SigCheck

This is the development version of SigCheck; for the stable release version, see SigCheck.

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

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DOI: 10.18129/B9.bioc.SigCheck

Bioconductor version: Development (3.23)

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 <bioconductor at starkhome.com> and Justin Norden

Maintainer: Rory Stark <bioconductor at starkhome.com>

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

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("SigCheck")

For older versions of R, please refer to the appropriate Bioconductor release.