Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
MixMAP: An R Package for Mixed Modeling of Meta-Analysis p Values in Genetic Association Studies | Matthews | Journal of Statistical Software
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.

Page views:: 1255. Submitted: 2012-12-10. Published: 2015-08-26.
Paper: MixMAP: An R Package for Mixed Modeling of Meta-Analysis p Values in Genetic Association Studies     Download PDF (Downloads: 1127)
Supplements:
MixMAP_1.3.4.tar.gz: R source package Download (Downloads: 53; 315KB)
v66c03.R: R example code from the paper Download (Downloads: 46; 774B)

DOI: 10.18637/jss.v066.c03

by
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.