Multilocus Association Mapping Using Variable-Length Markov Chains

I propose a new method for association-based gene mapping that makes powerful use of multilocus data, is computationally efficient, and is straightforward to apply over large genomic regions. The approach is based on the fitting of variable-length Markov chain models, which automatically adapt to th...

Full description

Saved in:
Bibliographic Details
Published in:American journal of human genetics 2006-06, Vol.78 (6), p.903-913
Main Author: Browning, Sharon R.
Format: Article
Language:English
Subjects:
Biological and medical sciences
Chromosome Mapping - methods
Crohn Disease - genetics
Cystic Fibrosis - genetics
General aspects. Genetic counseling
Genetic linkage
Genetic Markers
Genetic testing
Genetics
Genomics
Genotype & phenotype
Humans
Linkage Disequilibrium
Markov analysis
Markov Chains
Medical genetics
Medical sciences
Methods
Polymorphism, Restriction Fragment Length
Sample size
Studies
Tests
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:I propose a new method for association-based gene mapping that makes powerful use of multilocus data, is computationally efficient, and is straightforward to apply over large genomic regions. The approach is based on the fitting of variable-length Markov chain models, which automatically adapt to the degree of linkage disequilibrium (LD) between markers to create a parsimonious model for the LD structure. Edges of the fitted graph are tested for association with trait status. This approach can be thought of as haplotype testing with sophisticated windowing that accounts for extent of LD to reduce degrees of freedom and number of tests while maximizing information. I present analyses of two published data sets that show that this approach can have better power than single-marker tests or sliding-window haplotypic tests.
ISSN:0002-9297
1537-6605
DOI:10.1086/503876