DOI: 10.18129/B9.bioc.BioQC  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see BioQC.

Detect tissue heterogeneity in expression profiles with gene sets

Bioconductor version: 3.17

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>

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


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HTML R Script 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
PDF   Reference Manual
Text   NEWS


biocViews GeneExpression, GeneSetEnrichment, QualityControl, Software, StatisticalMethod
Version 1.28.0
In Bioconductor since BioC 3.3 (R-3.3) (7.5 years)
License GPL (>=3) + file LICENSE
Depends R (>= 3.5.0), Biobase
Imports edgeR, Rcpp, methods, stats, utils
LinkingTo Rcpp
Suggests testthat, knitr, rmarkdown, lattice, latticeExtra, rbenchmark, gplots, gridExtra,, hgu133plus2.db, ggplot2, reshape2, plyr, ineq, covr, limma, RColorBrewer
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