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Batch Effects Quality Control Software

Bioconductor version: Release (3.19)

Sequencing and microarray samples 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.

Author: Jessica McClintock [aut, cre] , W. Evan Johnson [aut] , 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 [aut], Solomon Joseph [ctb]

Maintainer: Jessica McClintock <jessica.mcclintock at>

Citation (from within R, enter citation("BatchQC")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

BatchQC Examples HTML R Script
Introdution to BatchQC HTML R Script
Reference Manual PDF


biocViews BatchEffect, DifferentialExpression, GraphAndNetwork, ImmunoOncology, Microarray, Normalization, Preprocessing, PrincipalComponent, QualityControl, RNASeq, Sequencing, Software, Visualization
Version 2.0.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License MIT + file LICENSE
Depends R (>= 4.3.0)
Imports data.table, DESeq2, dplyr, EBSeq, ggdendro, ggnewscale, ggplot2, limma, matrixStats, pheatmap, RColorBrewer, reader, reshape2, scran, shiny, stats, SummarizedExperiment, sva, tibble, tidyr, tidyverse, utils
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Suggests BiocManager, BiocStyle, bladderbatch, dendextend, devtools, knitr, lintr, plotly, rmarkdown, shinythemes, spelling, testthat (>= 3.0.0)
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Follow Installation instructions to use this package in your R session.

Source Package BatchQC_2.0.0.tar.gz
Windows Binary
macOS Binary (x86_64) BatchQC_2.0.0.tgz
macOS Binary (arm64) BatchQC_2.0.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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