MetaPath-package

MetaPath


Description: This R package was implemented to 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).<p></p><p>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.
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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.

MetaPath-package: Perform the Meta-Analysis for Pathway Enrichment (MAPE) analysis by combining multiple genomic studies

Description

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References