BioQC

DOI: 10.18129/B9.bioc.BioQC    

Detect tissue heterogeneity in expression profiles with gene sets

Bioconductor version: Release (3.6)

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 <jitao_david.zhang at roche.com>, Laura Badi, Gregor Sturm, Roland Ambs

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

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BioQC")

Documentation

HTML R Script BioQC Alogrithm: Speeding up the Wilcoxon-Mann-Whitney Test
HTML R Script BioQC: Detect tissue heterogeneity in gene expression data
HTML R Script Using BioQC with signed genesets
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneExpression, QualityControl, Software, StatisticalMethod
Version 1.6.0
In Bioconductor since BioC 3.3 (R-3.3) (2 years)
License GPL (>=3)
Depends utils, Rcpp, Biobase, methods, stats
Imports
LinkingTo
Suggests testthat, knitr, rmarkdown, lattice, latticeExtra, rbenchmark, gplots, gridExtra, hgu133plus2.db, ineq
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package BioQC_1.6.0.tar.gz
Windows Binary BioQC_1.6.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) BioQC_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BioQC
Package Short Url http://bioconductor.org/packages/BioQC/
Package Downloads Report Download Stats

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