saps: Significance Analysis of Prognostic Signatures
Version 2.4.2

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.

Package details

AuthorDaniel Schmolze [aut, cre], Andrew Beck [aut], Benjamin Haibe-Kains [aut]
MaintainerDaniel Schmolze <[email protected]>
LicenseMIT + file LICENSE
Version2.4.2
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("saps")

Try the saps package in your browser

Any scripts or data that you put into this service are public.

saps documentation built on Oct. 5, 2016, 4:32 a.m.