the vector created by groupProbPlot

  • Correcting dColorPlot so that it can take a hex color vector as input, and

  • keep the colors.

  • Adding a test for groupProbPlot.

  • Minor bug fixes for groupProbPlot.

  • Small edits to the vinjette, to clarify that umap is preferred over tSNE and

  • that dViolins currently does not fully support plotting of CyTOF data due to

  • its sparsity.

Changes in version 1.1.5 (2019-08-07)

  • 4x speedup of the new groupProbPlot.

  • Proper citations of the MixOmics package, that the dSplsda function uses

  • heavily.

  • Bug fixes of the groupProbPlot.

Changes in version 1.1.4 (2019-07-30)

  • A brand new function is added! Here, the user can get single-cell resolution

  • on which group of two that a cell is more probable to belong to. See docs for

  • further information. Highly recommended to test!

  • Internal c++ test corrected by external contribution by Zimoun, which we are

  • most grateful for.

Changes in version 1.1.3 (2019-06-28)

  • dResidualPlot bug making colors sometimes represent the wrong group fixed.

Changes in version 1.1.2 (2019-06-28)

  • Fixing the dColorPlot and the dDensityPlot functions, so that original names

  • in character vectors and factors are correctly displayed.


Changes in version 1.19.9


  • Fixed an important bug in findRegions() that affected the end positions of the regions when maxRegionGap was supplied with a value greater than the default of 0 and the data was filtered (so position was not all TRUE in the findRegions() call). To check this scenario now there is a new unit test under tests/testthat/test-maxRegionGap.R. - The above bug went unnoticed in getRegionCoverage() and thus for regionMatrix() for the same type of situations (filtered data with a non-zero maxRegionGap). The coverage values are ok, it’s just the end positions of the regions returned by findRegions() that were incorrect and that would need to be re-computed with the fixed version. - Changed some internal tests to check bumphunter::loessByCluster() instead of bumphunter::runmedByCluster() given some issues with the second one.

Changes in version 1.19.8

  • Added a file to track changes to the package.

Changes in version 1.19.4


  • railMatrix() and loadCoverage() helper functions had an issue when the input set of regions was duplicated. This could be reproduced with

sampleFile <- c(‘SRR387777’ = ‘’) regs <- GenomicRanges::GRanges(‘chrY’, IRanges(start = c(1, 1), width = 10), strand = ‘-‘) names(regs) <- c(1:2) result <- rtracklayer::import(sampleFile, selection = regs, as = ‘RleList’)

This error affected recount and other reverse dependencies that use derfinder for processing BigWig files.

Changes in version 1.19.2


  • railMatrix() and loadCoverage() helper functions now attempt to import a BigWig file 3 times before giving up. Based on and which will make these functions more robust to occasional web access issues.


Changes in version 1.19.3

  • Added a file to track changes to the package.


Changes in version 1.19.3

  • Added a file to track changes to the package.


Changes in version 1.26.0

  • Incorporation of fast code from Constantin Ahlmann-Eltze which speeds up DESeq2 for large sample sizes (n > 100) by at least an order of magnitude. In fact the speed is now linear with number of samples whereas previously DESeq2 would scale quadratically. The critical merge commits were: c96c1c0ad43280c82403d3e6bc3501332a62e7b8 (2019-07-16) 0a47a0c750aa5c31df759a171c737d6ed782d6c2 (2019-07-30)

  • Fixed a bug where rbind() in parallel=TRUE would proliferate metadata items.

  • Updated vignette to discuss tximeta (workflow also updated to show use of tximeta instead of read counting).


Changes in version 0.99.0 (2019-09-23)

  • Submitted to Bioconductor


Changes in version 3.13.1

  • Change dba.plotPCA to use proper loading


Changes in version 1.5.6

  • Update ‘diffcyt()’ wrapper function to handle new SingleCellExperiment object structure from CATALYST.


Changes in version 1.1.1 (2019-09-27)

  • Added report execution mode with zip archive of results. Results can now be emailed from the public server.

  • Automatically fix duplicate row names.

  • Allow direct upload of metadata table to web application.

  • Cosinor now works with NA values (using discoODAs only).

  • Bug fixes.


Changes in version 0.99.1

New Features

  • None.

CHANGES IN VERSION 0.99.1 (2019-06-02)


  • None.


  • None.


  • None.


  • None.


Changes in version 2.0.0

  • Full utility for WGBS and RRBS assays implemented using sequencing.annotate(): Users can either input a) A BSseq object and model matrix from edgeR::modelMatrixMeth, or b) Output from DSS::DMLtest() or DSS::DMLtest.multiFactor(),

  • Major reconstruction of class types in S4: a S3 “annot” object is now a S4 “CpGannotated” object and a S3 “dmrcate.output” object has had its “input” and “pcutoff” slots removed, and “results” are now represented in an S4

  • Improved DMR.plot() using more detailed transcript annotation from hg19, hg38 and mm10 GeneRegionTracks from updated DMRcatedata, as well as smoothed group means (group specified via “phen.col” argument). For bisulfite sequencing assays, the CpGs argument now takes a BSseq object instead of a GRanges object

  • Extra DMR-level summary statistics including Fisher’s multiple comparison test and harmonic mean of individual CpG FDRs

  • Addition of the changeFDR() utility function that allows the re-thresholding of a “CpGannotated” object without fitting the entire model again

  • Simplification of the rmSNPandCH() function

  • Overlapping.promoters in extractRanges() are now overlapping.genes

  • All vignette examples use ExperimentHub data

  • Extra data object from DMRcatedata needed for rmSNPandCH(), extractRanges() and DMR.plot() are now in ExperimentHub

  • Removal of the “p.adjust.method” argument to dmrcate() - it is confusing since thresholding should be performed at the (cpg|sequencing).annotate level

  • Removal of the “samps” argument to DMR.plot() - it is redundant and usage can be specified by subsetting “CpGs” and “phen.col”

  • Multicore processing removed since WGBS DMRs should be able to be produced in serial in < 1 hour


Changes in version 1.5.2


  • adding importFrom(methods, is)

  • Change class() == to is()

Changes in version 1.5.1


  • Adapt to new GenomicRanges::GPo function

Changes in version 1.5.0


  • DominoEffect BioC 3.10 development version


Changes in version 3.11.2

  • ignore universe and print a waring message if users passing accidentally passing wrong input (2019-10-24, Thu) - - gene with minimal ES value (NES < 0) will be reported in core_enrichment (2019-07-31, Wed)

Changes in version 3.11.1

  • build_Anno now compatible with tibble (2019-05-28, Tue)


Changes in version 1.8.0

  • Added the downsampleBatches() function for convenient downsampling of batches.

Changes in version 1.6.0

  • Switched emptyDrops() to use Boost’s discrete_distribution for weighted sampling. This results in some minor stochastic changes to the Monte Carlo p-values. Automatically round non-integer count matrices.


Changes in version 3.28.0

  • Add head() and tail() methods for edgeR classes.

  • Remove the ‘mixed.df’ argument and add a ‘locfit.mixed’ option to ‘trend.method’ in estimateDisp() and WLEB().

  • Add two new arguments ‘large.n’ and ‘min.prop’ to filterByExpr() to allow users to change parameters previously hard-wired.

  • Remove ‘values’ and ‘col’ arguments to plotMD.DGELRT() and plotMD.ExactTest() as no longer needed because of changes to plotWithHighlights().

  • roast.DGEList() and mroast.DGEList() now pass the ‘nrot’ argument to roast.default().

  • Rename dglmStdResid() to plotMeanVar2().

  • getDispersions() is no longer exported.

  • Estimated dispersions are now numeric even if NA.

  • Bug fix to goana.DGELRT() and kegga.DGELRT() when the LRT was on more than 1 df.


Changes in version 1.4

  • modified behaviour where a p-value of 0 is found: now converts these to 10^-1 * lowest non-zero p-value

  • added new paremeter ‘legendLabels’, which allows user to use expressions in the legend label

  • added support for tibbles

  • transcriptPointSize, transcriptLabSize, transcriptLabCol, transcriptLabFace, transcriptLabhjust, and transcriptLabvjust now deprecated. Use pointSize, labSize, labCol, labFace, labhjust, and labvjust, respectively, instead

  • pointSize default changed to 2.0

  • boxedlabels now deprecated. Use boxedLabels


Changes in version 1.5.2

  • update node_label parameter in cnetplot to support selection of subset to be labeled (2019-09-27, Fri) -
  • upsetplot for gseaResult (2019-09-25, Wed) - reimplement upsetplot based on ggupset

Changes in version 1.5.1

  • gseadist for plotting logFC distribution of selected gene sets. (2019-06-25, Tue)


Changes in version 1.28.0

  • add support for Ensembl release 97/98


Changes in version 999.999

  • This NEWS file is only a placeholder. The version 999.999 does not really exist. Please read the NEWS on Github: <URL:>


Changes in version 1.11.0


  • (1.11.2) system environment variable to control localHub option for creating hub based only on previously downloaded resources

  • (1.11.5) With change in AnnotationHub. All force redownload of Hub sqlite file with refreshHub


  • (1.11.2) Fix localHub when no internet connection. The internal use of isDevel was preventing Hub creation when no internet connection. Fixed by checking connection. This code pretained to orgDb filters


Changes in version 1.13.1

  • Parameters id.col, father.col, mother.col, family.col and sex.col for FAData allow now to specify the column names for the respective content also if a data.frame is provided.


Changes in version 0.99

  • Fixing bugs and preparing for submission


Changes in version 1.5.3

  • Changed buildDataFromGraph() so that it looks for organismal annotations in keggInfo().

  • If ncbi-geneid was not available, buildDataFromGraph() would crash with 404. Now, it can use ncbi-proteinid if ncbi-geneid is missing.

  • Discovered by LY by building db for "cvi"

  • Small update on sanitise()

Changes in version 1.4.2

  • The REST KEGG service changed and modules are no longer listable by organism. FELLA now chooses modules that have at least one organismal gene. This seems equivalent to picking the modules from keggLink("genome", "module"), but the latter is slow (90s).

Changes in version 1.4.1

  • Fixed bug in vignette due to changes in biomaRt


Changes in version 1.11.2

  • Simpler handling of conditional probabilities

  • Added the exact algorithm to inst folder

Changes in version 1.11.1

  • Proper absEps handling


Changes in version 1.2.0

  • Switching to a faster version of Swish which only computes the ranks of the data once, and then re-uses this for the permutation distribution. This bypasses the addition of uniform noise per permutation and is 10x faster. Two designs which still require re-computation of ranks per permutation are the paired analysis and the general interaction analysis. Two-group, stratified two-group, and the paired interaction analysis now default to the new fast method, but the original, slower method can be used by setting fast=0 in the call to swish().

  • Adding Rcpp-based function readEDS() written by Avi Srivastava which imports the sparse counts stored in Alevin’s Efficient Data Storage (EDS) format.

  • Changed the vignette so that it (will) use a linkedTxome, as sometime the build would break if the Bioc build machine couldn’t access

  • Add ‘computeInfRV’ function. InfRV is not used in the Swish methods, only for visualization purposes in the Swish paper.

  • removed ‘samr’ from Imports, as it required source installation, moved to Suggests, for optional qvalue calculation


Changes in version 1.20.0

Bug fixes

  • In the shinyFlow app, include.area now defaults to FALSE


Changes in version 1.19.8

  • -Adding densityoverlay option to plotDens, and changing sweave to markdown


Changes in version 0.99.4 (2019-09-30)

  • responses to BioConductor review #1

Changes in version 0.99.3 (2019-09-18)

  • Submitted to BioConductor

Changes in version 0.99.2 (2019-09-18)

  • Diminishing the size of the example data, to fit all size requirements.

Changes in version 0.99.1 (2019-09-18)

  • Version change, to suit BioConductor.

Changes in version 0.9.2 (2019-09-17)

  • Formal tests included for all user functions.

  • Using specMatCalc with one color is deprecated.

Changes in version 0.9.1 (2019-09-16)

  • The name “flowSpecs” is introduced.

  • The older “theFlowSpec” is from now on deprecated.


Version: 2018-12-19 Text:

Version: 2019-03-31 Text:

Version: 2019-05-04 Text:

Version: 2019-05-07 Text:

Version: 2019-05-29 Text:

Version: 2019-08-08 Text:


Changes in version 1.2.3 (2019-07-17)

  • issue with wrong amount of tests fixed

Changes in version 1.2.2 (2019-07-16)

  • Multiple testing procedure corrected

Changes in version 1.2.1

  • Bug with wrong arguments order in plotting functions fixed


Changes in version 1.0.0

  • All GCSscore probe packages are now automatically generated from Bioconductor sources (platform design (pd) and annotation (.db) packages) by using the makeProbePackage() function from the ‘AnnotationForge’ package. These are generated and installed based on the chip-type being analyzed by the end user on an as-needed basis. NEW FEATURES

  • Initial release of R package.

  • All GCSscore probe packages are now automatically generated from Bioconductor sources (platform design (pd) and annotation (.db) packages) by using the makeProbePackage() function from the ‘AnnotationForge’ package. These are generated and installed based on the chip-type being analyzed by the end user on an as-needed basis.


Changes in version 1.5.3


  • Dollar completion for ‘GDSFile’ class.


  • dimnames() of GDSArray and GDSArraySeed is now list of all character vectors.


Changes in version 1.22.0


  • a new function unload.gdsn() to unload a GDS node from memory


  • add ‘#pragma GCC optimize(“O3”)’ to some of C++ files when GCC is used

  • add the compiler information in system.gds()

  • change the file name “vignettes/gdsfmt_vignette.Rmd” to “vignettes/gdsfmt.Rmd”, so vignette("gdsfmt") can work directly


  • avoid the segfault if the data type is not registered internally

  • use O_CLOEXEC (the close-on-exec flag) when open and create files to avoid potentially leaking file descriptors in forked processes


Changes in version 0.3.0

  • 6-01-19: Introducing GEMINI, a variational Bayesian approach to analyze pairwise CRISPR screens.

  • Note: This is a pre-release version of GEMINI.

  • Added a file to track changes to the package.

  • Minor modifications were made to prepare for repository submission.

  • 6-13-19: Incremented version number from 0.2.0 to 0.99.0 for pre-release.

  • 6-24-19: Bioconductor revision in progress. Version 0.99.9

  • Note: This is a pre-release version of GEMINI.

  • Modified documentation for all functions and added a workable vignette


Changes in version 1.9.0

  • Bugfix: Added signature( “FixedExpressionData”, i=ANY, j=missing ) for the “[” and “[[” functions

  • More indepth checking of function arguments

  • Additional unit tests


Changes in version 2.15.3

  • Add option “fastSKAT” to assocTestAggregate. Some other arguments and names of output columns for SKAT tests have also changed. This update includes code from the bigQF package ( With the addition of C code, GENESIS now requires compliation.


Changes in version 1.22.0


  • Add stackStringsFromGAlignments(). Analog to stackStringsFromBam() except that it stacks the read sequences stored in a GAlignments object instead of a BAM file.


  • Fix summarizeJunctions() error when no junctions are found and ‘genome’ is specified.


Changes in version 1.38.0


  • Small improvement to exonicParts() and intronicParts(): - When ‘’ is set to TRUE, exonicParts() now returns an additional “exonic_part” metadata column that indicates the rank of each exonic part within all the exonic parts linked to the same gene. This is for compatibility with old disjointExons(). - intronicParts() does something similar except that the additional metadata column is named “intronic_part”.


  • makeTxDbFromGRanges() and makeTxDbFromGFF() now recognize more features as transcripts, exons, or CDS (see commits 822665f8 and 6281f856)


  • Fix makeTxDbFromUCSC(…, “refGene”) for bosTau9/galGal6/panTro6/rheMac10


Changes in version 0.99.9

  • Added clutering method: Multi-channel weighted univariate clustering.

  • In function MD.Chr.zoning.Granges(), if only using one core, stop calling parallel computing.

  • Correct a bug in function MD.rank.statistic(). ANOVA requires every group has no less than 2 elements. If not, report p-value 1 directly.

  • Fixed the mal-formated NEWS file.

Changes in version 0.99.8

  • Solved problem connecting to GitHub and bioconductor git server.

Changes in version 0.99.7

  • Solved problem connecting to GitHub and bioconductor git server.

Changes in version 0.99.6

  • Solved problem connecting to GitHub and bioconductor git server.

Changes in version 0.99.5

  • Solved problem connecting to GitHub and bioconductor git server.

Changes in version 0.99.4

  • Modified R document files. + Corrected typos. + Replaceded “expression” with “activity”, because not only expression can be analyzed, but also all kinds of gene activity. + Replaced the “GenomicOZone list” with “GenomicOZone object”.

Changes in version 0.99.3

  • Replaced c(1:nrow()) into seq_len(nrow()) to avoid potential issues.

  • Modified the vignettes to avoid long lines in code chunks.

  • Renamed parameter ‘p.value.cutoff’ with ‘alpha’.

  • Renamed parameter ‘effect.size.rate’ with ‘min.effect.size’.

  • Updated .bib files. Added missing citations. Removed duplicated citations.

  • Replace all c(1:…) with seq_len().

  • Replaced the \texttt in vignettes Rmd file with a correct format using “``”.

  • Replaced the \textit in vignettes Rmd file with a correct format using “**”.

  • Adjusted the image size in vignettes Rmd file.

  • Updated R documents.

Changes in version 0.99.2

  • Submitted on 2019-08-18

  • Added joemsong as a coresponding auther to the submission.

Changes in version 0.99.1

  • Submitted on 2019-08-17

  • Reformatted the package for Bioconductor submission.

Changes in version 0.99.0

  • Submitted on 2019-08-17

  • Packed the completed package.


Changes in version 1.38.0


  • GPos objects now exist in 2 flavors: UnstitchedGPos and StitchedGPos GPos is now a virtual class with 2 concrete subclasses: UnstitchedGPos and StitchedGPos. In an UnstitchedGPos instance the positions are stored as an integer vector. In a StitchedGPos instance, like with old GPos instances, the positions are stored as an IRanges object where each range represents a run of consecutive positions. This is analog to the IPos/UnstitchedIPos/StitchedIPos situation. See ?GPos for more information. Old serialized GPos instances can be converted to StitchedGPos instances with updateObject().

  • GPos objects now can hold names

  • Coercion to GPos now propagates the names

  • Add GRangesFactor class (Factor derivative). See ?GRangesFactor


  • Export from_GPos_to_GRanges()

  • Some reorgnization of the GenomicRangesList hierarchy (see commit f988a5a9).

  • Swap order of arguments ‘seqlengths’ and ‘seqinfo’ of the GRanges() constructor so now the latter comes before the former.


  • Remove findOverlaps, seqnames, and seqinfo<- methods for RangedData objects. These methods were deprecated in BioC 3.8 and defunct in BioC 3.9.


  • Coercion from RangesList to GRanges is more robust to seqlevel differences

  • Fix bug in isSmallGenome() (introduced by change in sum() in R >= 3.5)


Changes in version 1.10.0


  • Added support to latest release 3.0 of gnomAD MAF data, stored in the package MafDb.gnomAD.r3.0.GRCh38.

  • Individual allele frequencies can be now retrieved from MafDb.* packages when ‘ref’ and ‘alt’ arguments are given to the functions ‘gscores()’ and ‘score()’. See manual pages and vignette for further details.

  • NonSNRs are now searched giving the argument type=”equal” to findOverlaps(). This means that only scores from exact matches to nonSNRs are returned.


  • Bugfix on the ‘getGScores(‘) function that precluded accessing the files downloaded by the AnnotationHub

  • Bugfix in accessing MAF values from nonSNVs when multiallelic variants are stored in different records from the VCF file.


Changes in version 1.99.1

  • bug fixed of geom_hilight for tree$edge.length = NULL (2019-10-16, Wed) -
  • fortify method for igraph (only work with tree graph) (2019-09-28, Sat) - ggdensitree (2019-09-11, Wed) - - -

Changes in version 1.99.0

  • prepare for ggtree v=2.0.0

Changes in version 1.17.5

  • fortify methods for hierarchical clustering objects, including agnes, diana and twins (2019-08-30, Fri) - now geom_hilight supports unrooted and daylight layouts (2019-08-28, Wed) - by calling geom_hilight_encircle - update geom_motif according to the change of gggenes and allow labeling genes (2019-08-27, Tue) -
  • re-implement geom_strip with more robust support of labelling strip, either input taxa using name or id. - support phylog defined in ade4 package (2019-08-14, Wed) -

Changes in version 1.17.4

  • now geom_cladelabel supports unrooted and daylight layouts (2019-08-14, Wed) - by integrating geom_cladelabel2 - defined nodelab method for ggtree to convert node number to label (2019-08-09, Fir) - redefined nodeid as S3 generic in tidytree v=0.2.6 - change the original function as a method for ggtree - move the nodeid function for tree object to treeio - defunct gzoom function - introduce rootnode parameter in geom_tree with default = TRUE and behave as previous version (2019-08-08, Thu) - the invisible root to itself line segment have advantage for the number of line segments is consistent with the number of nodes. - if rootnode = FALSE, there will be no line segment of root to itself. - extend gheatmap to support collapsed node (2019-08-06, Tue) - - support hclust and dendrogram (2019-07-31, Wed)

Changes in version 1.17.3

  • remove re-export treeio parser function, user now need to load treeio explictly (2019-07-24, Wed) - export layout_circular, layout_fan and layout_rectangular - layout_dendrogram and theme_dendrogram - - scale_x_range for adding second x-axis for geom_range (2019-07-23, Tue) - change branch.length parameter to center for geom_range

Changes in version 1.17.2

  • extend expand according to the change of collapse (2019-07-11, Thu)
  • mode parameter in collapse - geom_tiplab now works with ‘circular’ and ‘fan’ layouts (2019-07-05, Fri) - geom_inset for adding subplots to specific nodes (see also the inset function introduced in v=1.3.8)

Changes in version 1.17.1

  • facet_data to extract data used in facet_plot or geom_facet (2019-07-02, Tue) - continuous parameter in geom_tree to to continuous color edge from parent to child (2019-09-25, Tue) - - root.position parameter for fortify and ggtree (2019-05-27, Mon) - geom_facet, a geom layer version of facet_plot (2019-05-23, Thu) - update scale_x_ggtree, now we can use gheatmap() + scale_x_ggtree() (2019-05-22, Wed) - extend xlim_expand to work with ggplot2 (2019-05-20, Tue) - - add legend_title variable in gheatmap (2019-05-16, Thu)


Changes in version 1.1.3

  • Fix module capatiblality issue.

Changes in version 1.1.2

  • Update plot format.

Changes in version 1.1.1

  • Fix several conditions that may cause error in tree construction.


Changes in version 1.5.2


  • update GO-graph (version 07-Oct-2019)

Changes in version 1.5.1


  • add refine() function to restrict results from enrichment analysis to more specific categories


Changes in version 1.31.1 (2019-10-24)

  • Updated all pathway data.

  • Removed HumanCyc pathways (database now requires subscription).


Changes in version 0.99.4

  • Replaced parallel::mclapply() with BiocParallel::bplapply()

  • Updated stop/warning/message functions. Testing if sampling timepoints are named correctly.


Changes in version 1.6.0

  • New function evalTypeIError for type I error rate evalution by sample permutation: - evaluation of one or more enrichment methods on one or more expression datasets - support for splitting permutations into blocks of defined size, and invoking parallel evaluation of the partitions

  • New function evalRandomGS for evaluation of random gene sets: - estimates proportion of rejected null hypotheses (= fraction of significant gene sets) of an enrichment method when applied to random gene sets of defined size - evaluation of one or more enrichment methods on an expression dataset of choice

  • New argument method to the evalRelevance function for the evaluation of phenotype relevance of gene set rankings, choices include: - “wsum”: computes a weighted sum of the relevance scores (default), - “auc”: performs a ROC/AUC analysis based on the ROCR package, - “cor”: computes a standard correlation measure such as Spearman’s rank correlation, - a user-defined function for customized behaviors.

  • New function metaFC for summarizing fold changes of individual datasets across a compendium of expression datasets

  • New functions plotDEDistribution and plotNrSamples for exploring differential expression and sample size across a compendium of expression datasets

  • Extended support for user-defined benchmarking inputs including simplified plug-in of user-defined enrichment methods (thanks to Marcel Ramos @LiNk-NY)


Changes in version 1.34


  • Bugfix to handle when parallel::detectCores() returns NA instead of an integer number of cores, which may happen when running GSVA in a docker container. Bug reporting and pull request fix thanks to Aaron (

  • Bugfix to handle when arguments ‘method=”ssgsea”’ and ‘tau=0’. Bug reporting thanks to Lena Morill (


Changes in version 1.17.1

  • fixed a bug of selecting chromosomes.


Changes in version 1.29.1


  • Exposed the possibility to specify width and distance for feather (arrowBar) in AnnotationTrack class


  • Fixed issue with subseq function for ReferenceSequenceTrack

  • Changed the visualized position of tickmarks, and values in DataTrack => align all to + 0.5 position, which matches the SequenceTrack and AnnotationTrack visualization

  • Changed the check for transparency support in currently opened device supportsAlpha, point moved from center to the left bottom corner


Changes in version 1.14.0


  • Add coercions from TENxMatrix (or TENxMatrixSeed) to dgCMatrix


  • h5mread() argument ‘starts’ now defaults to NULL


  • h5mread() now supports datasets with contiguous layout (i.e. not chunked)


Changes in version 1.19.1 (2019-10-24)


  • Fixed minor bug.


Changes in version 1.19.0

  • Drop forced strand conversion to ‘+’ and makeGRanges with add strand as ‘*’ if none was found.


Changes in version 1.22.0

  • change the file name “vignettes/HIBAG_Tutorial.Rmd” to “vignettes/HIBAG.Rmd”, so vignette("HIBAG") can work directly


Changes in version 0.99.11 (2019-09-10)

  • Update the CITATION after the paper has been accepted by PeerJ

Changes in version 0.99.10 (2019-07-24)

  • Fix the issues commented by the Bioconductor reviewer

Changes in version 0.99.9 (2019-07-24)

  • Fix the issues commented by the Bioconductor reviewer

Changes in version 0.99.8 (2019-06-22)

  • Remove git tracking .o and .dll files

Changes in version 0.99.7 (2019-06-22)

  • Remove git tracking .o and .dll files

Changes in version 0.99.6 (2019-06-22)

  • Remove git tracking .o and .dll files

Changes in version 0.99.5 (2019-06-22)

  • Remove git tracking .o and .dll files

Changes in version 0.99.4 (2019-06-22)

  • Remove git tracking .o and .dll files

Changes in version 0.99.3 (2019-06-21)

  • Fix the issues commented by the Bioconductor reviewer

Changes in version 0.99.2 (2019-06-05)

  • Remove pmsignature dependency

Changes in version 0.99.1 (2019-06-04)

  • Submitted to Bioconductor


Changes in version 2.1.1 (2019-05-17)

  • Adding function mgi_from_sif, which allows to create a pathways object from SIF + ATT files.


Changes in version 1.3.1

  • Added the citation file.


Changes in version 1.3

  • Changes in version 1.3.3
    • Fix sn error introduced in version 1.3.2 where hpaVisPatho plotted incorrectly.
    • Added a vignette with codes for figures in the HPAanalyze manuscript.
  • Changes in version 1.3.2
    • To reduce dependency, hpaVis now use gridExtra for multiple plots instead of cowplot
    • Removed dependency on reshape2
  • Changes in version 1.3.1
    • hpaExport is now supporting csv and tsv.
    • Support for JSON export is added via vignette.
    • Fix the error where hpaXmlGet give an error when curl is not installed.
    • Most functions with now take both HGNC gene names and ensemble ids.
    • hpaVisSubcell now allows user to choose reliability scores.
    • Removed dependency on magrittr
  • Changes in version 1.3.0
    • Starting devel for Bioconductor 3.10


Changes in version 1.10.0

New features

  • ggplotCounts gains a new parameter, labels_repel, to control the placement of the different labels in the plot - this can be useful when a large number of samples is available

Bug fixes

  • Fixed an error in the initialization of the app due to a new behavior introduced by shinyAce in version >= 0.4.0 - occurred in the same way as for pcaExplorer

Other notes

  • Better class checks via is(…) as per BiocCheck suggestion


Changes in version 0.99.2

  • added consistent ticks and limits to IDR plot functions

  • updated function documentation

Changes in version 0.99.1

  • added reference to Li et al. paper

  • added diagnostics plots

  • changed rank order

  • added IDR1D functionality

  • fixed local / global IDR issue

Changes in version 0.99.0

  • initial release


Changes in version 0.99.0 (2019-07-15)

  • Submitted to Bioconductor


Changes in version 1.6


  • bam (Alignment) tracks now supported

  • Motif logos now displayed by clicking on appropriately configured tracks

  • pkgdown website (vignettes and man pages) at

  • more genomes supported: hg38, hg19, hg18, mm10, bostau8, canfam3, ce11, danrer10, danrer11, dm6, gorgor4, panpan2, pantro4, pfal3d7, rn6, saccer3, susscr11, tair10

  • R commands sent to the browser now return only when the Javascript command completes

  • built with version 2.3.2 of igv.js


Changes in version 1.17.3

  • CHANGES * bugfix in subset.immunoMeta

Changes in version 1.17.2

  • NEW FEATURES * introducing immunoMeta-class on meta-clustering results to buildup and annotate a hierachical population/sub-populaton tree

  • CHANGES * trail of automated annotation of meta-clusters using scatter-clustering is removed. The approach does not work in a usefull manner. Instead the immunoMeta-class is introduced providing methods for a manual annotation of meta-cluster. See man-pages and vignette for more details. * set.seed is removed from clustering routines. To obtain reproducable results with cell.process function set.seed has to set explicit before.

Changes in version 1.17.1

  • CHANGES * minor bugfixes and code cleaning * minor additional options for immunoClust.plot/splom


Changes in version 1.1.4 (2019-10-29)

  • Fix reading of input annotations when some are only digits to be properly read as characters.

  • Added checks that HMM_report_by option is compatible with analysis_mode option. If not, change it automatically.

  • Fix reading of bayesian filtered HMM results in add_to_seurat after previous version changes to keep CNV ids and states scale.

Changes in version 1.1.3 (2019-09-16)

  • Fix to reload checks on HMM steps. +Added new smoothing method, ‘coordinates”, that smooths the per cell data using a window based on a base pairs distance (around 10.000.000 seems to be a good start for the window size) to the current gene. As the hspike does not model gene distances/positions on a chromosome at this time, the HMM i6 mode is not compatible with this smoothing method and an error will be returned if both try to be used together.

  • Added a bp distance tolerance to “merge” top CNVs that are actually the same CNV in different subclusters in add_to_seurat method.

  • Removed the top any type of CNV field, as it is redundant to top loss and top dupli.

  • Added text output of identified top CNVs as they the base pair tolerance aggregates some compared to the original HMM output.

  • Added an argument “up_to_step” to stop infercnv::run() after a given step.

  • Fix contents of @options field in infercnv_obj to store non default run time arguments in the same form as object creation arguments.

  • Update so that HMM predictions outputs have the analysis_mode in their name and do not get overwritten when using different modes. Can also know which pairs of file to reload together now.

  • Update add_to_seurat so that it checks what analysis_mode was used in the run based on the @options field to reload the matching HMM predictions or Bayesian Network filtered predictions.

  • Updated “subclustering” method for sample mode so that @tumor_subclusters$subclusters indices have the cell names attached to be able to map back in add_to_seurat.

  • Allow HMM steps to be resumed if needed even if steps 20/21 are done.

Changes in version 1.1.2 (2019-07-08)

  • Added method to write table of wide array of predicted features from HMM results to file or add them as to a Seurat object if one is provided.

  • Overhaul of save/reload system to store non default arguments and keep track of relevant options at each step when trying to reload backups. Also check for input counts matrix identity with reloaded one (hash at object creation time).

  • Added linking of image() option useRaster to run() and plot_cnv() to be able to enable by default, speeding up plotting significantly.

Changes in version 1.1.1 (2019-05-20)

  • Added method to sample an infercnv object to a given number of cells, or at a given frequency, per annotation group. This is to make it easy to plot figures where all annotations groups have the same overall height, as well as downsample very large datasets that would otherwise take too long to plot (while still running the analysis on the full data)

  • Added method to plot each annotation group to a different figure and combine with sampling. Mostly intended to split data for larger datasets.

  • Added support for output_format option within run() to link to plot_cnv() to support only writting text outputs during the analysis.

Changes in version 1.0.4 (2019-09-16)

  • Fix check that contig to cluster by was found when specified.

  • Added support to plot_cnv for cell groups with exactly 2 cells.

  • Fix which input file type is checked.

  • Made it so that plot_cnv recalculates clustering automatically if non null ref_contig argument is provided.

  • Fix for plot_cnv() when providing multiple ref_contigs and cluster_by_group is False.

  • Fix only 1/n genes being taken into account when using n ref_contig in plot_cnv.

  • Fix error in file creation when using multiple ref_contig and cluster_by_groups=FALSE in plot_cnv.

  • Bayesian filtering now preserves CNV ids in outputs

Changes in version 1.0.3 (2019-07-05)

  • Fix missing dendrograms in text output when drawing figures.

  • Fix path to save object to when splitting references.

  • Fix file name creation when using num_ref_groups option.

  • Fix reference cells indices returned from method that splits references in num_ref_groups when references are not sorted and at the beginning of the matrix.

  • Fix to support of data.frame as input type for counts matrix.

Changes in version 1.0.2 (2019-05-21)

  • Reduce peak memory usage.

  • Fix to subclusters definition when using a sparse matrix and a non random trees method with no references.

Changes in version 1.0.1 (2019-05-20)

  • Improved when the clustering is defined for groups when running in sample mode.

  • Fixed support for NA to be understood as an output_format value to plot_cnv() in case a user only wants to generate the text outputs and not the plot.

  • Fix ordering of cells and color bars on the heatmap and text outputs when cells are not sorted in the same order in the input matrix and the annotation file.

  • Fix to (sub)cluster definition when a group only has 1 cell.

  • Fix plot_cnv() to handle observations groups with only 1 cell (that can’t be hierarchically clustered), a single reference group when no references are not clusterd, and a single reference group with a single cell.


Changes in version 1.17.3

  • update documentation.

Changes in version 1.17.2

  • add citation of cleanUpdTSeq.


Changes in version 2.20.0


  • IPos objects now exist in 2 flavors: UnstitchedIPos and StitchedIPos IPos is now a virtual class with 2 concrete subclasses: UnstitchedIPos and StitchedIPos. In an UnstitchedIPos instance the positions are stored as an integer vector. In a StitchedIPos instance, like with old IPos instances, the positions are stored as an IRanges object where each range represents a run of consecutive positions. See ?IPos for more information. Old serialized IPos instances need to be converted to StitchedIPos instances with updateObject().

  • IPos objects now can hold names

  • The IRanges() and IPos() constructors now accept user-supplied metadata columns

  • Add grep(), startsWith() and endsWith() methods for CharacterList objects


  • now propagates the metadata columns

  • Move splitAsList() to the S4Vector package

  • Move S4 class “atomic” from the S4Vector package

  • No longer export %in% (was a leftover from an older time when the package was defining an %in% method)


  • After being deprecated in BioC 3.9, the following RangedData methods are now defunct: findOverlaps, rownames<-, colnames<-, columnMetadata, columnMetadata<-, c, rbind, as.env,, and coercion from RangedData to DataFrame.

  • Remove the following RangedData methods: - score, score<-, lapply, within, countOverlaps; - coercions from list, data.frame, DataTable, Rle, RleList, RleViewsList, IntegerRanges, or IntegerRangesList to RangedData. These methods were deprecated in BioC 3.8 and defunct in BioC 3.9.


  • Fix integer overflow issue in end() setter for IRanges objects.


Changes in version 1.5.13

  • Order features selected in heat map selectize from top to bottom.

Changes in version 1.5.12

  • Support gene list input from aceEditor and fileInput.

Changes in version 1.5.11

  • Rename isColorMapCompatible to checkColormapCompatibility.

  • Fix graceful server side handling of checkColormapCompatibility.

  • Update documentation about panel organisation in vignette.

Changes in version 1.5.10

  • Fix test to provide a non-empty selection to custom plot function.

Changes in version 1.5.9

  • Introduce Bugs Easter egg.

Changes in version 1.5.8

  • Substitute deprecated scater::normalize by logNormCounts.

Changes in version 1.5.7

  • Simplify protection of redDimPlotDefaults against empty reducedDims.

  • Fix to declare all panel types not available.

Changes in version 1.5.6

  • Updates following deprecation of isSpike and sizeFactorNames.

Changes in version 1.5.5

  • Add modeEmpty().

  • Support zero-row initialPanels argument.

Changes in version 1.5.4

  • Added support for file upload with server re-initialization.

  • Moved observers to separate file. Exclude from code coverage.

  • Updating calls to ReprocessedAllenData() to load only tophat_counts assay.

Changes in version 1.5.3

  • Use ReprocessedAllenData() following the deprecation of data(allen).

Changes in version 1.5.2

  • Minor doc fix..

  • Do not allow duplicated values in Name field of initialPanels.

  • Downsample points randomly.

Changes in version 1.5.1

  • Fix report of table links.

Changes in version 1.5.0

  • Bioconductor release.


Changes in version 1.7.2 (2019-10-18)

  • Update type: Major.

  • analyzeIUPred2A() for analyzing intrincially disordered regions (and binding sites therein) was introduced. To enable this the following changes were also made: * analyzeNetSurfP2() was extended to also create the idr_type column in the result * analyzeSwitchConsequences() was extended to handle idr_type. Also it was upgrated to handle large differences in IDR lengths. * The data included in the “exampleSwitchListAnalyzed” object was updated to include the result of an IUPred2A analysis (instead of the NetSurfP2 analysis) * The build in data file for analysis of NetSurfP-2 in relation to exampleSwitchListIntermediary was replaced by the corresponding data for the IUPred2A analysis. * switchPlotTranscript() (which is used by switchPlot() internally) was extended to also handle IDR types * the switchPlot() layout was re-optimied for the new annotation. * isoformSwitchAnalysisPart2() was updated to also handle IUPred2A input. * The vignette was updated accordingly.

  • switchPlotTranscript() (and thereby also switchPlot) now use the annotationImportance in a much nicer way. Instead of removing the annotation (which could cause problems when comparing computational analysis to visual output) it now uses annotationImportance to plot the data as layers with the most important on top - meaning no annotation is skipped.

  • switchPlotGeneExp() was updated to follow the condition coloring used by switchPlotIsoExp() and switchPlotIsoUsage() when used by the switchPlot() function.

  • Corrected a bug in switPlot() which caused the interpretation of the “increased/decreased usage” added to the plot to be the min instead of max of the supplied alphas.

  • Corrected a bug in analyzeSwitchConsequences() that could cause the “domain_length” consequnce type to give wrong results. Now the ‘domain_length’ test transcripts for differences in the length of overlapping domains of the same type (same hmm_name)

  • isoformSwitchAnalysisPart2() now also uses n=Inf to create all plots (NA have same function for backward compatability).

  • importRdata now ensures the order of columns in the designmatrix is always.

  • All functions for importing external analysis, which supports multiple files, now automatically remove duplicated interies.

  • The extractExpressionMatrix function was depreciated.

  • All function documentation was spell-checked.

  • Various documentation improvements.

  • Error message improvements.

Changes in version 1.7.1 (2019-07-19)

  • Update type: Minor.

  • Version bump due to Bioconductor release.

  • Updated NEWS layout in accordance with Bioconductor guidelines.

  • switchPlotTranscript() was extended to also indicate increased/decreased/unchanged isoform usage making interpretation easier. This also required switchPlotTranscript() and switchPlot() was updated with extra arguments to control this behaviour. The switchPlotTranscript() function was furthermore updated to also indicate significance (indated by asterisks) and size (dIF) when used alone (aka not from within switchPlots) making it a good alternative to the switchPlot.

  • switchPlotGeneExp(), switchPlotIsoExp(), switchPlotIsoUsage() was prettyfied and now also show the name of the gene plotted.

  • importRdata() and importGTF() now also supports import of RefSeq GFF files (downloaded from, see FAQ in vignette). This should increase ease of usage for a long range of species not in the Ensembl catalogue.

  • importRdata() * Now also removes non-exsisting introns from annotation even when it is supplied as a GRange (previously only done for GTF files). * No longer removes isoforms with NA as biotypes when removeTECgenes = TRUE. * Was extended to better handle gene_names when novelt transcripts are predicted. Specificallt if there are NA in the gene_name column (e.g. like done by StringTie) these are automatically assigned the same gene name as the other isoforms from the same gene_id (only for cases where a single gene_name is associated to the gene_id).

  • isoformSwitchTestDEXSeq() was updated to: * Better handle rare design setups that could cause an error to occure. * Now handle analysis of data with some isoforms only analyzed in a subset of comparisons

  • The extractSwitchSummary() was extended to also print number of switches.

  • A bug was fixed in extractSequence() which cased a fail when CDS sequences with multiple stop codons where annotated

  • A bug was fiexed which caused extractSplicingSummary() to only return the summary of splicing types with more than “minEventsForPlotting” events.

  • analyzeNetSurfP2() was updated to handle multiple files due to recent restrictions on the number of sequences one can upload to the webserver.

  • switchPlotTopSwitches() and extractTopSwitches() now uses n = Inf to to output all (although internally NA is converted to Inf for backward compatability).

  • subsetSwitchAnalyzeRlist() was improved to be more stable to edgecase sitiuations.

  • isoformToGeneExp() was improved * To be more userfriendly. * To directly support annotation stored in a GTF file (which it itself imports into R). * To directly support switchAnalyzeRlists.

  • analyzePFAM() was updated to be more robust to edge usecases

  • Improved error messages in mutliple function.

  • Various documentation updates.

  • Various stability updates.


Changes in version 1.20.0

  • release as part of Bioconductor 3.10

Changes in version 1.19.1

  • removed change history from package vignette for easier maintenance

Changes in version 1.19.0

  • new branch for Bioconductor 3.10 devel


Changes in version 1.27.4

  • Fix bugs in vignette

  • Improvements for notes and warnings in R cmd check

Changes in version 1.27.3

  • Improvement for plot_pathway_overall function

Changes in version 1.27.2

  • Fix bugs in convertId function, which was caused by the updates of biomaRt package

Changes in version 1.27.1

  • Fix bugs in download_KEGGfile function, which was caused by the updates of KEGG web site.

  • New function: plot_pathway_overall function to plot gene expression in pathway level.

  • Improvement for documents and examples.


Changes in version 0.99.55 (2019-10-09)

  • Several minor bug fixes and enhancements and xgrid/ygrid added to classification plots Further versions

  • MAC_OS alignment tools support

  • Incorporation of RUV to batch effect methods

Changes in version 0.99.51 (2019-08-19)

  • New method web platform added (targetValidation) to retrieve the diseases in the DEGsToDiseases function

Changes in version 0.99.42

  • dataPlots genesBoxplot mode improvements

Changes in version 0.99.31 (2019-07-17)

  • Best tunning parameters for SVM functions

Changes in version 0.99.30 (2019-06-05)

  • Initial release with Bioconductor

  • Alignment functions only works on Unix system (For now)

  • The rest of the pipeline is completely functional for all the OS including windows and MAC_OS


Changes in version 3.42.0

  • New head() and tail() methods for all limma data classes.

  • New unique() and subsetting methods for TestResults objects. Previously a subsetted TestResults object became an ordinary numeric matrix, but now the TestResults class is preserved. Single index subsetting is also allowed but produces a numeric vector.

  • roast() and mroast() now use less memory. Memory usage now remains bounded regardless of the number of rotations used. Both functions are faster than before when approx.zscore=TRUE. A new argument legacy is added to allow users to turn these improvements off if they wish to reproduce numerical results from limma 3.40.0 exactly. The default number of rotations nrot is increased from 999 to 1999. A bug has been fixed for roast() and mroast() when index is a character vector of geneids or rownames. Previously this usage failed.

  • Complete rewrite of zscoreT(), which is now somewhat faster and offer two new options for the normalizing transformation. The new argument method indicates which transformation is used when approx=TRUE. The default approximation method is changed from “hill” to “bailey”. zscoreT() now allows NA values when approx=TRUE and works correctly for all valid df values. Previously approx=TRUE returned NA results for df infinite or <= 0.05. A simple robust approximation from Wallace (1959) has been introduced to handle very large or very small df values. Previously approx=FALSE treated any df greater than 10000 as infinite; this threshold is now raised to 1e300.

  • tZScore() is slightly faster.

  • New argument gene.weights for fry() so as to match the arguments and behavior of mroast(). Previously gene weights could be input to fry() only through the index argument. fry’s mixed p-values now take account of gene weights. Previously gene weights were not used in fry’s mixed p-value calculation.

  • Add arguments block, correlation and weights to voom() and remove the ... argument.

  • Update the arguments of voomWithQualityWeights() to match the revisions to arrayWeights() in limma 3.40.0. Add new argument

  • New arguments xlab, ylab and main for plotFB(). The default plot title now includes the column name from the data object. Default for pch increased to 0.3.

  • plotWithHighlights and plotMD.MArrayLM now gives special treatment to the case that status is a TestResults object.

  • Update Yoruba case study in User’s Guide to call voom() and duplicateCorrelation() twice each instead of once.

  • Update Users Guide: update Rsubread reference, correct remarks about prior distribution for 1/sigma^2 in Section 13.2 and rerun the Yoruba and Pasilla case studies.

  • Use “RNA-seq” and “ChIP-seq” consistently in the documentation instead of “RNA-Seq” and “ChIP-Seq”.

  • All uses of the approx() function now set ties=list("ordered",mean), except for fitFDistRobustly() which uses ties=mean. The change was prompted by a change in R 3.6.0 whereby using the default for ties generates a warning message whenever ties are present in x. The new code gives the same results but is very slightly faster and avoids the warning message. limma now depends on R >= 3.6.0 because of this change.

  • Fix bug in barcodeplot() when index or index2 are character vectors.


Changes in version 0.99.2 (2019-09-30)

  • Modify behaviour when SummarizedExperiment object used as input

  • Use SummarizedExperiment object in vignettes

  • Add description for the vignettes figure

  • Change examples in manual for lioness function

Changes in version 0.99.1 (2019-09-05)

  • Bug fixed for matrix without column names

  • Accept SummarizedExperiment object as input

Changes in version 0.99.0 (2019-08-19)

  • Submitted to Bioconductor


Changes in version 1.99.2

  • Breaking changes: changed the core object to LipidomicsExperiment.

  • Added support for both targeted and untargeted lipidomics analysis.

  • lipidr can accept numerical matrix as input.

  • Added integration with Metabolomics Workbench API for enable data mining.


Changes in version 0.99.15 (2019-08-05)

  • Add value to categorical plots.

  • Adding another dependency required by bioconductor MacOS automated build/test

Changes in version 0.99.14 (2019-07-31)

  • Adding two more dependencies required by bioconductor MacOS automated build/test

Changes in version 0.99.13 (2019-07-31)

  • Iterations for addition to bioconductor: Add back in license file and small changes to coding sections of vignette.

  • Modifications to man page to include new option.

Changes in version 0.99.12 (2019-07-26)

  • Add new option to set the max number of features shown in heatmap.

  • Fix heatmap to include all rows of significant values for the top N features instead of only including the rows after finding the top N features.

Changes in version 0.99.11 (2019-07-24)

  • Update demo to data from HMP2 (provided by Himel).

Changes in version 0.99.10 (2019-07-19)

  • Small modifications to documentation to update dependency install notes to match bioconductor.

Changes in version 0.99.9 (2019-07-18)

  • Add dependency to namespace for automated tests.

Changes in version 0.99.8 (2019-07-18)

  • Add one more dependency for bioconductor MacOS build tests

Changes in version 0.99.7 (2019-07-17)

  • Change file paths to relative to package for windows tests.

Changes in version 0.99.6 (2019-07-17)

  • Fix format of R sections in vignette to pass tests.

Changes in version 0.99.5 (2019-07-17)

  • Update R sections of vignette format.

  • Change test paths for windows.

Changes in version 0.99.4 (2019-07-17)

  • Update required R version.

  • Modifications in vignette format for bioconductor build.

Changes in version 0.99.3 (2019-07-17)

  • Modifications to package based on feedback from bioconductor review (additions to description, notes on data files, update testing to testthat, condensing vignette sections and updating install to bioconductor method, remove tests for packages, use seq_len and lapply)

Changes in version 0.99.2 (2019-06-27)

  • Show top N features in heatmap instead of top N associations

Changes in version 0.99.1 (2019-06-05)

  • Fix plots to allow for NAs in values

Changes in version 0.99.0 (2019-05-24)

  • Only show the top 50 associations in the heatmaps

  • Use static heatmap plot colors

  • In boxplots, use angle for x axis text for long text strings (if any in set is over 5 chars)

  • For larger y axis labels reduce the font size (if over 15 chars)

  • Add Ns to plots in annotation for continuous and x axis label for categorical

Changes in version 0.3.0 (2019-05-20)

  • Plots now show normalized/filtered/transformed data

  • Package modifications for submission to bioconductor

Changes in version 0.2.3 (2018-12-20)

  • Move filtering to after normalization

  • Updates to barplots

Changes in version 0.2.2 (2018-11-15)

  • Fix issue with single column in visualizations (Thanks, sma!)

  • Add hash to dependencies

  • Change output column names to match data.frame names

  • Add options to bypass plotting

  • Add crossed random effects for LM using lme4 and lmerTest

  • Fix ZICP fitting errors

  • Add stderr to results

  • Rotate heatmap column names by 45 degrees

Changes in version 0.2.1 (2018-10-10)

  • Update read/slicing to support input files with a single feature.

Changes in version 0.2.0 (2018-10-09)

  • Group boxplots/scatter plots by metadata name.

  • Replace ggsave with pdf to print heatmap/plots to resolve ggsave Rplot.pdf issue.

  • Add tryCatch to allow for error in heatmap but still print other plots.

  • Allow data/metadata inputs to be paths to files or data.frame.

  • Return fit data from maaslin2 function.

  • Set na.action default in model fit to na.exclude.

Changes in version 0.1.0 (2018-09-27)

  • Initial tagged release.


Changes in version 0.99.0 (2018-11-14)

  • Not submitted o GUI interface o Sort o Statistics o Graphics


Changes in version 2.2.0


  • survGroup, mafSurvGroup - Predict genes/genesets associated with survival. Issue: #396

  • New argument altered in oncoplot to plot top genes based on CNV or mutation. Default is FALSE. Issue: #405


  • oncotate - Oncotator is no longer supported by Broad. Issue: #403 #384 #381

  • findPathways argument in somaticInteractions function has been deprecated


  • Signature analysis has been modified to be more flexible. It now consits of three functions namely:

  • estimateSignatures - which measures cophenetic correlation metric (a measure of goodness of fit) for a range of values

  • plotCophenetic - which draws an elbow plot of cophenetic correlation metric from estimateSignatures and helps to decide an optimal number of signature (n).

  • extractSignatures - which then extracts final n signatures

  • compareSignatures now has two databases of known signatures. Classic 30 signatures and newer 67 SBS signatures from COSMIC.


  • gisticChromPlot bug fix. Issue: #392

  • annovarToMaf bug fix for results without exonic variants. Issue: #388

  • Avoid conflict with plotly::layout with graphcis::layout. Issue: #387 #202

  • Fix side-bar heights in Oncoplot with copy-number data. Issue: #383

  • Update y-axis label for tcgaCompare plot. Issue: #366

  • annovarToMaf annotating variants with MNPs. Issue: #335


Changes in version 1.4.3

  • Remove bugs when perform enrichment analysis based on use-defined gene sets.

  • Prioritize NormalizeBeta.

  • Customize KEGG pathways (04***).

Changes in version 1.4.1

  • Prioritize many functions.


Changes in version 1.11.7 (2019-10-25)


  • Fixed errors in ‘rowStats()’ and ‘colStats()’ when calculating group statistics over minor dimensions

Changes in version 1.11.6 (2019-10-23)


  • Added ‘locmax()’ function for finding local maxima

  • Added ‘binvec()’ function for binning vectors

Changes in version 1.11.5 (2019-10-13)


  • Exposed ‘chunk_apply()’ for applying functions over parallelized chunks of vectors and matrices

Changes in version 1.11.4 (2019-10-13)


  • Added ‘rowStats()’ and ‘colStats()’ methods for chunk-applying grouped summary statistics over the rows and columns of matrices


  • Family of ‘apply()’ and ‘lapply()’ methods now attempt to respect the object’s ‘chunksize()’

  • Added getOption(‘matter.default.chunksize’) for setting default chunksize for matter objects

Changes in version 1.11.3


  • Faster subsetting of matter-backed ALTREP objects

  • Updated ‘bsearch()’ to return the closest match when tol > 0

  • Added getOption(‘matter.dump.dir’) to control where temporary files are stored for matter objects

Changes in version 1.11.2


  • Coercing to native R types now returns an ALTREP representation for most ‘matter’ objects

  • Use ‘as.altrep()’ method to coerce an existing ‘matter’ object to ALTREP or to coerce native R types to ‘matter’-backed out-of-memory ALTREP objects

  • ALTREP coercion can be controlled by new options: getOption(‘matter.coerce.altrep’) getOption(‘matter.coerce.altrep.list’) getOption(‘matter.wrap.altrep’)

  • See ?matter-options for details


  • The ‘show()’ method for ‘matter’ objects now prints a preview of the data head

  • Printing of data can be controlled with new options getOption(‘’) and getOption(‘’)

Changes in version 1.11.1


  • Added ‘stream_stat’ class for streaming statistics with functions s_mean(), s_var(), s_sd(), etc.


Changes in version 0.99.3

  • The latest one.

Changes in version 0.99.2

  • Update package to build NAMESPACE with roxygen and use seq_len() in MEB function.

Changes in version 0.99.1

  • Update package.

Changes in version 0.99.0

  • Update package to transform data format so that the data inputs and outputs are consistent with standard Bioconductor representations such as SummarizedExperiment.


Changes in version 1.14.1

  • MS_keggNetwork returns interaction subtype (e.g. activation) instead of type (e.g. PPrel). Thank you Shilpa Harshan for noticing this!


Changes in version 1.1.4 (2019-07-12)

  • Improved documentation of control samples in design.

Changes in version 1.1.3 (2019-05-13)

  • When parameter validation fails, the metagene2 object will now fall back to the previous set of parameters, instead of ending up in an invalid state.

Changes in version 1.1.2 (2019-05-09)

  • rnaseq mode now sets strand_specific to TRUE by default.

Changes in version 1.1.1 (2019-05-03)

  • Added log2_ratio normalization option.

  • Fix a bug that prevented strand_specific and stitch mode to work together.

Changes in version 1.1.0 (2019-04-05)

  • Submitted package to Bioconductor.


Changes in version 1.21.4

  • Pull request accepted bug correction in annotation pipeline

Changes in version 1.21.2

  • change Maintainer


Changes in version 1.15.2 (2019-09-09)

  • add codecov

  • add Travis-CI for continuous integration

Changes in version 1.15.1 (2019-08-29)

  • add ggplot2 in dependencies

  • change GPL-2 to GPL-3 license

Changes in version 1.15.0 (2019-04-23)

  • implement the MSnbase Spectra/Spectrum2 as the container for MS2 spectra, change all functions that they accept Spectra objects

  • write function convertMsp2Spectra that converts MSP files to Spectra files

  • change data files: change convertMSP2MSP.RData to convertMsp2Spectra, create spectra.RData, update similarityMat.RData

  • remove data files: binnedMSP.RData, idMSMStoMSP.RData


Changes in version 0.99.0

  • Submitted to Bioconductor


Changes in version 0.99.0

o Submission to Bioconductor


Changes in version 1.3.5

  • Using IlluminaHumanMethylationEPICanno.ilm10b4.hg19

Changes in version 1.3.2

  • Shiny app is available within the package

Changes in version 1.3.1

  • Bug fixes in methylgometh


Changes in version 1.10.1

  • fixed the error that caused failed build of the package as follows: Changed the argument “entrezgene” used in getBM() to “entrezgene_id”, since this was changed in the Ensembl database and caused an error in the internal function ‘.get.genes.rnaseq()’.


Changes in version 2.0 (2019-08-20)

  • spreadplot function added

  • removed ready made themes from functions

  • Added is.compositional

  • Fixed a bug in core_members (also non-compositional detection now allowed)

  • removed option from aggregate_taxa

  • Deprecating noncore_* functions (replacing with rare_* functions everywhere)

  • Removed variable_members function

  • Support removed from R-3.3.3 and lower


Changes in version 0.99.0 (2019-08-26)

  • Submitted to Bioconductor


Changes in version 1.3.2

  • Update miRSM function <2019-09-11, Wed>

Changes in version 1.3.1

  • Add modular analysis <2019-08-12, Mon>


Changes in version 1.11.1

  • Add citation <2019-05-10, Fri>.


Changes in version 6.8.6

new features / enhancements


bug fixes

  • predict function bug for single sample prediction fixed - plotLoadings bug for long variable names fixed

minor improvements

  • missing values in plotIndiv’s group argument no more throws error - mixOmics::predict function documentation now more accessible

Changes in version 6.8.5

bug fixes

  • names of linnerud datasets fixed.

Changes in version 6.8.4

minor improvements

  • package startup message with direct liks to useful resources - mixOmics function documentation disambiguated with instruction on how to get package help.

Changes in version 6.8.3

new features / enhancements

  • You can now customise auroc plots. Refer to documentation for more info.

bug fixes

  • Fixed tune.spls and pef.plsda bugs when using cpus argument for parallel processing

minor improvements

  • auroc help files now updated with latest changes

Changes in version 6.8.2

minor improvements

  • Updated onLoad message with discussion forum info, bug reports, and more - Dropped legacy comp.tol argument from pca

Changes in version 6.8.1

bug fixes

  • perf.plot bug in extracting names fixed - Few fixes for tune.splsda with AUC

minor improvements

  • plot.perf now respects ylim arguments for custom y range - Added code of conduct - Updated DESCRIPTION with bug reports and biocViews
  • Updated README


Changes in version 0.99.0

  • Submitted to Bioconductor


Changes in version 0.99.2 (2019-10-21)

  • Changed default output of Maaslin2_wrapper and rma_wrapper to tempdir()

Changes in version 0.99.1 (2019-10-15)

  • Switched reference links for igraph and fpc in Rd documents.

Changes in version 0.99.0 (2019-10-15)

  • Initial submission to Bioconductor.


Changes in version 0.99.0 (2019-06-13)

  • Submitted to Bioconductor


Changes in version 1.29.8

  • remove google scholar from vignette.

Changes in version 1.29.7

  • Add google scholar in vignette.

Changes in version 1.29.6

  • fix a bug that ‘grid’ and ‘graphics’ output mixed for plotMotifStackWithPhylog

Changes in version 1.29.5

  • fix a bug that importMatrix can not handle empty matrix.

Changes in version 1.29.4

  • fix a bug that markers shift position when alignment.

Changes in version 1.29.3

  • accept pcm for plotMotifLogoA

  • geom_motif accept x,y,width,height

Changes in version 1.29.2

  • add markers

Changes in version 1.29.1

  • add function geom_motif


Changes in version 1.18.0

  • release as part of Bioconductor 3.10

Changes in version 1.17.2

  • removed change history from package vignette for easier maintenance

Changes in version 1.17.1

  • fixed regular expression to comply with PCRE2

  • fixed Windows makefile for gc lib

  • fixed Windows cleanup script

  • fixed src/

Changes in version 1.17.0

  • new branch for Bioconductor 3.10 devel


Changes in version 2.11

Changes in 2.11.13

  • Fix bug in readSRMData (issue #486) which caused the function to not discriminate between chromatograms with different precursor collision energy.

Changes in 2.11.12

  • Fix bug in pickPeaks: set variable centroided only to TRUE for spectra matching the provided msLevel.. - Add parameter msLevel. to smooth.

Changes in 2.11.11

  • Update news files titles to be consistent with other Bioc packages.

Changes in 2.11.10

  • Updates to consensusSpectrum: add parameter mzFun allowing to define the aggregation function for m/z values, change default for mzd to 0 (hence avoid estimating m/z differences by default) and change the default for parameter intensityFun to median.

Changes in 2.11.9

  • Use latest mzR

Changes in 2.11.8

  • Update URL to point to pkgdown site

Changes in 2.11.7

  • Add parameter weighted to consensusSpectrum and change the default from reporting the intensity-weighted mean of m/z values for consensus peaks to reporting the m/z of the largest peak <2019-09-12 Thu>.

Changes in 2.11.6

  • Update to match changes in mzR version 2.17.4 <2019-09-04 Wed>. - Add parameter msLevel to pickPeaks to allow peak picking in specific MS levels. See #478 <2019-09-04 Wed>.

Changes in 2.11.5

  • Use filterMsLevel, filterMz, filterPolarity, filterRt, filterAcquisitionNum, filterEmptySpectra, filterPrecursorScan, productMz, filterPrecursorMzandfilterIsolationWindowgenerics fromProtGenerics`.

Changes in 2.11.4

  • plot,Spectrum,Spectrum now also supports MS1 spectra (see #477) <2019-07-23 Tue>

Changes in 2.11.3

  • Make combineFeatures a method <2019-05-31 Fri> - Remove message about changed meaning of the “modifications” argument in calculateFragments’ that was introduced in MSnbase 1.17.6 (2015-06-21). <2019-06-01 Sat> - Implement combineSpectra,MSnExp (see #474) <2019-06-02 Tue>.

Changes in 2.11.2

  • Fix bug in calculateFragments for neutral loss calculation. For the “loss of water” the mass of HO~2~ instead of H~2~O was removed (see #462). Thanks to Max Helf (@mjhelf) for the fix (see #463) <2019-05-31 Fri>.

Changes in 2.11.1

  • Migrate generics to ProtGenerics

Changes in 2.11.0

  • Bioconductor 3.10 (devel)


Changes in version 1.11.5

  • frag4feature fileid fix for conversion from factor to character

  • Add missing plyr:: reference (thanks jsaintvanne)

Changes in version 1.11.3

  • Overhaul of combineAnnotation function. Uses local database now as previously API calls would take too much time to finish and was not usable

  • Various updates of createMSP to make compatible with Galaxy workflows

  • Parameter added to purityA to allow user to change the PPM tolerance for MZ values between scans when calculated the interpolated precursor ion purity

  • Update of spectralMatching results columns to include additional details (e.g. retention time)

  • Update of spectralMatching so that either PostgreSQL or MySQL database can be used as input to either query or library

Changes in version 1.11.2

  • Bug fix for EIC with MSMS data

Changes in version 1.11.1

  • Bug fix for duplicate MSP spectra when not using metadata table

  • Added xcms3 to xcmsSet conversion for “create database” code

  • Fix for sirius combine annotations (incorrect column format)

Changes in version 1.11.0

  • Bioconductor dev (automatic version bump)


Changes in version 2.19.6

  • header for the pwiz backend returns NA instead of 0 for not defined or missing information <2019-09-24 Tue>.

  • peaks for pwiz backend rewritten (small performance improvement) <2019-09-26 Thu>.

Changes in version 2.19.5

  • version bump to force build with latest Rcpp

Changes in version 2.19.4

  • Add header columns scanWindowLowerLimit and scanWindowUpperLimit

Changes in version 2.19.3

  • use ProtGenerics::tolerance generic <2019-08-16 Fri>

Changes in version 2.19.2

  • Fix issue 190, compiles on clang-8.0

Changes in version 2.19.1

  • Remove analyzer generics, now in ProtGenerics <2019-05-13 Mon>


Changes in version 1.9.2

  • Update citation. - Update trimPeaks.R to filter peaks using adjusted pvalues and trimmed peaks by removing windows with zscore < 1.696

Changes in version 1.9.1

  • Add citation.


Changes in version 1.1.1 (2019-08-16)

  • Added a new function makeplot

  • Visualization part in vignette is modified


Changes in version 0.99.7 (2019-08-22)

  • Added citaion

Changes in version 0.99.2 (2019-06-19)

  • Submitted to Bioconductor

Changes in version 0.5.0 (2019-04-02)

  • Uploaded to GitHub


Changes in version 1.1.3 (2019-08-01)

  • Introduction of the fully rank based extension (netboost(…,robust_PCs=TRUE,filter_method=”spearman”,method=”spearman”)).

Changes in version 1.1.1 (2019-05-06)

  • Introduction of Pearson-, Spearman- and Kendall-based filtering.


Changes in version 1.1.1

  • Added plotAlignmentSummary()

  • Added plotFastqcPCA()

  • Added quast, busco, cutadapt, featureCounts, trimmomatic, flagstats & AdapterRemoval support to importNgsLogs()

  • Enabled auto detection for report type for importNgsLogs()

Changes in version 1.0.2

  • Added Transcriptomic GC Content for A.thaliana to default gcTheoretical object

Changes in version 1.0.1

  • Table in default FastQC template now scroll for larger datasets

  • Kmers removed from default FastQC template

  • Typos in vignette corrected, seperate LICENSE file added & dplyr updates corrected

  • Corrected dependencies for writeHtmlReport


Changes in version 1.3.3

  • Extended input validation when executing NormalyzerDE using experimentObj

Changes in version 1.3.2

  • Correctly showing the number of values replaced with NA in status text

Changes in version 1.3.0

  • Sync with Bioconductor changes


Changes in version 1.11.2

  • Added correct CITATION

Changes in version 1.11.1

  • Maintainer E-mail adress updated


Changes in version 1.5.4

  • explicitly calling some functions to prevent conflicts (jsonlite::fromJSON)

  • corrected namespace and description

  • removed “require(libraries”) from ui.

  • bug fix for calculating aldex object. sometimes would need to click generate effect plot twice.

  • version bump

  • changed T to TRUE in rab_script and server.R

Changes in version 1.5.1

  • choice of pseudocount or CZM

  • changed how conditions are selected manually for effect size. now, you input the column number

  • added ability to download GO slim annotated feature tables directly from MGNify database by inputting a Study ID

  • added density plots for interactive effect sizes

  • currently depends on specific version of ALDEx2 (temporary)


Changes in version 0.99.12 (2019-10-21)

  • Modification in the separation between genes within a complex (From dash) to Underscore

Changes in version 0.99.0 (2019-10-10)

  • Submitted to Bioconductor


Changes in version 2.15.2 (2019-08-14)

  • Trying to prevent fscanf warning in FitnessLandscape/input.c

Changes in version 2.15.1 (2019-06-06)

  • Added MAGELLAN’s sources and functionality from MAGELLAN.

Changes in version 2.15.0 (2019-06-06)

  • Bumped version to match current Biocdevel.


Changes in version 1.4.0


  • added online FWER algorithms of Tian and Ramdas [2019b]

  • added the ADDIS algorithms of Tian and Ramdas [2019a]

  • added asynchronous online testing algorithms of Zrnic et al. [2018]

  • added the SAFFRON procedure for online FDR control [Ramdas et al., 2018]

  • added the Alpha-investing procedure of Ramdas et al. [2018]

  • updated vignette

  • deprecated LORDdep and added functionality to LORD

  • deprecated Bonfinifinite, which is replaced by AlphaSpending

  • removed LORD versions 1 and 2

  • added unit tests

  • updated references

  • updated authors


Changes in version 0.99.13

Features in the first version, Bioconductor 3.10 Release (September 2019

  • artImpute Artificially miss and impute each data entry individually by ignoring outlying values

  • clusterData Hierarchical cluster analysis

  • dropMarkers Filter out markers

  • dysReg Analyze dysregulated (protruding) events

  • markOut Display outlying expressions

  • oppti Outlier protein and phosphosite target identification

  • outScores Analyze putative outliers

  • plotDen Draw densities

  • rankPerOut Rank markers by the percentage of outlying events

  • statTest Analyze dysregulation significance


Changes in version 1.14.0


  • src_organism() supports an option overwrite=FALSE to optionally over-write exisiting (cached) resources created from a previous txdb version.

  • src_organism() supports construction from a TxDb object.


Changes in version 1.3.2

  • Documentation

  • New plot functionality - plotExpectedVsObservedCounts() - plotCountGeneSampleHeatmap() - plotExpressedGenes()

  • Minor bug fixes

  • Linking to publication REVISED VERSION 0.99.29

  • Major changes

  • Improved autoencoder model.

  • Updated API

  • Improved default parameters. SECOND BIOCONDUCTOR SUBMISSION 0.99.10

  • Smaller and faster example data set

  • Loss and gradient of loss in C++


  • Better documentation

  • Little changes in default values

  • Code cleanup and improvements


  • Adding the R implementation of the autoencoder

  • Little changes in default values

  • Updating and completing documentation


  • Minor changes in plotting functions

  • Update interface to autoCorrection



  • Initial setup of OUTRIDER package

  • Added autoCorrect (Auto Encoder) as normalization function


Changes in version 1.1.1


Our build on Bioconductor 3.9 devel fails for the second vignette. This patch resolves this issue.


Changes in version 0.25.1

  • Removing mapping functions, moved to the ensembldb package. <2019-08-08 Thu>

  • Marking package for deprecation <2019-08-08 Thu>


Changes in version 2.12.0

Bug fixes

  • Fixed an error in the initialization of the app due to a new behavior introduced by shinyAce in version >= 0.4.0 - topGOtable does not generate rows with NAs if providing a too high number for the categories to report

Other notes

  • The type of the columns in the data.frame returned by topGOtable are now correctly referring to the type they contain - e.g. the p values are now stored as numeric values - Citation now refers to the published manuscript -


Changes in version 2.0.0

  • added parallelPCA function to perform Horn’s parallel analysis, which chooses an ideal number of principal components to retain (courtesy Aaron Lun)

  • added findElbowPoint function, which finds the elbow point in the curve of variance explained and which can also be used to determine the number of principal components to retain (courtesy Aaron Lun)

  • user can now specify custom labels for points

  • fixed bug with singlecol parameter for biplot colouring everything black


Changes in version 0.99.3 (2019-10-01)

  • Revisions for Bioconductor submission

Changes in version 0.99.2 (2019-09-10)

  • Revisions for Bioconductor submission

Changes in version 0.99.0 (2019-06-09)

  • Submitted to Bioconductor


Changes in version 0.99.11 (2019-09-19)

  • Fixed bugs

  • Made the following significant changes o Removed Knight dataset

Changes in version 0.99.10 (2019-09-17)

  • Submitted to Bioconductor


Changes in version 1.15.1

  • Implementation for the protein database construction from fusion events(buildFusionProteinDB). Currently, this function only supports the calling result from STAR-fusion.

Changes in version 1.14.1

  • Add a parameter to set FDR

  • Update parser program V


Changes in version 0.99.31

  • Submitted to Bioconductor


Changes in version 2.2.0


  • Fix import exprs<- bug in loadMAdata.

Changes in version 2.0.1


  • Fix error message handling in network plot in exploreGSAres().


Changes in version 1.11.34 (2019-10-21)


  • The pipeline is now explained step by step in the vignette.

Changes in version 1.11.32 (2019-10-18)

Changes in existing functions

  • The Data argument of compute.pigengene can now be a matrix with only 1 column.

Changes in version 1.11.30 (2019-10-02)

Changes in existing functions

  • The doRetuNetworks argument is now added to the combine.networks function.

Changes in version 1.11.28 (2019-10-01)

New functions

  • message.if() is now exported.

Changes in version 1.11.26 (2019-09-26)

Changes in existing functions

  • Better QC in the gene.mapping() function, the possible keys will be printed if the input is not appropriate.

New functions

  • save.if() is now exported.

Changes in version 1.11.24 (2019-09-03)

Bug Fixes

  • In the function, selectedModules does not need to be “All”. Also, if saveFile=NULL, nothing will be saved without any error.

Changes in version 1.11.20 (2019-05-15)

Changes in existing functions

  • Data and Labels can now be lists, which will be combined using before analysis.

Changes in version 1.11.4 (2019-05-02)

Bug Fixes

  •,…) now produces valid output.


Changes in version 1.18.0

  • release as part of Bioconductor 3.10

Changes in version 1.17.3

  • removed change history from package vignette for easier maintenance

Changes in version 1.17.2

  • minor changes to DESCRIPTION file (system requirement GNU make) and src/Makevars

Changes in version 1.17.1

  • changed summary() method for VariantAnnotation class in order to stay compatible with print() method in GenomicRanges package

  • corresponding minor adaptations in documentation and package vignette

Changes in version 1.17.0

  • new branch for Bioconductor 3.10 devel


Changes in version 1.99.3

  • NB function now exported

  • note that version 1.99.3 on GitHub was version 1.1.0 on Bioconductor.

Changes in version 1.99.2

  • bug fix in fragment generation (last 2 bases of transcript were never sequenced)


Changes in version 2.2


  • Default minimal PQS score was decreased from 52 to 47. The score 47 shows the best balanced accuracy on new G4 sequencing data provided by Marsico et al. 2019.


  • Fixed bug allowing unlimited length of third loop leading to invalid memory access and random scores.


Changes in version 0.99.0 (2019-06-02)

  • Initial submission


Changes in version 1.25

Changes in version 1.25.2

  • Fix new biomart attribute <2019-08-09 Fri> - Bug fix: pass fcol to helper function (see <2019-08-09 Fri>

Changes in version 1.25.1

  • Always use mvtnorm::dmvnorm <2019-06-21 Fri>

Changes in version 1.25.0

  • Version bump for Bioc 3.10 (devel)


Changes in version 1.17.4

  • New generics needed in Spectra and Chromatograms packages <2019-08-20 Tue>

Changes in version 1.17.3

  • New tolerance generic <2019-08-16 Fri>

Changes in version 1.17.2

  • New generics (see issue #8) <2019-05-12 Sun>

Changes in version 1.17.1

  • Move many generics from MSnbase <2019-05-11 Sat>


Changes in version 1.16.0


  • Flag segments in poor quality regions

  • predictSomatic now provides log-likelihood of allelic balance (ALLELIC.IMBALANCE column) for each variant

  • Added readLogRatioFile function to read GATK4 DenoiseReadCounts output files containing log2 tumor/normal ratios

  • Added readSegmentationFile function to read GATK4 ModelSegment output files containing segmented log2 tumor/normal ratios

  • Added callAmplificationsInLowPurity to call gene-level amplifications in samples < 10% purity

  • Dx.R now reports chromosomal instability scores (available also via callCIN function)

  • Dx.R supports deconstructSigs 1.9.0 and COSMIC signatures v3. To run both v2 and v3, simply add –signature_databases signatures.exome.cosmic.v3.may2019:signatures.cosmic to Dx.R


  • Made filterTargets and createTargetWeights defunct

  • setMappingBiasVcf now returns a data.frame

  • Best practices vignette now HTML-based

  • Renamed normal.panel.vcf.file in setMappingBiasVcf to mapping.bias.file; in 1.18, setMappingBiasVcf will not accept a VCF anymore but requires a precomputed mapping bias RDS file.

  • calculateIntervalWeights now directly called by createNormalDatabase and information included in the normalDB RDS object. This function is thus deprecated.

  • Column gene.mean in callAlterations output now weighted by interval weights when available

  • Changed default of in preprocessIntervals from 10 to 100 (#73)

  • replaced write.table with data.table::fwrite to automatically support producing gzipped output (requires data.table 1.12.4, #106)

  • Coverage.R now gzips BAM file coverage (requires data.table 1.12.4, #106)

  • Output coverage files now code FALSE as 0 and TRUE as 1

  • PureCN.R now bgzips and tabix indexes VCFs when –vcf is provided


  • Fix for bug in CCF calculation resulting in NAs (happens in high coverage samples, early mutations with > 1 allele copy number)

  • Fix for a bug in preprocessIntervals when small targets (< were present

  • Fix for a bug in callMutationBurden when VCF contained indels (#82)

  • Die with helpful error message when snp.blacklist import failed

  • Check input segmentation files for missing values resulting in crash

  • Fixed a crash in Varscan2 produced VCFs when ALT field missed ref counts (#109)


Changes in version 0.1.0

  • Initial version


Changes in version 1.21.6 (2019-09-25)


  • Link to the ‘GEM library’ tool was broken.

Changes in version 1.21.5 (2019-09-09)


  • plot(…, logTransform=TRUE, doSegments=TRUE) on QDNAseqSignals would position segments that were out of range incorrectly, because it forgot to take the log transform on those outliers.

Changes in version 1.21.4 (2019-09-06)


  • Bin annotation data files are no longer downloaded automatically. They are instead part of Bioconductor annotation packages QDNAseq.hg19 and QDNAseq.mm10, which needs to be installed by the user. If not installed, an error is now produced. The reason for this change, is that the QDNAseq maintainers will no longer host QDNAseq bin annotation files online (in the cloud).

Changes in version 1.21.3 (2019-09-04)


  • All functions that produce verbose output gained argument ‘verbose’. For backward compatibility, it currently defaults to ‘verbose=TRUE’ but that may be changed to ‘verbose=FALSE’ in a future release.


  • callBins() now respects option ‘QDNAseq::verbose’ for controlling whether output from the CGHcall package should be relayed or not.

  • MEMORY: Utilize more memory-efficient matrixStats functions colSums2(), colMeans2(), etc.


  • Argument ‘seeds’ of segmentBins() is deprecated because it did not use proper parallel random number generation (RNG). We now instead rely on future.apply::future_lapply(…, future.seed=TRUE) for this.

Changes in version 1.21.2 (2019-09-03)


  • Package now imports the ‘future’ and ‘future.apply’ packages; previously the ‘future’ was listed as a suggested package.

  • Package no longer depends on BiocParallel.

  • binReadCounts() now uses the future framework instead of BiocParallel for parallelization.


  • MEMORY: Avoiding data type coercions in more places by for instance making sure that vectors and matrices are initated with the values of the correct data type (instead of the default NA, which is a logical value).


  • Using future_lapply() and future_apply() of the well-tested future.apply package instead of internal analogue implementations.

  • TESTS: Now testing numerical reproducibility also for parallel processing (using future strategies ‘multisession’ and ‘multicore’).

  • TESTS: Now asserting numerical reproducibility of also segmentBins() and callBins().

Changes in version 1.21.1 (2019-08-30)


  • exportVCF() is no longer exported. Use exportBins(…, format=”vcf”) instead.


Changes in version 1.3.2

  • Added mergePeptides to NAMESPACE

Changes in version 1.3.1

  • Added mergePeptides function to summarize identical peptides to single peptide for specific protein.


Changes in version 0.99.12 (2019-09-06)

  • eval=false for package installation in vignette

  • Title change in vignette

Changes in version 0.99.11 (2019-09-03)

  • Incorporated Bioconductor reviewer comments

Changes in version 0.99.10 (2019-08-27)

  • Minor

Changes in version 0.99.9 (2019-08-27)

  • Bugfixes, error handling

Changes in version 0.99.8 (2019-08-27)

  • Additional HTTP error handling

Changes in version 0.99.7 (2019-08-27)

  • Minor

Changes in version 0.99.6 (2019-08-27)

  • Code revised

Changes in version 0.99.5 (2019-08-27)

  • Added parameter return_obj to have the possibility to get a GenomicRanges::GRanges object

Changes in version 0.99.4 (2019-08-14)

  • Added parameter ld_method and corr

Changes in version 0.99.0 (2019-08-12)

  • Submitted to Bioconductor


Changes in version 1.10.0

Bug fixes and minor improvements

  • Include reference to TCGAutils functions for qreduceAssay examples
  • Add robustness to RaggedExperiment constructor including unit tests
  • Include class and assay operations overview schematic in the vignette


Changes in version 1.21.1 (2019-05-17)


  • Removed AppVeyor CI due to the frequent Bioconductor installation and dependency issues which are not related to the package itself. - Updated GitHub repository links due to the recent handle change. - Updated the vignette style.


Changes in version 1.1.12 (2019-09-09)

  • Add ExpressionTool, Extensions and Metadata

Changes in version 1.1.7 (2019-07-25)

  • New feature, baseCommand works with R function


Changes in version 1.1.14 (2019-10-21)

  • Add pvactools neoantigen prediction pipeline

Changes in version 1.1.8 (2019-08-22)

  • Add more Somatic Variant Callers: VarScan2, LoFreq, MuSE, SomaticSniper, VarDict, lancet, manta, strelka2

Changes in version 1.1.5 (2019-07-19)

  • Structure updates: export all tools and pipelines.

  • Added GATK4 Mutect2 tools and pipelines.

  • Added Command and Container to metadata of cwlTools.

  • Vignette updated.

Changes in version 1.1.2 (2019-05-22)

  • fix samtools index bug for cwltool 2019


Changes in version 2.6.0

  • New functions: - createGroupByColumn - clearEdgeBends - getNodePosition

  • New parameter to return SUIDs for - getSelectedNodes - getSelectedEdges

  • Node and edge property values returned as named lists

  • Faster results for getting all node and edge property values, #78

  • More robust handling of file type in export functions

  • More robust handling of dataframes in createNetworkFromDataFrames

  • New support for loading list data

  • Doc Fixes - added Filters to Overview vignette - improved file type handling descriptions

Changes in version 2.4.4

  • Bug Fixes - filter functions – #73 wrong params

Changes in version 2.4.3

  • Bug Fixes - import functions – #62 fixed default directory

Changes in version 2.4.2

  • Bug Fixes - getEdgeInfo – #61 missing function

Changes in version 2.4.1

  • Bug Fixes - getLayoutPropertyNames – #59 fixed returned values - createNetworkFromIgraph – #58 flatten list attributes to strings


Changes in version 0.99.8 (2019-08-13)

  • Removed package startup message

  • Changed spelling of name to ReactomeGSA

  • Removed all default values from the method signatures

  • Added constructor function for the ReactomeAnalysisRequest class.

Changes in version 0.99.7 (2019-07-22)

  • Adapted the get_reactome_methods function to provide a more readable overview

  • Changed to reactome analysis service API URL to the new domain name.

Changes in version 0.99.6 (2019-07-09)

  • Minor bugfixes in examples

Changes in version 0.99.5 (2019-07-09)

  • Updated vignette to new API data types

  • Added new function remove_dataset

  • Fixed bugs when overwriting existing datasets in AnalysisRequests

  • Fixed bug that pathways function did not sort the pathway table

Changes in version 0.99.0 (2019-07-01)

  • Submitted to Bioconductor


Changes in version 1.11.14

  • Added a file to track changes to the package.

Changes in version 1.11.13


  • Added the function getTPM() as discussed in and based on Sonali Arora et al

Changes in version 1.11.12


  • Now geo_characteristics() can deal with the scenario reported at by @Jacques.van-Helden.

Changes in version 1.11.7


  • Renamed .load_install() as .load_check() as this function now only checks that the package(s) was installed and returns an error if missing. The error shows the user how to install the package(s) they are missing instead of installing them automatically. This complies with Marcel Ramos’ request at

Changes in version 1.11.4


  • Added the function download_retry() based on such that download_file() and other recount functions will re-try to download a file 3 times before giving up. This should help reduce the number of occasional failed Bioconductor nightly checks.


Changes in version 1.18.0


  • Expanded toGRanges support. It is now possible to transform coverage objects (i.e. toGRanges(coverage(A))) into GRanges. It also supports “.assoc” files produced by PLINK.

  • overlapPermTest now supports multiple region sets in B and will perform a multi- permutation test against each one much faster than testing them independently.


  • Multiple bug fixes


Changes in version 1.19.2

  • Added a file to track changes to the package.


  • Renamed load_install() as load_check() as this function now only checks that the package(s) was installed and returns an error if missing. The error shows the user how to install the package(s) they are missing instead of installing them automatically. This complies with Marcel Ramos’ request at


Changes in version 1.17.1

  • assign to foreName and backName when querying GREAT

  • use rmarkdown for vignette

  • support GREAT version 4.0.4

  • add startup messages


Changes in version 2.30.0


  • Functions H5Lmove & H5Lcopy are now exported and accessible.


  • Source file names are no longer mangled when printing error messages.

  • NA values in a character() vector can now be written to an HDF5 dataset.


Changes in version 1.8

New features

  • Updated internal version of HDF5 to 1.10.5

Bug fixes

  • Quote paths reported by pkgconfig() to allow installation in librarys with whitespace in the path.


Changes in version 1.18.0


  • Compile HTSlib with libcurl enabled

  • Support an installation path that contains whitespaces


  • Switch from dynamic to static linking on all Unix-like systems (see commit db1d8e17)

  • Package now requires libbz2 & liblzma & libcurl (with header files), and GNU make. This is declared in new SystemRequirements field.


  • Use preprocessor flag -D_FILE_OFFSET_BITS=64. This addresses nasty problem with big files that get truncated on Windows. See

  • Don’t overwrite CPPFLAGS, CFLAGS, or LDFLAGS values set in ${R_HOME}/etc/Makeconf on Linux or Mac


Changes in version 0.99.0 (2019-04-29)

  • Submitted to Bioconductor


Changes in version 0.99.0 (2019-04-29)

  • Submitted to Bioconductor


Changes in version 0.99.0 (2019-04-29)

  • Submitted to Bioconductor


Changes in version 0.99.0 (2019-04-29)

  • Submitted to Bioconductor


Changes in version 2.3.3

  • Fixed non ASCII column names in age prediction and immune estimation

Changes in version 2.3.2

  • Added stratification plots for inferred covariates in different sample groups


Changes in version 2.13


  • Remove failing test - term is now obsolete <2019-10-12 sam.>


  • Fix failing test <2019-08-12 Mon>


Changes in version 1.17.34


  • ‘view’ method (wrapper of the imageF and strF functions)

Changes in version 1.17.32


  • plot.oplsMultiDataSet correction to include all plots in the .pdf file

Changes in version 1.17.30


  • Additional correction in getMset documentation (example)

Changes in version 1.17.28


  • Correcting typo in getMset documentation (example)

Changes in version 1.17.26


  • Including the set name in the figure of MultiDataSet models

Changes in version 1.17.24


  • Correction of the documentation for ‘residuals’ and ‘plot-oplsMultidDataSet’

Changes in version 1.17.22


  • Correction of the example in the oplsMultiDataSet class documentation

Changes in version 1.17.20


  • plotPhenoDataC parameter for coloring (score plots) according to one column from the pData data frame when the opls method has been applied to an ExpresssionSet

Changes in version 1.17.18


  • Minor internal modification

Changes in version 1.17.16


  • Minor internal modification

Changes in version 1.17.14


  • Example of the analyis of a MultiDataSet (‘NCI60_4arrays’ from the ‘omicade4’ package)

Changes in version 1.17.12


  • Multi data set names display on graphics

Changes in version 1.17.10


  • plot method for oplsMultiDataSet objects

Changes in version 1.17.8


  • opls can now be applied to MultiDataSet objects; getMset method to extract the complemented MultiDataSet

Changes in version 1.17.6


  • minor internal modification

Changes in version 1.17.4


  • minor internal modification

Changes in version 1.17.2


  • info.txtC and fig.pdfC argument values NULL and NA replaced by ‘none’ and ‘interactive’, respectively


Changes in version 1.21

Changes in version 1.21.3

  • Update NEWS titles

Changes in version 1.21.2

  • Temporary fix for issue #5 (wrong URL from PRIDE server) <2019-10-02 Wed>

Changes in version 1.21.1

  • Don’t set old class <2019-08-09 Fri>


Changes in version 2.0.0

  • Rsubread package is ported to Windows OS.

  • New function cellCounts(): generate UMI counts for Chromium 10X single-cell RNA-seq data.

  • flattenGTF() function can merge or chop overlap features.

  • Check and display the amount of memory available on the computer before starting read mapping.

  • Optimize the data structure used in buildindex() function to reduce its memory use.

  • qualityScores() function can optionally retrieve quality scores from all the reads.

  • File paths included in column names of objects returned by featureCounts(), align(), subjunc() and propmapped() functions are removed or shortened where appropriate.

  • featureCounts() will be terminated if both single-end and paired-end reads are found in the same input file.

  • Limit on the length of input file names is increased to 1000 bytes for all functions.


Changes in version 2009-07-13

  • combineRTCA(list): Additional column is renamed into Plate. The vlues is evaluated from list item names. When the list has no name, an integer index beginning from 1 is used. Special attentions to list partially with names is noted in the documentation.

  • parseRTCA(file, dec=”.”,phenoData, skipWell,…): Example is added in the documentation how to import pre-configured phenoData. Details section in the documentation is re-written to describe the process of parsing.

  • RTCA-class: Experiment ID added to RTCA class

  • Makefile: add Makefile to simplify common tasks like check and install

  • plotGridEffect: takes ‘column’ instead of ‘col’ as mode parameter, and renders the mode as the title of the legend. Documentation updated.

  • plotRTCA: is removed from the package and is substituted by the plot function.


Changes in version 2.16.0

New features

  • RNASeq2GeneNorm slot in the FirehoseData class is a list now (from matrix) - Use tempdir() as the default directory for downloading data in getFirehoseData

Bug fixes and minor improvements

  • Save all RNASeq2GeneNorm datasets within the output object as a list. Previously, only the last dataset would get returned (#30) - Read files from the appropriate download location in getFirehoseData
  • Move static text file references from ‘’ to GitHub hosted locations - Check file sizes using httr instead of ‘’ query (@mksamur, #32)


Changes in version 1.6.0

  • Minor updates to the Pathway Analysis vignette

Changes in version 1.4.1

  • Bug fixes - Updated the findPathwaysByLiterature test case (fixing a false positive fail) - Removed tests for unavailable service: getColoredPathway


Changes in version 0.24.0


  • Add Factor class. Serves a similar role as factor in base R except that the levels of a Factor object can be any Vector derivative.

  • New methods for DataFrame comparisons (by Aaron Lun)

  • Add sameAsPreviousROW() generic and methods for ANY, atomic, integer, numeric, complex, Rle, DataFrame, and Pairs (by Aaron Lun)

  • Support more comparison methods for Pairs objects

  • Add methods for coercing back and forth between HitsList and SortedByQueryHitsList.

  • Add anyDuplicated() method for Vector derivatives.

  • Support ‘by=’ argument on sort,List

  • Add is.finite() method for Rle objects

  • Add add “&” method for FilterRules objects as a convenience for concatenation


  • Add DFrame class (commit 36837bdf). DataFrame() now returns a DFrame instance (commit 83b09b19).

  • Now ‘stringsAsFactors’ is set to FALSE when coercing something to a DataFrame.

  • Move splitAsList() from the IRanges package

  • Move S4 class “atomic” from the IRanges package

  • Improve handling of user-supplied metadata columns


  • Remove phead(), ptail(), and strsplitAsListOfIntegerVectors(). These functions were deprecated in BioC 3.7 and defunct in BioC 3.8.


  • Fix split() on a SortedByQueryHits object (issue #39)

  • Fix the following coercions: - Hits -> SelfHits - SortedByQueryHits -> SortedByQuerySelfHits - SelfHits -> SortedByQuerySelfHits - Hits -> SortedByQuerySelfHits Before this fix all these coercions seemed to work but they were in fact silently producing invalid objects.

  • A fix to anyDuplicated() method for Rle objects (commit 63495d6)

  • A fix related to replacing DataFrame columns with matrix columns (commit 00169dd6)

  • All show() methods now return an invisible NULL (commit f4b4ee76)


Changes in version 1.0.0

  • first Bioconductor release

Changes in version 0.99.0

  • package submitted to Bioconductor

Changes in version 0.9.10

  • SAIGE algorithm implementation for quantitative outcomes

Changes in version 0.9.9

  • add a vignette to the package

  • the default of random number generator changes in R: “Rounding” was the default in RNGkind() prior to R_3.6.0, but “Rejection” is used in R (>= v3.6.0). For reproduction of the results created by R (< v3.6.0), please use RNGkind("Mersenne-Twister", "Inversion", "Rounding") in R (>= v3.6.0)

Changes in version 0.9.7

  • seqAssocGLMM_SPA(): load balancing in parallel

Changes in version 0.9.0

  • first version of SAIGEgds


Changes in version 1.14.0

  • Removed deprecated dplyr verbs.

  • Removed deprecated method= option in runPCA(). Increased ncomponents= default to 50. Deprecated use_coldata= and related options in favour of runColDataPCA(). Switched BSPARAM= default to bsparam().

  • Added runColDataPCA() function for running PCA on colData(). Switch outlier detection strategy to avoid mvoutlier’s dependency tree.

  • Added the annotateBMFeatures() function to perform annotation without modifying the input.

  • Pass all … options to biomaRt::useMart() in getBMFeatureAnnos().

  • Added name= arguments to runPCA(), etc. to change the name of the output reducedDim.

  • Added the logNormCounts() function to compute log-normalized counts in an alternative experiment-aware manner. Added a normalization-by-downsampling option via DropletUtils.

  • Added the perCellQCMetrics() function to compute per-cell QC metrics in an alternative experiment-aware manner.

  • Deprecated the normalize() method, which was considered too vague to describe what the function was actually doing.

  • Added the perFeatureQCMetrics() function to compute per-feature QC metrics.

  • Deprecated the calculateQCMetrics() function, to be replaced by the streamlined addQCPerCell() and addQCPerFeature().

  • Generalized all functions, where possible, to operate on SummarizedExperiment and numeric matrices. This involved converting a number of them to S4 methods to take advantage of dispatch. Affected functions include normalizeCounts(), calculateCPM(), librarySizeFactors() and so on.

  • Added calculateTSNE() and related methods to operate directly on an input matrix.

  • Renamed the use_dimred= argument to dimred=, along with similar renamings of other arguments for consistency.

  • Report all percentages of variances explained as actual variances in runPCA() and getVarianceExplained().

  • Added aggregateAcrossCells() and aggregateAcrossFeatures() to create a summed SingleCellExperiment object.

  • Added the mockSCE() function to generate example objects for the documentation.

  • Support multiple factors for grouping cells in sumCountsAcrossCells().

  • Support list of grouping vectors in sumCountsAcrossFeatures().

  • Added the order_columns_by= argument to plotHeatmap() for easy plotting by a given factor. Changed defaults to more common values.

  • Added a plotDots() function to create a Seurat-style dot plot.

  • Dropped default nmads= to 3 in isOutlier().


Changes in version 1.2.0

  • cxds performance improvement

  • Added heuristics to estimate number of doublets


Changes in version 0.99.7

  • Changed sapply to vapply in utility-function.

Changes in version 0.99.6

  • Changed the link from Seurat to Seurat-class.

Changes in version 0.99.5

  • Fixed error introduced through merge conflict.

Changes in version 0.99.4

  • Fixed typos in vignettes. - Added explanation of ggplot connection to vignettes. - Added explanation for interactivity in iSEE to vignette. - Fixed global variables. - Fixed documentation in plot_hexbin_gene. - Reformatted news. - Added packages to suggests in description.

Changes in version 0.99.3

  • Minimal functioning package created. - Mostly compliant with BiocCheck::BiocCheck() and goodpractice::goodpractice().


Changes in version 1.1.6

  • Accepts DelayedArray, HDF5Array and dgCMatrix inputs in the slots of input SCE objects. - Significant speed optimisation on scSEGIndex and add BiocParallel support. - Updated scSEGIndex references after publication. - scMerge now has the svd_k input that controls the number eigenvectors needed in the RUV step to allow fast approximation for large dataset. - Now using BiocSingular to manage all SVD components. - Now automatically remove zeroes in the rows and columns of the SCE.

Changes in version 1.1.5

  • Adding version restrictions on S4Vectors and SingleCellExperiment dependent packages.

Changes in version 1.1.4

  • plot_igraph would allow suppression of igraph output during unsupervised scMerge

Changes in version 1.1.3

  • Column name must be non-NULL and without duplicates

Changes in version 1.1.2

  • Resolved problems with only a single linking cell-type across multiple batches

Changes in version 1.1.0

  • Accepted by Bioconductor


Changes in version 0.99.0 (2019-09-13)

  • Submitted to Bioconductor


Changes in version 1.14.0

  • Removed deprecated approximate= and pc.approx= arguments.

  • Removed deprecated batch correction functions.

  • Added option to pairwiseTTests() for standardization of log-fold changes.

  • Changed default BSPARAM= to bsparam() in quickCluster(), denoisePCA(), doubletCells() and build*NNGraph().

  • Added the pairwiseBinom() function for pairwise binomial tests of gene expression.

  • Renamed output fields of pairwiseWilcox() to use AUC for less confusion. Added the lfc= argument to test against a log-fold change.

  • Added the fitTrendVar(), fitTrendCV2(), modelGeneVar(), modelGeneVarWithSpikes(), modelGeneCV2(), modelCV2WithSpikes(), fitTrendPoisson() and modelGeneVarByPoisson() functions to model variability.

  • Deprecated the trendVar(), technicalCV2(), improvedCV2(), decomposeVar(), trendVar(), testVar(), makeTechTrend(), multiBlockVar() and multiBlockNorm() functions.

  • Modified combineVar() to not weight by residual d.f. unless specifically instructed.

  • Added the combineCV2() function to combine separate CV2 modelling results.

  • Added the test.type= argument in findMarkers() to switch between pairwise DE tests. Added the argument to easily include row metadata in reordered tables. Deprecated overlapExprs(), which is replaced by type=”wilcox” in findMarkers().

  • Added the getTopMarkers() function to easily retrieve marker lists from pairwise DE results.

  • Added the getTopHVGs() function to easily retrieve HVG sets from variance modelling results.

  • In all functions that accept a block= argument, any level of the blocking factor that cannot yield a result (e.g., due to insufficient degrees of freedom) will now be completely ignored and not contribute to any statistic.

  • Added the getDenoisedPCs() function for general-purpose PCA-based denoising on non-SingleCellExperiment inputs. Converted denoisePCA() to a normal function, removed the method for ANY matrix. Dropped max.rank= default to 50 for greater speed in most cases.

  • Added the calculateSumFactors() function for general-purpose calculation of deconvolution factors on non-SingleCellExperiment inputs. Converted computeSumFactors() to a normal function, removed the method for ANY input. Auto-guess min.mean= based on the average library size.

  • Deprecated all special handling of spike-in rows, which are no longer necessary when spike-ins are stored as alternative experiments.

  • Deprecated general.use= in computeSpikeFactors(), which is no longer necessary when spike-ins are stored as alternative experiments.

  • Deprecated parallelPCA(), which has been moved to the PCAtools package.

  • Modified clusterModularity() to return upper-triangular matrices, fixing a bug where the off-diagonal weights were split into two entries across the diagonal. Added the as.ratio= argument to return a matrix of log-ratios. Renamed the get.values= argument to get.weights=.

  • Simplified density calculation in doubletCells() for greater robustness.

  • Added a method=”holm-middle” option to combinePValues(), to test if most individual nulls are true. Added a min.prop= option to control the definition of “most”.

  • Added a pval.type=”some” option to combineMarkers(), as a compromise between the two other modes. Added a min.prop= option to tune stringency for pval.type=”some” and “any”.

  • Added the getClusteredPCs() function to provide a cluster-based heuristic for choosing the number of PCs.

  • Added the neighborsTo*NNGraph() functions to generate (shared) nearest neighbor graphs from pre-computed NN results.

  • Switched to using only the top 10% of HVGs for the internal PCA in quickCluster().


Changes in version 1.2.0

  • goenrich, meshenrich, reactomeenrich, doenrich, ncgenrich, and dgnenrich in cellCellReport are added

  • A bug related in sparse matrix in cellCellSetting is fixed

  • All the vignettes are updated

  • A vignette for reanalysis of the results of scTensor is added

  • Some bugs are fixed


Changes in version 0.99.0

  • Package released


Changes in version 1.26.0


  • new function seqAddValue()


  • RLE chromosome coding in seqBED2GDS()

  • change the file name “vignettes/R_Integration.Rmd” to “vignettes/SeqArray.Rmd”, so vignette("SeqArray") can work directly

  • correct Estimated remaining Time to Complete (ETC) for load balancing in seqParallel()


  • seqBED2GDS(, verbose=FALSE) should have no display


  • use a svg file instead of png in vignettes

Changes in version 1.24.2


  • add the compiler information in seqSystem()

  • new arguments ‘.balancing’, ‘.bl_size’ and ‘.bl_progress’ in seqParallel() for load balancing


  • improve unix forking processes for load balancing in seqParallel()


  • fix seqSummary() when no phase data


Changes in version 1.8.0


  • The Python implementation of profile creation has been deprecated

  • SNV profiles are now stored as data frames, rather than GRanges objects

  • The create_profile function now now reads profiles into memory, instead of storing them on disk. De-duplication and removal of mitochondrial variants is now also performed at this stage

  • The create_profiles function now returns a list of data frames

  • A new function, write_profile, can write profiles to disk

  • The read_profile function now reads profiles without performing any de-duplication or removing mitochondrial chromosomes

  • The compare_profiles, compare_many and list_variants functions now converts input profiles to GRanges internally

  • Keep the FILTER column in created SNV profiles

  • Add a check for the creation of zero-variant profiles

  • Add a check for the existance of the specified input samples

  • Removal of non-standard chromosomes and variant de-duplication is now optional, and filtration documentation has been extended


Changes in version 1.15.1


  • Added new fields created_by, created_on, and modified_on to the Project class following the recent API improvements. This enables better project filtering when querying projects. See the vignette for details.


Changes in version 0.99.2

  • Clean some formating issues

Changes in version 0.99.0 (2019-05-16)

  • Submitted to Bioconductor


Changes in version 1.1.0 (2019-10-23)

  • Initial version

Changes in version 0.99.20 (2019-10-22)

  • Submitted to Bioconductor - Major changes - used HDF5 file to read and write the matrix in batches - data stored in ExperimentHub


Changes in version 1.11.1

  • ignore mutations on edges of chromosomes


Changes in version 1.11.1 (2019-10-13)

  • Fix C++ bug.


Changes in version 1.8.0

  • Added altExp() and related methods to get and set alternative Experiments.

  • Added the splitAltExps() utility to create many alternative Experiments at once.

  • Added the swapAltExp() utility to swap between main and alternative Experiments.

  • Deprecated isSpike(), spikeNames() and related arguments for handling spike-ins, in favor of representing spike-ins as alternative Experiments.

  • Deprecated type= in sizeFactors() and sizeFactorNames(), which were previously only required to store size factors for spike-ins.

  • Internal change to the representation of reducedDims() to streamline subsetting and combining.


Changes in version 1.5.1

  • added link to the F1000research published workflow that demonstrates usage of singscore on a real dataset ( - allow labelling of samples on dispersion plots (plotDispersion) in a similar manner to landscape plots (projectScoreLandscape)


Changes in version 1.1.10

  • Allow user to choose whether to show tip labels in the plot functions

Changes in version 1.1.9

  • Add progress bar for the resampling and summarizing step of the function ‘multiFixationSites’

Changes in version 1.1.8

  • Add ‘plot’ function for directly plotting the return of ‘extractSite’

  • Apply resampling method for ‘multiFixationSites’

  • The function ‘fixationSites’ applys the old ‘multiFixationSites’

Changes in version 1.1.7

  • Add functionality ‘extractSite’ to allow accessing a single site from the result of ‘fixationSites’ and ‘multiFixationSites’

Changes in version 1.1.6

  • Add functionality ‘setSiteNumbering’ to allow manipulating the reference of site numbering

Changes in version 1.1.5

  • Move similarity calculation to ‘addMSA’. This will slow the function

Changes in version 1.1.4

  • Use total number of tips divided by number of nodes as ‘minEffectiveSize’

  • Ignore invariant sites when search for fixation sites

Changes in version 1.1.3

  • Expose ‘searchDepath’ for ‘multiFixationSites’

Changes in version 1.1.2

  • Use ‘multiFixationSites’ for both single and multiple fixation sites

Changes in version 1.1.1

  • Bug fix: Error when adding new result in ‘fixationSites’


Changes in version 1.20.0

  • a leading tilde in the file path is allowed in snpgdsGDS2BED()

  • change the file name “vignettes/SNPRelateTutorial.Rmd” to “vignettes/SNPRelate.Rmd”, so vignette("SNPRelate") can work directly

Changes in version 1.18.1

  • support long vector in snpgdsIBDSelection()


Changes in version 0.99.8

  • added unit test - createTrackll() and msd() in this version

Changes in version 0.99.7

  • fixed BiocCheck error checkForSupportSiteRegistration - unblocked maintainer email account

Changes in version 0.99.6

  • fixed BiocCheck warning - revised sojourner.r

Changes in version 0.99.5

  • fixed various issues raised in review for Bioconductor submission.

Changes in version 0.99.4

  • fixed Linux build error and removed extraneous .pdf files

Changes in version 0.99.3

  • fixed git clone issues for Windows

Changes in version 0.99.2

  • reduced time runing for examples

Changes in version 0.99.1

  • changed system.time() format

Changes in version 0.99.0

  • Submitted to Bioconductor


Changes in version 0.99.0

  • Submitted to Bioconductor


Changes in version 1.1

  • (1.1.9) Added example on how to customize resolutions and assignment function to vignette

  • (1.1.8) Changed UI to make better use of screen real estate

  • (1.1.7) Added “top genes” barplot in array plot tooltip

  • (1.1.6) Scoring is now based on normalized distances

  • (1.1.5) Added interactivity to array plots

  • (1.1.4) Increased numerical stability

  • (1.1.3) Added log messages

  • (1.1.2) Performance improvements

  • (1.1.1) Added “top features” barplot in cluster tree tooltip


Changes in version 1.10.0 (2019-10-20)

  • Add the (experimental) Kersplat simulation model. This model incorporates a gene network and other useful features.

  • Refactor the summariseDiff function and add the KS statistic.

  • Add variable gene correlation plot to compareSCEs and violins to other comparison plots.

  • Check for counts assay when estimating from SingleCellExperiment objects.

  • Fix where simpleSimulate stores parameters.

  • Fix bugs where parameters were not being passed correctly in BASiCSEstimate and sparseDCEstimate.

  • Replace the sc_example_counts dataset from scater with the mockSCE function.

  • Tidy and improve estimation function examples and add checks for suggested packages.

  • Various fixes for compatibility with updates to other packages.


Changes in version 1.0.0 (2019-10-01)


  • Supports tidy grammar for ‘select’, ‘filter’, ‘mutate’ and ‘%>%’ pipe.

  • Supports representation and saving of MySQL database tables.

  • Supports lazy cross-MySQL database table aggregations, such as join, union, rbind, etc.


  • Fixed bugs for single square bracket subsetting with key column(s).

Changes in version 0.99.0 (2019-04-05)

  • Submitted to Bioconductor


Changes in version 1.1.3 (2019-10-17)

  • GeneEx added to inst

Changes in version 1.1.2 (2019-10-17)

  • Time series option added to sracipeSimulate

  • Minor bug fixes


Changes in version 1.1.1

  • parseDoc did not handle doctitles correctly, fixed

  • DocSet() did not succeed in 1.0+, new defaults added to allow this

  • parseDoc had presumptive elimination of rownames-associated columns generated by read.csv, which was removed in 1.1.1

  • increased testing for DocSet updating via parseDoc

  • added cautions about parseDoc updating to man page

  • for 1.1.2, adding title as a string into searchable ‘token’ set


Changes in version 2.0


  • 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

Changes in version 1.15.4

  • edit colum name for the result table

  • skip the roc analysis once the number of samples in any groups was less than 5.

Changes in version 1.15.3

  • odds.ratio. Add the ratio of the odds of an event occurring in one group (A) to the odds of it occurring in reference group (B), such as odds_of_AtoB.


Changes in version 1.1.6 (2019-09-23)

  • DotBracketDataFrame refactored to split concept from data implementation

  • fixed sequence column not returned when calling getBasePairing with a StructuredXStringSet


Changes in version 2.3.7 (2019-09-18)

  • Bug fix: update call on tidyr::gather in tidyUpMetrics to work after bump in tidyr version to 1.0.0 on CRAN

Changes in version 2.3.6 (2019-09-06)

  • Replace sc_example_counts dataset from scater with call to scater::mockSCE

  • Fix error thrown by show.BDData when dataset is a list

Changes in version 2.3.5 (2019-06-22)

  • Fix index title for “Feature: Error Handling” vignette

  • Replace Rd references to rlang::quos with rlang:quotation topic page since aliasing appears to be causing warnings on Windows build

  • Update pkgdown site with latest devel docs

Changes in version 2.3.4 (2019-06-18)

  • Fix scRNAseq simulation case study vignette to work with changes in scRNAseq package

  • Add code examples and import statements to pass BiocCheck

  • Update pkgdown site with latest devel docs

Changes in version 2.3.3 (2019-06-14)

  • Added NEWS file to track changes

  • Incorporated major updates to package documentation and vignettes

  • Added pkgdown site


Changes in version 1.16.0


  • Some improvements to the SummarizedExperiment() constructor (see commit 0d74843c)

  • Support ‘colData(SummarizedExperiment) <- NULL’ to clear colData


  • All the arguments of the SummarizedExperiment() constructor are now visible (no more ellipsis) and have default values. So tab completion works. See commit 0d74843c

  • The dimnames on the individual assays of a SummarizedExperiment derivative now can be anything (see issue #25 for the details)


  • Some fixes to the SummarizedExperiment() constructor (see commit 0d74843c)

  • Address all.equal() false positives on SummarizedExperiment objects (see issue #16 for the details)


Changes in version 1.1.3 (2019-05-08)

  • Revise dinu_to.keep algorithm, enhance performance.

Changes in version 1.1.2 (2019-05-08)

  • Bug fix: “dinu_to” ifelse issue in get_optimal_codon.

Changes in version 1.1.1 (2019-05-06)

  • Bug fix: “dinu_to” fix wrong result with “keep == TRUE” parameter.

Changes in version 1.1.0 (2019-05-06)

  • Bump


Changes in version 0.1.0

  • Submit to Bioconductor


Changes in version 1.42.0


  • As announced in version 1.40.0, the graphical user interface is gone for good (i.e., defunct). The source code is available in my github repository.


  • The most interesting feature is the introduction of a custom CDF-4 format which hold the same data as a normal CDF-3 (as exported by the software vendors), but allows faster read-access (specially for plotting) and compression (among other features). This is at the cost of compatibility as the CDF-4 files are unlikely to be used outsied TargetSearch

  • A new baseline correction method based on quantiles around a retention time window. In addition, the new CDF-4 file format allows storing of baseline-corrected values so it is not needed to recompute the baseline each time like in older TargetSearch versions.

  • New function to transform to nominal mass. Some GC instruments export CDF not in nominal mass format (some even export high mass accuracy). Formely, this type of files were not supported and TargetSearch would refuse to process them. Now, all types of mass accuracy are allowed, obviously at the cost of losing that accuracy.


  • Mostly code refactoring and house-keeping.


Changes in version 1.6.0

New features

  • oncoPrintTCGA: Create an oncoPrint visualization for mutation data
  • Support aliquot_ids as input to UUIDtoBarcode function - Additional sections in the vignette: CpGtoRanges, UUIDtoBarcode for aliquot_ids
  • TCGAprimaryTumors allows users to select all primary tumors for a given curatedTCGAData MultiAssayExperiment object (@vjcitn)

Minor changes and bug fixes

  • Now merging clinical data using both rows and columns in mergeColData - Added informative error when query results are empty in UUIDtoBarcode - Updates to makeGRangesListFromExonFiles to use S4Vectors::splitAsList (@hpages)


Changes in version 0.99.7

  • Add options to improve feature selections in reference-free deconvolution.

Changes in version 0.99


  • Initial release.


Changes in version 099.1


  • changed function behvaiour in the whole package from call-by-ref to call-by value. Adjusted accordingly all examples and the vignette.


  • depends now on ProtGenerics from which it uses ‘mz’

  • exchanged various print() with message()


Changes in version 1.1.4 (2018-12-29)

  • Prepare for Bioconductor submission.

Changes in version 1.1.3 (2018-11-14)

  • Add “full” output option for limma_confects and normal_confects, which adds se, df, and fdr_zero columns.

Changes in version 1.1.2 (2018-06-30)

  • Add DESeq2 support.

  • Code to do with non-linear effect sizes has been move to the “ql” branch on github, pending publication of the basic method and a possible rethink and use of a simpler method.

Changes in version 1.1.1 (2019-09-20)

  • Update citation information.

Changes in version 1.0.1 (2018-02-04)

  • Initial release.


Changes in version 1.7

  • New version for Bioc 3.10 (devel)

Changes in version 1.7.1

  • Remove NEWS file (just keep - Never remove “AgcTarget” column from colData DataFrame. - Strip white spaces from ScanHeadsman output. - Defunct defaultMs1Settings and defaultMs2Settings. They will be removed in 3.11 [2019-06-19].

Changes in version 1.7.2

  • Add readTopDownSet(…, conditions=”ScanDescription”) as a new way to read scan conditions (see #80/#81) [2019-08-08].


Changes in version 3.13.3

  • defunct the following functions: tpp2dPlotCCRGoodCurves, tpp2dPlotCCRAllCurves, tpp2dPlotCCRSingleCurves, tpp2dEvalConfigTable, tpp2dRemoveZeroSias, tpp2dReplaceColNames, tpp2dCreateCCRConfigFile

Changes in version 3.13.2

  • Revise vignette

Changes in version 3.13.1

  • Avoid warnings due to factor/character conversions in vignette


Changes in version 1.1.0 (2019-05-06)

  • Carry-over detection now works via a LDA model


Changes in version 1.21.18

  • update NEWS file from “CHANGES IN VERSION” to “Changes in version”.

Changes in version 1.21.17

  • remove google scholar in vignette.

Changes in version 1.21.16

  • Try to avoid the error introduced by BiocStyle: Invalid Parameter - /figure-html.

Changes in version 1.21.15

  • Add google scholar in vignette.

Changes in version 1.21.14

  • Update the citation in readme file.

Changes in version 1.21.13

  • Fix a typo in plotLollipops.

Changes in version 1.21.12

  • setTrackXscaleParam accept position attribute.

Changes in version 1.21.11

  • set rescale of lolliplot by precentage.

Changes in version 1.21.10

  • fix the bug of score is NumericList.

Changes in version 1.21.9

  • accept negative values for bigwig files.

Changes in version 1.21.8

  • update legend method.

Changes in version 1.21.7

  • fix the label

Changes in version 1.21.6

  • add sample code of Proteins API.

Changes in version 1.21.5

  • fix the bug that lollipop stem is too long.

Changes in version 1.21.4

  • add shape for lolliplot.

Changes in version 1.21.3

  • add shinyApp video.

Changes in version 1.21.2

  • add citation.

Changes in version 1.21.1

  • fix the bug if condiction with multiple logical values.


Changes in version 0.99.9902 (2019-10-23)

  • tradeSeq’s fitGam and evaluateK functions do not have a seed argument anymore, as per Bioconductor’s guidelines. Users are encouraged to set the seed manually with the set.seed function before running those functions for reproducibility purposes.

Changes in version 0.99.47 (2019-09-02)

  • tradeSeq now provides singleCellExperiment output o fitGam now accepts a slingshotDataSet object as input o All tests and plotting functions accept a singleCellExperiment object that contain tradeSeq output

Changes in version 0.99.0 (2019-06-22)

  • Submitted to Bioconductor

Changes in version 0.9.0 (2019-03-15)

  • Reformatted to fulfill Bioconductor guidelines


Changes in version 1.2.1

  • updated author list


Changes in version 1.9.3

  • add citation information (2019-10-05, Sta) - rename phyPML to as.treedata.pml (2019-10-01, Tue) - as.phylo method for igraph (only work with tree graph) (2019-09-28, Sat)

Changes in version 1.9.2

  • nodeid and nodelab methods for converting between node number and labels (2019-08-09, Fri) - parent, ‘ancestor, child, offspringandrootnodemethods fortreedata` (2019-08-07, Wed) - read.mega_tabular to parse MEGA Tabular output (2019-07-16, Tue) - read.mega to parse MEGA NEXUS (actually BEAST compatible)

Changes in version 1.9.1

  • rename_taxa now use 1st column as key and 2nd column as value by default (2019-05-28, Tue) - enable tree_subset to specify group_name and enable to incorporate root.edge by setting root_edge = TRUE (2019-05-27, Mon) - full_join method for phylo object (2019-05-22, Wed) - redefined root method to wrape ape::root.phylo for compatibility (2019-05-20, Mon) -


Changes in version 1.5.3 (2019-08-25)

  • added get.tRNAprecursor function to retrieve tRNA precursor sequences in combination with genomic sequences

  • fixed typos in the NEWS file

  • updated tRNAscan example file for human (the high confidence set is now included)


Changes in version 1.11.12

  • Updates to include 3’-read capturing from bam input files and data structures to allow ignoring spurious TSSs.

  • Added capabilities for sorting by strand (and seq/TSS) for TSS merging.

  • Made a change leading to a substantial speed-up of mergeSampleData().

  • Added qname to saved columns from .bam input.

  • Minor changes to writeTSR() and writeTSS().

  • Rewrite to mergeSampleData).

  • Improvements to loadTSSobj().

  • Necessary updates to the Singularity recipe to reflect the above changes.


Changes in version 1.4.0

  • tximeta will now pull down RefSeq seqinfo, using the dirname() of the GTF location, and assuming some consistency in the structure of the assembly_report.txt that is located in the same directory. Needs more testing though across releases and organisms.

  • expanded caching of ranges to exons and genes as well. Exons in particular take a long time to build from TxDb, so this saves quite a lot of time.

  • new ‘addExons’ function will add exons to trancript-level summarized experiments, by replacing transcript GRanges with exon-by-transcript GRangesList. Purposely designed only for transcript-level, see note in ?addExons

  • tximeta now also caches the transcript ranges themselves, rather than just the TxDb. This shaves extra seconds off the tximeta() call!

  • add ‘skipSeqinfo’ argument, which avoids attempting to fetch chromosome information (from UCSC) if set to TRUE.


Changes in version 1.14.0

  • Alevin count and inferential variance can be imported now ~40x faster for large number of cells, leveraging C++ code from the fishpond package (>= 1.1.18).

  • Alevin inferential replicates can be imported (also sparse). To not import the inferential replicates, set dropInfReps=TRUE.


Changes in version 1.3.22


  • New stand alone functions that don’t require shiny app : bsj_to_circRNA_sequence() and bsj_fastq_generate()


  • BUG fix: All warnings in bioconductor now resolved

  • BUG fix: Added dependencies to DESCRIPTION to allow automatic install

Changes in version 1.3.1


  • BUG fix: Fixed code in Compatible_Annotation_DBs examples that was causing error in bioconductor builds.


Changes in version 1.4.0


  • scan_sequences(…, threshold.type) option: ‘logodds.abs’. Allows the exact threshold scores to be provided.

  • compare_motifs() option: ‘min.position.ic’. Prevent low-IC positions in an alignment from contributing to the final alignment score.

  • compare_motifs() option: ‘score.strat’. Instruct the function how to deal with individual column scores in an alignment. This is also replaced the old way of choosing between sum and mean via prepending an ‘M’ to the metric name. Strategies for combining column scores include: sum, arithmetic mean, geometric mean, median, Fisher Z-transform, and weighted means.

  • Motif comparison metrics: average log-likelihood ratio, squared Euclidean distance, Hellinger distance, Bhattacharyya coefficient, Manhattan distance, lower limit average log-likelihood ratio, weighted Euclidean distance, weighted Pearson correlation coefficient.

  • compare_columns() utility: Compare two 1d numeric vectors using the comparison metrics from compare_motifs().

  • compare_motifs() option: ‘’. Generate an output report when ‘’ is provided, showing motif alignments of top matches.

  • get_scores() utility: Extract all possible scores from a motif.

  • filter_motifs(): Filter using the ‘extrainfo’ slot.

  • MotifComparisonAndPvalues.pdf vignette: the comparisons and P-values sections have been moved from AdvancedUsage.pdf to their own vignette. Higher order motifs, enrichment and run_meme() usage sections have been moved to SequenceSearches.pdf.


  • Removed ‘random’ shuffling method.

  • Using RcppThread instead of BiocParallel in several functions: compare_motifs(), create_sequences(), get_bkg(), motif_pvalue(), scan_sequences(), shuffle_sequences(). This means parallelization can occur within C++ code which is much faster than having to jump between R and C++. Currently motif_peaks(), read_motifs() and write_motifs() are the only remaining functions which offer optional BiocParallel usage.

  • Many performance improvements to functions relying on internal C++ code. Several internal R functions have been replaced with C++ versions.

  • Changed behaviour of make_DBscores() and motif comparison P-values. Re-calculated internal P-value databases.

  • For merge_motifs(…, use.type): now only accepts ‘PPM’.

  • When comparing all motifs to all motifs with any method in compare_motifs(), the diagonal entries now properly show the max/min possible similarity/distance scores.

  • New internal merge_motifs() implementation. This also fixes a previous bug with incorrect PPM averaging.

  • read_homer(): the logodds score is converted to a P-value.

  • motif_pvalue(): New score calculator. Exact scores are still calculated the same (but with a faster C++ function), but approximate scores are now calculated by randomly generating score distributions from size ‘k’ motif score blocks.

  • motif_pvalue(): Added a safety check when trying to use this function with large motifs. Will throw a warning when nrow(matrix)^k > 1e8 and reduce k accordingly before continuing.

  • Adjusted P-value calculation in motif_peaks() to not display Pval = 0 so easily by instead estimating a normal distribution from random peaks.

  • convert_type(): make sure not to leave any zeros in bkg vector when a pseudocount greater than zero is used.

  • enrich_motifs(): split up ‘hits’ and ‘positional’ resuts into their own data.frames.

  • Replaced several instances of cat() with message() for printing progress updates.

  • Positional tests have been removed from enrich_motifs(). See motif_peaks() for testing motif-sequence positional preferences.

  • In read_meme(): E-values are now additionally stored in the extrainfo slot. This is to preserve E-values smaller than the R double precision limit.

  • In read_transfac(): Matrix values are rounded, to prevent errors when reading in matrices with non-integers.

  • Update JASPAR2018_CORE_DBSCORES with new compare_motifs() methods and params.

  • universalmotif print() method now returns the object invisibly, instead of NULL.


  • read_meme() will now properly parse background letter frequencies which span more than one line.

  • convert_motifs() will not error-out when trying to convert a PFMatrix with a family character vector longer than one.

  • Fixed P-value calculation when importing HOMER motifs. Peviously it would simply assume the log threshold value was the P-value. Now motif_pvalue() is used to properly calculate a P-value.

Changes in version 1.2.1


  • Mispelled variable in enrich_motifs()


Changes in version 1.15.8

  • Replace cat() with message()

  • add quiet option to a few functions

  • dream() does not call eBayes() when lmFit is used

Changes in version 1.15.7

  • Official release to development branch

Changes in version 1.15.6

  • fix convergence errror when recycling parameters values from first gene

  • add column z.std and F.std to topTable

Changes in version 1.15.4

  • Add error message when scale of fixed effects causes a problem

Changes in version 1.15.3

  • Try changing order of eBayes

Changes in version 1.15.2

  • Update vignette

Changes in version 1.15.0

  • Push changes to Bioconductor devel


Changes in version 0.99.8

  • saveVariantExperiment returns newly generated VariantExperiment object by calling loadVariantExperiment


Changes in version 0.99.42

  • remove environment signature in merge_enrich_terms

Changes in version 0.99.41

  • keep require(“topGO”) in create_topGOdata method

Changes in version 0.99.40

  • add attachNamespace(“topGO”) instead require(“topGO”) in create_topGOdata method for prevent build check warnings

Changes in version 0.99.39

  • check gene background in merge_enrich_terms upgrade

Changes in version 0.99.38

  • show method for GO_cluster print bug correction

Changes in version 0.99.37

  • add environment option for merge_enrich_terms

Changes in version 0.99.36

  • annotate id argument signature with “NULL”

Changes in version 0.99.35

  • README update

Changes in version 0.99.34

  • README update (download from Bioconductor and forgeMIA gitlab)

  • add require(“topGO”) in create_topGOdata method

Changes in version 0.99.33

  • merge_enrich_terms exemple update.

Changes in version 0.99.32

  • GOterms_heatmap GO.clusters column convert to character in order to prevent data.table merge error.

Changes in version 0.99.30

  • ViSEAGO citation update


Changes in version 0.99.6 (2019-10-28)

  • P-value reproducibility feature: o Now using nextRNGstream to generate independent seeds for each gene o Setting the seed (with set.seed()) only in .testWass o Removed use of seeds and the seed argument everywhere in WassersteinTest.R

Changes in version 0.99.5 (2019-10-14)

  • P-value reproducibility feature for the permutation procedure: o as described here, a seed argument has been added to the functions wasserstein.test and

  • Fix: o Checks for the validity of the “method” argument in and wasserstein.test that have become unnecessary with the use of match.arg have been removed

Changes in version 0.99.4 (2019-10-01)

  • Fixes: o Fixed a bug in .wassersteinTestSp where the names in the output vector were changed unexpectedly and added a test for this bug

  • Bioc Review I: o vignette: Added SessionInfo() to each vignettes o vignette/README: Changed the install instructions o unit tests: removed unused and commented-out code o R: Changed to switch statements to dispatch different methods in wasserstein.test and o R: Changed the order of arguments in wasserstein.test and and added default methods o R: wasserstein.test.sp has been renamed to .wassersteinTestSp; wassersetin.test.asy has been renamed to .wassersteinTestAsy -> both are now private o R/NAMESPACE: removed the previously private functions .fishersCombinedPval and .combinePVal from NAMESPACE by removing @export decorators

Changes in version 0.99.3 (2019-08-30)

  • Fixes: o Fixed a bug in wasserstein.test that led to NAs during gpd fitting o Fixed a bug in .gpdFittedPValue that led to NAs during gpd fitting

  • Modified tests and added new tests to reproduce the bugs and challenge the fixes

  • Change in squared_wass_decomp: If the standard deviation of one condition is 0, quantile-quantile corelation is not computed, since the shape term would be zero anyway. Previously, NAs were produced in some cases.

  • Swapped ‘true’ and ‘test’ values in call to .relativeError

Changes in version 0.99.2 (2019-08-27)

  • Changes to DESCRIPTION: o removed the “Maintainer” field in favor of “Authors@R” to address build warnings o Changed roles: ‘cre’ = Maintainer, ‘aut’ = author

Changes in version 0.99.0 (2019-08-27)

  • Version Bump for BioC Submission

  • Vignettes: o Added introduction section and sessionInfo() to main vignette o Added link to main vignette

  • Code style: o renaming where possible to conform with BioC convention o file renaming to uniform upper camel-case o comments edited o additional helper functions introduced

Changes in version 0.2.8 (2019-08-19)

  • R Code redesign: o new unexported functions to help avoiding repeats o Redesign of all single-cell methods as S4 methods that are also capable to take SingleCellExperiment objects as input o Bioc-style function naming implemented o Now using the cpp decomp functions instead computations in R

  • Output names changed

  • Descriptions changed to match altered code

Changes in version 0.2.7 (2019-08-13)

  • Bug fix in interval table / wasserstein_metric causing runs to fail

  • Tests for that bug added

Changes in version 0.2.6 (2019-08-08)

  • Fix in wasserstein_metric where a result was squared

  • Work on CPP implementations: o Rework on the quantile computation in CPP that now produces more accurate approximations o Removal of obsolete parameter “p” in approximation functions

  • Now using wasserstein_metric in two sample testing procedures

Changes in version 0.2.5 (2019-08-06)

  • Fixing R CMD check size error by reducing package size: Brownian bridge distribution, used in the asymptotic implementation of wasserstein.test now is downloaded into a local cache during the first run of wasserstein.test. From there it is loaded in all subsequent runs.

  • Fixed Bug in wasserstein.test

Changes in version 0.2.4 (2019-07-31)

  • Added Vignettes for wasserstein distance, wasserstein.test, and

  • Fixed examples and unparsable comments

  • Adressing Notes of R CMD BiocCheck …: o Removed use of 1:… in favor of seq() or seq_len() o Removed use of set.seed(), which changed the signature of testing functions o Using 4 spaces instead of tabs and multiples of 4 spaces for indentation

Changes in version 0.2.3 (2019-07-29)

  • Adressing Notes and Warnings of R CMD check …: o Reverted changes of BiocParallel from Import to Enhancement o Removed redundant imports of arm, eva, BiocParallel o Removed CITATION, as it could be formatted to satisfy the checks without naming a paper

Changes in version 0.2.2 (2019-07-29)

  • Added this NEWS file for change announcements

  • Added a file inst/CITATION that is supposed to hold the citation (after publication)

  • DESCRIPTION file: o Title and Description improved and shortened o Added bioView Categories: StatisticalMethod, SingleCell, DifferentialExpression o Added BugReports and URL in DESCRIPTION o Changed the former Import BiocParallel to an Enhancement

  • Changes to NAMESPACE: o Explicitly declare the functions that should be imported from the packages arm, eva, and BiocParallel

  • Changed all code files in the package to have max. 80 Character per line


Changes in version 3.7.5

  • Remove xcmsMSn vignette (based on old xcms).

Changes in version 3.7.4

  • mzClust correspondence analysis: check and fix missing values in column mz of the peaks matrix (issue #416).

Changes in version 3.7.3

  • plot type = “XIC” on an XCMSnExp object will draw rectangles indicating the identified chromatographic peaks.

  • Add a vignette describing LC-MS/MS data analysis with xcms.

Changes in version 3.7.2

  • Fix documentation (issue #401).

  • Add support for SWATH data analysis.

Changes in version 3.7.1

  • Add correlate method for Chromatogram objects.

  • Add parameter lwd to plotAdjustedRtime.

  • Add align method for Chromatogram objects.

  • Add findChromPeaksIsolationWindow to enable chromatographic peak detection in isolation windows.

  • Fix issue in chromPeakSpectra with method = “signal”.

  • chromPeakSpectra and featureSpectra return now MS2 spectra with an precursor m/z >= mzmin, <= mzmax and retention time >= rtmin, <= rtmax.

  • Improve performance of chromPeakSpectra and featureSpectra.


Changes in version 1.7.5 (2019-10-08)

  • Changed default of zinbwave to observationalWeights=FALSE to speed up computations when weights are not needed.

  • Added argument zeroinflation = TRUE: when set to FALSE a negative binomial model is fit.

  • Removed dependence on the copula package to avoid depending on gsl.

NEWS from new and existing Data Experiment Packages


Changes in version 0.99.15 (2019-06-06)

  • Updated vignette to remove excessive printing of data objects

Changes in version 0.99.14 (2019-05-08)

  • bioc4: Added non-eval code chuck to vignette for installing package

Changes in version 0.99.13 (2019-05-08)

  • Changes based on feedback from Bioconductor review

  • bioc1: Added ‘BugReports:’ field to DESCRIPTION file

  • bioc2: Removed reference to ‘remotes’ pkg from vignette

  • bioc3: Added details to vignette for alt approach to load resource from ExperimentHub

Changes in version 0.99.12 (2019-05-07)

  • Explicitly add metadata param documentation to each Rd

  • Update description in DESCRIPTION file

Changes in version 0.99.11 (2019-05-06)

  • Fixed typo in one doc reference again

Changes in version 0.99.10 (2019-05-06)

  • Added metadata parameter to docs

  • Changed examples to just load metadata

Changes in version 0.99.9 (2019-05-06)

  • Added running examples to all docs

  • Fixed typo in one doc reference

Changes in version 0.99.8 (2019-05-04)

  • Added documentation for all data objects with roxygen2 code in R files

Changes in version 0.99.7 (2019-04-24)

  • Changed NEWS message for 0.99.6 to prevent BiocCheck warning

Changes in version 0.99.6 (2019-04-24)

  • Changed T/F to TRUE/FALSE in make-data Rmd files

  • Changed how object class is checked in plotMethodRank code

Changes in version 0.99.5 (2019-04-23)

  • Deleted and untracked .Rproj file

Changes in version 0.99.4 (2019-04-23)

  • Removed .Rproj file from git tracking

Changes in version 0.99.3 (2019-04-23)

  • Fixed typo in DESCRIPTION file

  • Added NAMESPACE file

Changes in version 0.99.2 (2019-04-23)

  • Triggering new build after adding webhook

Changes in version 0.99.1 (2019-04-23)

  • Updating vignette and triggering new build after data have been moved into ExperimentHub

  • Adding CITATION and NEWS files

  • Adding ORCID for authors

Changes in version 0.99.0 (2019-04-09)

  • Submitted to Bioconductor

Changes in version 2.10.0

  • Added data required for proxReg: enhancers.dnase_thurman.0, gene.enh.desc, spline.log_dtss.90ENCODE


Changes in version 0.99.6

  • 19Q3 data
  • New data loading functions

Changes in version 0.99.0

  • Preparing for Bioconductor submission


Changes in version 2.3.4

  • Added a file to track changes to the package.


Changes in version 2.0.0

  • Data package now uses ExperimentHub

  • Objects myBetas, CpGs, tx.hg19, tx.hg38 and tx.mm10 have been retired

  • Objects hg19.generanges, hg19.grt, hg38.generanges, hg38.grt, mm10.generanges and mm10.grt have been added as annotation for extractRanges() and DMR.plot()


Changes in version 2.17


  • ch2locs (retrievable via dsQTL::getSNPlocs) has been changed at about 1850 locations where rs numbers had been associated with hg19 addresses; the dsQTL regions are hg18 as are all the chr2… SNP addresses. Previously the discoverable rs numbers used in the Chicago distribution from had be mapped via SNPlocs…20111119, but now they come directly from the Chicago text file.


Changes in version 1.5.4

  • Add Weber_AML_sim and Weber_BCR_XL_sim datasets

  • Update documentation


Changes in version 0.99.20 (2019-05-30)

  • Submitted to Bioconductor, nearing end of review process

  • See NEWS in MMAPPR2 package for relevant updates


Changes in version 0.99.0 (2019-06-17)

  • Submitted to Bioconductor


Changes in version 0.99.0 (2019-05-30)

  • Submitted to Bioconductor


Changes in version 2016-04-21

  • Initial release for Bioconductor

Changes in version 0.1.0

  • Initial version


Changes in version 1.23.1

  • remove getThermoHelaPRTC function (server down) <2019-10-24 Thu>


Changes in version 0.99.0 (2019-04-29)

  • Submitted to Bioconductor

Changes in version 0.99.10

  • Added gene expression demo datasets.


Changes in version 2.0.0

  • Added lots of new ExperimentHub datasets, inspired by simpleSingleCell use cases and Martin Hemberg’s website.

  • All outputs are now SingleCellExperiment instances with spike-ins stored as alternative experiments.

  • Deprecated inbuilt datasets in favor of ExperimentHub equivalents.


Changes in version 1.1.0 (2019-10-23)

  • Initial version

Changes in version 0.99.10 (2019-10-22)

  • Stored data in ExperimentHub

  • Saved LINCS gctx file to hdf5 file in batches

  • Saved cmap databases (cmap, cmap_rank, cmap_expr) to hdf5 files

  • Loaded hdf5 file into R as SummarizedExperiment object

  • hdf5 file includes matrix, rownames and colnames

Changes in version 0.99.0 (2019-04-02)

  • Needed 50Gb memory to load matrix in LINCS gctx file and save as HDF5 backed SE object


Changes in version 0.99.0 (2019-01-08)

  • Submitted to Bioconductor for review

NEWS from new and existing Workflows


Changes in version 1.1.1

  • Better manage transcript version

  • Manage output directory when calls are generated for several libraries

  • Manage transcript version when calls are generated for several libraries

Changes in version 1.1.0

  • Change kmer size of kallisto index from 21 to 15 for libraries with readLength <= 50bp

  • Can choose the output directory

  • By default use a simpler arborescence for the output directory

  • Can use reference intergenic sequences generated by the community

  • Can use custom reference intergenic sequences from a local fastq file


Changes in version 1.1.5

  • Updated main text with suggestions from F1000 reviewers.

  • Added F1000 paper as citation.

  • Slightly updated code examples to be compliant with new Bioconductor release.

Deprecated and Defunct Packages

Twelve software packages were removed from this release (after being deprecated in Bioc 3.9): flowQ, rMAT, TSSi, flowQB, rSFFreader, ProCoNA, spliceSites, DOQTL, NGScopy, SVM2CRM, miRsponge, htSeqTools

Nineteen software are deprecated in this release and will be removed in Bioc 3.11: SNPchip, rHVDM, GenomeGraphs, plateCore, charm, HTSanalyzeR, PathNet, Rchemcpp, exomePeak, flipflop, Pbase, RnaSeqSampleSize, birte, SEPA, CNPBayes, dSimer, mlm4omics, condcomp, brainImageR

Two experimental data packages were removed in this release (after being deprecated in BioC 3.9): PGPC, flowQBData.

Three experimental data packages are deprecated in this release and will be removed in Bioc 3.11: charmData, facopy.annot, allenpvc.

Two annotation packages were removed this release: MafDb.gnomADex.r2.0.1.GRCh38, MafDb.gnomAD.r2.0.1.GRCh38 (they have been replaced with MafDb.gnomADex.r2.1.GRCh38, MafDb.gnomAD.r2.1.GRCh38)

Two annotation packages are deprecated in this release and will be removed in Bioc 3.11: MafDb.ESP6500SI.V2.SSA137.hs37d5, MafDb.ESP6500SI.V2.SSA137.GRCh38