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: 1.0.0
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
Packaged: 2014-10-08 01:32:33 UTC; Daniel
Author: Daniel Schmolze [aut, cre],
  Andrew Beck [aut],
  Benjamin Haibe-Kains [aut]
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-10-08 04:52:36
