sigora: Signature Overrepresentation Analysis

Pathway Analysis is statistically linking observations on the molecular level to biological processes or pathways on the systems(i.e., organism, organ, tissue, cell) level. Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative. However, this can lead to identifying spurious pathways as statistically significant since components are often shared amongst pathways. SIGORA seeks to avoid this pitfall by focusing on genes or gene pairs that are (as a combination) specific to a single pathway. In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways. The current version allows for pathway analysis of human and mouse datasets. In addition, it contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories and mechanisms for extracting GPS for user-supplied repositories.

Package details

AuthorAmir Foroushani [aut] (<https://orcid.org/0000-0003-2748-3009>), Fiona Brinkman [aut], David Lynn [aut], Witold Wolski [cre] (<https://orcid.org/0000-0002-6468-120X>)
Bioconductor views GO GeneSetEnrichment KEGG Pathways Software
MaintainerWitold Wolski <wew@fgcz.ethz.ch>
LicenseGPL-3
Version3.1.1
URL https://github.com/wolski/sigora
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("sigora")

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sigora documentation built on March 18, 2022, 8:05 p.m.