A Bayesian approach for applying Haseman-Elston methods.

Yoon, Seungtai, Suh, Young Ju, Mendell, Nancy Role, Ye, Kenny Qian (December 2005) A Bayesian approach for applying Haseman-Elston methods. BMC Genetics, 6 Supp (SUPPL.). S39. ISSN 1471-2156

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URL: https://www.ncbi.nlm.nih.gov/pubmed/16451649
DOI: 10.1186/1471-2156-6-S1-S39


The main goal of this paper is to couple the Haseman-Elston method with a simple yet effective Bayesian factor-screening approach. This approach selects markers by considering a set of multigenic models that include epistasis effects. The markers are ranked based on their marginal posterior probability. A significant improvement over our previously proposed Bayesian variable selection methodology is a simple Metropolis-Hasting algorithm that requires minimum tuning on the prior settings. The algorithm, however, is also flexible enough for us to easily incorporate our hypotheses and avoid computational pitfalls. We apply our approach to the microsatellite data of Collaborative Studies on Genetics of Alcoholism using the coded values for the ALDX1 variable as our response.

Item Type: Paper
Subjects: organism description > animal behavior > addiction
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes
CSHL Authors:
Communities: CSHL labs > Yoon lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 30 December 2005
Date Deposited: 20 May 2021 17:11
Last Modified: 20 May 2021 17:11
PMCID: PMC1866746
URI: https://repository.cshl.edu/id/eprint/40097

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