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- Title
Bayesian Linkage Analysis of Categorical Traits for Arbitrary Pedigree Designs.
- Authors
Brisbin, Abra; Weissman, Myrna M.; Fyer, Abby J.; Hamilton, Steven P.; Knowles, James A.; Bustamante, Carlos D.; Mezey, Jason G.
- Abstract
Background: Pedigree studies of complex heritable diseases often feature nominal or ordinal phenotypic measurements and missing genetic marker or phenotype data. Methodology: We have developed a Bayesian method for Linkage analysis of Ordinal and Categorical traits (LOCate) that can analyze complex genealogical structure for family groups and incorporate missing data. LOCate uses a Gibbs sampling approach to assess linkage, incorporating a simulated tempering algorithm for fast mixing. While our treatment is Bayesian, we develop a LOD (log of odds) score estimator for assessing linkage from Gibbs sampling that is highly accurate for simulated data. LOCate is applicable to linkage analysis for ordinal or nominal traits, a versatility which we demonstrate by analyzing simulated data with a nominal trait, on which LOCate outperforms LOT, an existing method which is designed for ordinal traits. We additionally demonstrate our method's versatility by analyzing a candidate locus (D2S1788) for panic disorder in humans, in a dataset with a large amount of missing data, which LOT was unable to handle. Conclusion: LOCate's accuracy and applicability to both ordinal and nominal traits will prove useful to researchers interested in mapping loci for categorical traits.
- Subjects
BAYESIAN analysis; CATEGORY management; GENETIC disorders; GENEALOGY; GENETIC markers; PHENOTYPES; ALGORITHMS; PANIC disorders; LOCUS (Genetics)
- Publication
PLoS ONE, 2010, Vol 5, Issue 8, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0012307