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| Authors: | Gregory J. Matthews, Andrea S. Foulkes | ||||
| Title: | MixMAP: An R Package for Mixed Modeling of Meta-Analysis p Values in Genetic Association Studies | ||||
| Abstract: | Genetic association studies are commonly conducted to identify genes that explain the variability in a measured trait (e.g., disease status or disease progression). Often, results of these studies are summarized in the form of a p value corresponding to a test of association between each single nucleotide polymorphisms (SNPs) and the trait under study. As genes are comprised of multiple SNPs, post hoc approaches are generally applied to determine gene-level association. For example, if any SNP within a gene is significantly associated with the trait at a genome-wide significance level (p < 5 x 10e-8), then the corresponding gene is considered significant. A complementary strategy, termed mix ed modeling of meta-analysis p values (MixMAP) was proposed recently to characterize formally the associations between genes (or gene regions) and a trait based on multiple SNP-level p values. Here, the MixMAP package is presented as a means for implementing the MixMAP procedure in R. | ||||
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Page views:: 1742. Submitted: 2012-12-10. Published: 2015-08-26. |
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| Paper: |
MixMAP: An R Package for Mixed Modeling of Meta-Analysis p Values in Genetic Association Studies
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| DOI: |
10.18637/jss.v066.c03
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This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |