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Bioconductor - BioQC

BioQC

This is the released version of BioQC; for the devel version, see BioQC.

Detect tissue heterogeneity in expression profiles with gene sets

Bioconductor version: Release (3.21)

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 "4.5") 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 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.

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