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]|
|Date of publication||None|
|Maintainer||Daniel Schmolze <firstname.lastname@example.org>|
|License||MIT + file LICENSE|
calculatePEnrichment: Compute P_enrichment
calculatePPure: Compute P_pure
calculatePRandom: Compute P_random
calculateQValue: Compute saps q-value
plotEnrichment: Plot concordance indices for a geneset
plotKM: Plot Kaplan-Meier curves for a gene set
plotRandomDensity: Draw density plot of 'p_pure' values for random gene sets
plotSapsScoreDensity: Draw density plot of 'saps_score' values for random gene sets
rankConcordance: Compute concordance indices
saps: Compute SAPS statistics
saps-package: Implements Significance Analysis of Prognostic Signatures...