BatchQC
Batch Effects Quality Control Software
Bioconductor version: 3.24 · Package version: 2.9.3
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Samples (-omics, imaging, single cell, etc) often are collected or processed in multiple batches or at different times. This often produces technical biases that can lead to incorrect results in the downstream analysis. BatchQC is a software tool that streamlines batch preprocessing and evaluation by providing interactive diagnostics, visualizations, and statistical analyses to explore the extent to which batch variation impacts the data. BatchQC diagnostics help determine whether batch adjustment needs to be done, and how correction should be applied before proceeding with a downstream analysis. Moreover, BatchQC interactively applies multiple common batch effect approaches to the data and the user can quickly see the benefits of each method. BatchQC is developed as a Shiny App. The output is organized into multiple tabs and each tab features an important part of the batch effect analysis and visualization of the data. The BatchQC interface has the following analysis groups: Summary, Differential Expression, Median Correlations, Heatmaps, Circular Dendrogram, PCA Analysis, Shape, ComBat and SVA.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BatchQC")Details
| Maintainer | Yaoan Leng <leng@bu.edu> |
| Author | Jessica Anderson [aut] (ORCID: <https://orcid.org/0000-0002-0542-9872>), W. Evan Johnson [aut, fnd] (ORCID: <https://orcid.org/0000-0002-6247-6595>), Yaoan Leng [ctb, cre] (ORCID: <https://orcid.org/0009-0002-3957-5250>), Solaiappan Manimaran [aut], Heather Selby [ctb], Claire Ruberman [ctb], Kwame Okrah [ctb], Hector Corrada Bravo [ctb], Michael Silverstein [ctb], Regan Conrad [ctb], Zhaorong Li [ctb], Evan Holmes [ctb], Solomon Joseph [ctb], Howard Fan [ctb], Sean Lu [ctb] |
| License | MIT + file LICENSE |
| URL | https://github.com/wejlab/BatchQC |
| Bug Reports | https://github.com/wejlab/BatchQC/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | BatchEffect, DifferentialExpression, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Normalization, Preprocessing, PrincipalComponent, QualityControl, RNASeq, Sequencing, ShinyApps, Software, Visualization |
| Package Short Url | https://bioconductor.org/packages/BatchQC/ |
Citation
From within R, enter citation("BatchQC"):
Jessica Anderson, W. Evan Johnson, Solaiappan Manimaran. BatchQC: Batch Effects Quality Control Software. doi:10.18129/B9.bioc.BatchQC, R package version 2.9.3, https://bioconductor.org/packages/BatchQC.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | BatchQC_2.9.3.tar.gz |
| Windows binary (x86_64) | BatchQC_2.9.3.zip |
| macOS binary (arm64) | BatchQC_2.9.3.tgz |
| macOS binary (x86_64) | BatchQC_2.9.3.tgz |
Dependencies
Depends: R (>= 4.5.0)
Imports: data.table, DESeq2, dplyr, EBSeq, edgeR, FNN, ggdendro, ggnewscale, ggplot2, ggpubr, Harman, limma, matrixStats, methods, MASS, pheatmap, RColorBrewer, reader, reshape2, scran, shiny, shinyjs, shinythemes, stats, SummarizedExperiment, sva, S4Vectors, tibble, tidyr, tidyverse, umap, utils
Suggests: BiocManager, BiocStyle, bladderbatch, curatedTBData, devtools, knitr, lintr, MultiAssayExperiment, plotly, rmarkdown, spelling, testthat (>= 3.0.0)