CHROMSCAN: genome-wide association using a linkage disequilibrium map
CHROMSCAN: genome-wide association using a linkage disequilibrium map
CHROMSCAN implements a composite likelihood model for the analysis of association data. Disease-gene localisation is on a linkage disequilibrium unit (LDU) map, and locations and standard errors, for putatively causal polymorphisms, are determined by the programme. Distortions of the probability distribution created by auto-correlation are avoided by implementation of a permutation test. We evaluated the relative efficiency of the LDU map by simulating pseudo-phenotypes in real genotype samples. We observed that multi-locus mapping on an underlying LDU map reduces location error by approximately 46%. Furthermore, there is a small, but significant, increase in power of approximately 5%. Effective meta-analysis across multiple samples, increasingly important to combine evidence from genome-wide and other association data, is achieved through the weighted combination of location evidence provided by the programme.
association mapping, linkage disequilibrium map, meta-analysis
121-126
Collins, Andrew
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Lau, Winston
125799a9-0468-46b1-ae01-2e2cb367e9b5
2008
Collins, Andrew
7daa83eb-0b21-43b2-af1a-e38fb36e2a64
Lau, Winston
125799a9-0468-46b1-ae01-2e2cb367e9b5
Collins, Andrew and Lau, Winston
(2008)
CHROMSCAN: genome-wide association using a linkage disequilibrium map.
Journal of Human Genetics, 53 (2), .
(doi:10.1007/s10038-007-0226-2).
Abstract
CHROMSCAN implements a composite likelihood model for the analysis of association data. Disease-gene localisation is on a linkage disequilibrium unit (LDU) map, and locations and standard errors, for putatively causal polymorphisms, are determined by the programme. Distortions of the probability distribution created by auto-correlation are avoided by implementation of a permutation test. We evaluated the relative efficiency of the LDU map by simulating pseudo-phenotypes in real genotype samples. We observed that multi-locus mapping on an underlying LDU map reduces location error by approximately 46%. Furthermore, there is a small, but significant, increase in power of approximately 5%. Effective meta-analysis across multiple samples, increasingly important to combine evidence from genome-wide and other association data, is achieved through the weighted combination of location evidence provided by the programme.
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Published date: 2008
Keywords:
association mapping, linkage disequilibrium map, meta-analysis
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Local EPrints ID: 59593
URI: http://eprints.soton.ac.uk/id/eprint/59593
ISSN: 1434-5161
PURE UUID: 749cc6d4-b3ed-4566-a10a-b430af7cf0a7
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Date deposited: 08 Sep 2008
Last modified: 16 Mar 2024 02:42
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Author:
Winston Lau
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