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.
|Depends:||R (≥ 3.0.0), Biobase, GSEABase, genefilter, impute|
|Author:||Kui Shen and Geroge Tseng|
|Maintainer:||Kui Shen <kuishen at alumni.pitt.edu>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]|
|CRAN checks:||MetaPath results|
|Windows binaries:||r-devel: MetaPath_1.0.zip, r-release: MetaPath_1.0.zip, r-oldrel: MetaPath_1.0.zip|
|OS X Mavericks binaries:||r-release: MetaPath_1.0.tgz, r-oldrel: not available|
|Old sources:||MetaPath archive|
Please use the canonical form https://CRAN.R-project.org/package=MetaPath to link to this page.