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

Bioconductor version: 3.1

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> and Justin Norden <jn333 at>

Maintainer: Rory Stark <rory.stark at>

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PDF R Script Checking gene expression signatures against random and known signatures with SigCheck
PDF   Reference Manual
Text   NEWS


biocViews Classification, GeneExpression, GeneSetEnrichment, Software
Version 2.0.2
In Bioconductor since BioC 3.0 (R-3.1) (1 year)
License Artistic-2.0
Depends R (>= 3.1.0), MLInterfaces, Biobase, e1071, BiocParallel, survival
Imports graphics, stats, utils, methods
Suggests BiocStyle, breastCancerNKI
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