To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("phenoTest")

In most cases, you don't need to download the package archive at all.

phenoTest

Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.

Bioconductor version: Release (3.0)

Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided.

Author: Evarist Planet

Maintainer: Evarist Planet <evarist.planet at epfl.ch>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("phenoTest")

Documentation

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

browseVignettes("phenoTest")

 

PDF R Script Manual for the phenoTest library
PDF   Reference Manual

Details

biocViews Classification, Clustering, DifferentialExpression, Microarray, MultipleComparison, Software
Version 1.14.0
In Bioconductor since BioC 2.8 (R-2.13)
License GPL (>=2)
Depends R (>= 2.12.0), Biobase, methods, annotate, Heatplus, BMA, ggplot2, gridExtra
Imports survival, limma, Hmisc, gplots, Category, AnnotationDbi, hopach, biomaRt, GSEABase, genefilter, xtable, annotate, mgcv, SNPchip, hgu133a.db, HTSanalyzeR, ellipse
Suggests GSEABase, KEGG.db, GO.db
System Requirements
URL
Depends On Me
Imports Me
Suggests Me

Package Archives

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

Package Source phenoTest_1.14.0.tar.gz
Windows Binary phenoTest_1.14.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) phenoTest_1.14.0.tgz
Mac OS X 10.9 (Mavericks) phenoTest_1.14.0.tgz
Browse/checkout source (username/password: readonly)
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Fred Hutchinson Cancer Research Center