Analyzing Genome-wide Association Study Data with the R Package genMOSS
Matthew Friedlander, Adrian Dobra, Helene Massam, Laurent, Briollais
TL;DR
The paper introduces the R package genMOSS for Bayesian analysis of GWAS data, utilizing the MOSS procedure and moving window approach to identify SNP combinations linked to responses.
Contribution
It presents a new R package implementing the MOSS Bayesian method and a moving window approach for GWAS data analysis.
Findings
Efficient identification of SNP combinations associated with traits.
Implementation of generalized hyper Dirichlet prior in Bayesian GWAS analysis.
Provides tools for mode oriented stochastic search in genetic data.
Abstract
The R package (R Core Team (2016)) genMOSS is specifically designed for the Bayesian analysis of genome-wide association study data. The package implements the mode oriented stochastic search (MOSS) procedure as well as a simple moving window approach to identify combinations of single nucleotide polymorphisms associated with a response. The prior used in Bayesian computations is the generalized hyper Dirichlet.
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Taxonomy
TopicsGene expression and cancer classification · Genetic Associations and Epidemiology · Bioinformatics and Genomic Networks