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Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3
This paper presents a novel method of identifying phenotypically important regions of the genome. It involves a form of association mapping that works by summarizing properties of the ancestral recombination graph (ARG) of a sample of unrelated phenotyped and genotyped individuals. By breaking the s...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367498/ https://www.ncbi.nlm.nih.gov/pubmed/18466474 |
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author | Platt, Alexander |
author_facet | Platt, Alexander |
author_sort | Platt, Alexander |
collection | PubMed |
description | This paper presents a novel method of identifying phenotypically important regions of the genome. It involves a form of association mapping that works by summarizing properties of the ancestral recombination graph (ARG) of a sample of unrelated phenotyped and genotyped individuals. By breaking the sample into many small sub-samples and averaging the results, it becomes computationally tractable to measure the degree to which the evolutionary history of any locus is consistent with the distribution of the phenotypes in the sample. Analysis of simulated rheumatoid arthritis data demonstrates the efficiency and effectiveness of this method in identifying loci of large phenotypic effect. |
format | Text |
id | pubmed-2367498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23674982008-05-06 Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 Platt, Alexander BMC Proc Proceedings This paper presents a novel method of identifying phenotypically important regions of the genome. It involves a form of association mapping that works by summarizing properties of the ancestral recombination graph (ARG) of a sample of unrelated phenotyped and genotyped individuals. By breaking the sample into many small sub-samples and averaging the results, it becomes computationally tractable to measure the degree to which the evolutionary history of any locus is consistent with the distribution of the phenotypes in the sample. Analysis of simulated rheumatoid arthritis data demonstrates the efficiency and effectiveness of this method in identifying loci of large phenotypic effect. BioMed Central 2007-12-18 /pmc/articles/PMC2367498/ /pubmed/18466474 Text en Copyright © 2007 Platt; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Platt, Alexander Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title | Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title_full | Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title_fullStr | Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title_full_unstemmed | Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title_short | Association mapping through heuristic evolutionary history reconstruction-application to GAW15 Problem 3 |
title_sort | association mapping through heuristic evolutionary history reconstruction-application to gaw15 problem 3 |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367498/ https://www.ncbi.nlm.nih.gov/pubmed/18466474 |
work_keys_str_mv | AT plattalexander associationmappingthroughheuristicevolutionaryhistoryreconstructionapplicationtogaw15problem3 |