metaOmics/MetaPath: Perform the Meta-Analysis for Pathway Enrichment

Perform the Meta-analysis for Pathway Enrichment (MAPE) methods introduced by Shen and Tseng (2010). It includes functions to automatically perform MAPE_G (integrating multiple studies at gene level), MAPE_P (integrating multiple studies at pathway level) and MAPE_I (a hybrid method integrating MAEP_G and MAPE_P methods). In the simulation and real data analyses in the paper, MAPE_G and MAPE_P have complementary advantages and detection power depending on the data structure. In general, the integrative form of MAPE_I is recommended to use. In the case that MAPE_G (or MAPE_P) detects almost none pathway, the integrative MAPE_I does not improve performance and MAPE_P (or MAPE_G) should be used. Reference: Shen, Kui, and George C Tseng. Meta-analysis for pathway enrichment analysis when combining multiple microarray studies.Bioinformatics (Oxford, England) 26, no. 10 (April 2010): 1316-1323. doi:10.1093/bioinformatics/btq148. http://www.ncbi.nlm.nih.gov/pubmed/20410053.

Getting started

Package details

AuthorXiangrui Zeng, Kui Shen, Zhou Fang, Wei Zong, Chien-wei Lin and Geroge Tseng
MaintainerKui Shen <kuishen@alumni.pitt.edu>
LicenseGPL-2
Version2.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("metaOmics/MetaPath")
metaOmics/MetaPath documentation built on June 15, 2020, 10:22 a.m.