BioQC

Detect tissue heterogeneity in expression profiles with gene sets


Bioconductor version: Release (3.19)

BioQC performs quality control of high-throughput expression data based on tissue gene signatures. It can detect tissue heterogeneity in gene expression data. The core algorithm is a Wilcoxon-Mann-Whitney test that is optimised for high performance.

Author: Jitao David Zhang [cre, aut], Laura Badi [aut], Gregor Sturm [aut], Roland Ambs [aut], Iakov Davydov [aut]

Maintainer: Jitao David Zhang <jitao_david.zhang at roche.com>

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

Installation

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


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("BioQC")

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

Documentation

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

browseVignettes("BioQC")
BioQC Algorithm: Speeding up the Wilcoxon-Mann-Whitney Test HTML R Script
BioQC-benchmark: Testing Efficiency, Sensitivity and Specificity of BioQC on simulated and real-world data HTML R Script
BioQC-kidney: The kidney expression example HTML R Script
BioQC: Detect tissue heterogeneity in gene expression data HTML R Script
Comparing the Wilcoxon-Mann-Whitney to alternative statistical tests HTML R Script
Using BioQC with signed genesets HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews GeneExpression, GeneSetEnrichment, QualityControl, Software, StatisticalMethod
Version 1.32.0
In Bioconductor since BioC 3.3 (R-3.3) (8.5 years)
License GPL (>=3) + file LICENSE
Depends R (>= 3.5.0), Biobase
Imports edgeR, Rcpp, methods, stats, utils
System Requirements
URL https://accio.github.io/BioQC
Bug Reports https://accio.github.io/BioQC/issues
See More
Suggests testthat, knitr, rmarkdown, lattice, latticeExtra, rbenchmark, gplots, gridExtra, org.Hs.eg.db, hgu133plus2.db, ggplot2, reshape2, plyr, ineq, covr, limma, RColorBrewer
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package BioQC_1.32.0.tar.gz
Windows Binary BioQC_1.32.0.zip
macOS Binary (x86_64) BioQC_1.32.0.tgz
macOS Binary (arm64) BioQC_1.32.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BioQC
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BioQC
Bioc Package Browser https://code.bioconductor.org/browse/BioQC/
Package Short Url https://bioconductor.org/packages/BioQC/
Package Downloads Report Download Stats