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SigCheck

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

Bioconductor version: 3.23 · Package version: 2.44.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SigCheck")

Details

MaintainerRory Stark <bioconductor@starkhome.com>
AuthorRory Stark <bioconductor@starkhome.com> and Justin Norden
LicenseArtistic-2.0
Downloads rank547
Source branchRELEASE_3_23
biocViewsClassification, GeneExpression, GeneSetEnrichment, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageSigCheck_2.44.0.tar.gz
Windows binary (x86_64)SigCheck_2.44.0.zip
macOS binary (arm64)SigCheck_2.44.0.tgz
macOS binary (x86_64)SigCheck_2.44.0.tgz
Dependencies

Depends: R (>= 4.0.0), MLInterfaces, Biobase, e1071, BiocParallel, survival

Imports: graphics, stats, utils, methods

Suggests: BiocStyle, breastCancerNKI, qusage