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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("BioQC")
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 |
Reference Manual | ||
Text | NEWS |
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 |
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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