DESCRIPTION

Package: saps
Title: Significance Analysis of Prognostic Signatures
Description: 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.
Version: 2.1.0
biocViews: BiomedicalInformatics, GeneExpression, GeneSetEnrichment,
        DifferentialExpression, Survival
Authors@R: c( person("Daniel", "Schmolze", email = "saps@schmolze.com",
        role = c("aut", "cre")), person("Andrew", "Beck", email =
        "abeck2@bidmc.harvard.edu", role = "aut"), person("Benjamin",
        "Haibe-Kains", email = "benjamin.haibe.kains@utoronto.ca", role
        = "aut"))
Maintainer: Daniel Schmolze <saps@schmolze.com>
Depends: R (>= 2.14.0), survival
Imports: piano, survcomp, reshape2
Suggests: snowfall, knitr
License: MIT + file LICENSE
LazyData: true
VignetteBuilder: knitr
Author: Daniel Schmolze [aut, cre], Andrew Beck [aut], Benjamin
        Haibe-Kains [aut]