This is the released version of SigCheck; for the devel version, see SigCheck.
Check a gene signature's prognostic performance against random signatures, known signatures, and permuted data/metadataBioconductor version: Release (3.21)
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, entercitation("SigCheck")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SigCheck")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SigCheck")
Checking gene expression signatures against random and known signatures with SigCheck PDF R Script Reference Manual PDF NEWS Text Details biocViews Classification, GeneExpression, GeneSetEnrichment, Software Version 2.40.0 In Bioconductor since BioC 3.0 (R-3.1) (10.5 years) License Artistic-2.0 Depends R (>= 4.0.0), MLInterfaces, Biobase, e1071, BiocParallel, survival Imports graphics, stats, utils, methods System Requirements URL See More Package Archives
Follow Installation instructions to use this package in your R session.
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