Work

A new Bayesian approach incorporating covariate information for heterogeneity and its comparison with HLOD

Year: 2005

Type: article

Abstract: We consider a new Bayesian approach for heterogeneity that can take into account categorical covariates, if available. We use the Genetic Analysis Workshop 14 simulated data to first compare the Bayesian approach with the heterogeneity LOD, when no covariate information is used. We find that the former is more powerful, while the two approaches have comparable false-positive rates. We then include informative covariates in the Bayesian approach and find that it tends to give more precise interval estimates of the disease gene location than when covariates are not included. We had knowledge of the simulation models at the time we performed the analyses.

Source: BMC Genetics

DOI: 10.1186/1471-2156-6-s1-s138

Authors: Swati Biswas, Shili Lin, Donald A Berry

Institutions: University of North Texas, University of North Texas Health Science Center, The Ohio State University, The University of Texas MD Anderson Cancer Center

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,170

Funders: National Science Foundation, National Institutes of Health, National Human Genome Research Institute