SigCheck

Check a gene signature's prognostic performance against random signatures, known signatures, and permuted data/metadata

Bioconductor version: 3.2

While gene signatures are frequently used to predict phenotypes (e.g. predict prognosis of cancer patients), it it not always clear how optimal or meaningful they are (cf David Venet, Jacques E. Dumont, and Vincent Detours' paper "Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome"). Based on suggestions in that paper, SigCheck accepts a data set (as an ExpressionSet) and a gene signature, and compares its performance on survival and/or classification tasks against a) random gene signatures of the same length; b) known, related and unrelated gene signatures; and c) permuted data and/or metadata.

Author: Rory Stark <rory.stark at cruk.cam.ac.uk> and Justin Norden

Maintainer: Rory Stark <rory.stark at cruk.cam.ac.uk>

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("SigCheck")

Details

Package Archives

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