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bmass
View on CRAN: Click
here
Download and install bmass package within the R console
Install from CRAN:
install.packages("bmass")
Install from Github:
library("remotes")
install_github("cran/bmass")
Install by package version:
library("remotes")
install_version("bmass", "1.0.3")
Attach the package and use:
library("bmass")
Maintained by
Michael Turchin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-17
Latest Update: 2019-05-17
Description:
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) .
How to cite:
Michael Turchin (2019). bmass: Bayesian Multivariate Analysis of Summary Statistics. R package version 1.0.3, https://cran.r-project.org/web/packages/bmass. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for bmass
Functions, R codes and Examples using
the bmass R package
Some associated functions: GetMarginalPosteriors . GetModelPriorMatrix . GetTopModelsPerSNPViaPosteriors . GlobalLipids2013.GWASsnps . bmass . bmass_SimulatedData1 . bmass_SimulatedData2 . bmass_SimulatedSigSNPs . bmass_TestData1 . bmass_TestData2 . bmass_TestSigSNPs .
Some associated R codes: CreateLogFile.R . GetResultsFromMarginalSNPsAndFormat.R . MergeDataGWASAnnotateAndGetMarginalSNPs.R . PassChecksForDataSources.R . ResultsFollowupAnalysisAndPlotting.R . Stephens2013PLoSONE.globallipids.GLCfuncs.R . Stephens2013PLoSONE.test.funcs.R . bmass.R . data.R . Full bmass package functions and examples
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