Monte carlo markov chain methods for genome screening

We used Monte Carlo Markov chain (MCMC) methods to analyze a quantitative trait, MAO level, and a discrete trait, Collaborative Study on the Genetics of Alcoholism (COGA) alcoholism. Segregation, linkage, and haplotype sharing were analyzed and effects of marker map features were examined. For MAO,...

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Bibliographic Details
Published inGenetic epidemiology Vol. 17; no. S1; pp. S133 - S138
Main Authors Daw, E.W., Kumm, J., Snow, G.L., Thompson, E.A., Wijsman, E.M.
Format Journal Article
LanguageEnglish
Published New York Wiley Subscription Services, Inc., A Wiley Company 1999
Subjects
Alcoholism - genetics
Chromosome Mapping
Chromosomes, Human, Pair 1
Chromosomes, Human, Pair 10
Chromosomes, Human, Pair 4
complex trait
Female
Genetic Linkage
Genetic Markers
Genetic Testing
Genome
Haplotypes
Humans
identical by descent
linkage
Lod Score
Male
Markov Chains
Monoamine Oxidase - genetics
Monte Carlo Method
multilocus
Quantitative Trait, Heritable
segregation
Sex Factors
Software
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Summary:We used Monte Carlo Markov chain (MCMC) methods to analyze a quantitative trait, MAO level, and a discrete trait, Collaborative Study on the Genetics of Alcoholism (COGA) alcoholism. Segregation, linkage, and haplotype sharing were analyzed and effects of marker map features were examined. For MAO, modest signals were found on chromosomes 1 and 17 for raw data, and 15 for covariate‐adjusted data. For alcoholism, a strong signal was found on chromosome 1 with modest signals on chromosomes 4 and 10.
Bibliography:National Institutes of Health - No. GM-46255
ArticleID:GEPI1370170723
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ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0741-0395
1098-2272
DOI:10.1002/gepi.1370170723