Multivariate tool for analyzing genome-wide association study results in the form of univariate summary statistics. The goal of 'bmass' is to comprehensively test all possible multivariate models given the phenotypes and datasets provided. Multivariate models are determined by assigning each phenotype to being either Unassociated (U), Directly associated (D) or Indirectly associated (I) with the genetic variant of interest. Test results for each model are presented in the form of Bayes factors, thereby allowing direct comparisons between models. The underlying framework implemented here is based on the modeling developed in "A Unified Framework for Association Analysis with Multiple Related Phenotypes", M. Stephens (2013) <doi:10.1371/journal.pone.0065245>.
|Depends:||R (≥ 3.3.0)|
|Suggests:||testthat, knitr, rmarkdown|
|Author:||Michael Turchin [aut, cre], Matthew Stephens [aut], Peter Carbonetto [ctb]|
|Maintainer:||Michael Turchin <mturchin20 at uchicago.edu>|
|License:||GPL (≥ 3)|
|Citation:||bmass citation info|
|CRAN checks:||bmass results|
bmass Introduction – Simulated Data
bmass Introduction – Real Data
|Windows binaries:||r-devel: bmass_1.0.3.zip, r-release: bmass_1.0.3.zip, r-oldrel: bmass_1.0.3.zip|
|macOS binaries:||r-release (arm64): bmass_1.0.3.tgz, r-oldrel (arm64): bmass_1.0.3.tgz, r-release (x86_64): bmass_1.0.3.tgz, r-oldrel (x86_64): bmass_1.0.3.tgz|
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