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Significance Analysis of Prognostic Signatures

Bioconductor version: Development (3.4)

Functions implementing the Significance Analysis of Prognostic Signatures method (SAPS). SAPS provides a robust method for identifying biologically significant gene sets associated with patient survival. Three basic statistics are computed. First, patients are clustered into two survival groups based on differential expression of a candidate gene set. P_pure is calculated as the probability of no survival difference between the two groups. Next, the same procedure is applied to randomly generated gene sets, and P_random is calculated as the proportion achieving a P_pure as significant as the candidate gene set. Finally, a pre-ranked Gene Set Enrichment Analysis (GSEA) is performed by ranking all genes by concordance index, and P_enrich is computed to indicate the degree to which the candidate gene set is enriched for genes with univariate prognostic significance. A SAPS_score is calculated to summarize the three statistics, and optionally a Q-value is computed to estimate the significance of the SAPS_score by calculating SAPS_scores for random gene sets.

Author: Daniel Schmolze [aut, cre], Andrew Beck [aut], Benjamin Haibe-Kains [aut]

Maintainer: Daniel Schmolze <saps at>

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biocViews BiomedicalInformatics, DifferentialExpression, GeneExpression, GeneSetEnrichment, Software, Survival
Version 2.5.2
In Bioconductor since BioC 3.1 (R-3.2) (1.5 years)
License MIT + file LICENSE
Depends R (>= 2.14.0), survival
Imports piano, survcomp, reshape2
Suggests snowfall, knitr
Depends On Me
Imports Me
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