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Check a gene signature's classification performance against random signatures, permuted data, and known signatures.

Bioconductor version: 3.0

While gene signatures are frequently used to classify data (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 partly on suggestions in that paper, SigCheck accepts a data set (as an ExpressionSet) and a gene signature, and compares its classification performance (using the MLInterfaces package) against a) random gene signatures of the same length; b) known, (related and unrelated) gene signatures; and c) permuted data.

Author: Justin Norden <jn333 at> and Rory Stark <rory.stark 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
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biocViews Classification, GeneExpression, GeneSetEnrichment, Software
Version 1.0.2
In Bioconductor since BioC 3.0 (R-3.1)
License Artistic-2.0
Depends R (>= 3.1.0), MLInterfaces, Biobase, e1071, BiocParallel
Imports graphics, stats, utils
Suggests BiocStyle, breastCancerNKI
Depends On Me
Imports Me
Suggests Me
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