saps

This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see saps.

Significance Analysis of Prognostic Signatures

Bioconductor version: 3.2

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 schmolze.com>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("saps")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("saps")

Details

Package Archives

Follow Installation instructions to use this package in your R session.