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Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic
Over the past decade, genetic analysis has shifted from linkage studies, which identify broad regions containing putative trait loci, to genome-wide association studies, which detect the association of a marker with a specific phenotype. Because linkage and association analysis provide complementary...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795871/ https://www.ncbi.nlm.nih.gov/pubmed/20017964 |
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author | Hendricks, Audrey E Zhu, Yanyan Dupuis, Josée |
author_facet | Hendricks, Audrey E Zhu, Yanyan Dupuis, Josée |
author_sort | Hendricks, Audrey E |
collection | PubMed |
description | Over the past decade, genetic analysis has shifted from linkage studies, which identify broad regions containing putative trait loci, to genome-wide association studies, which detect the association of a marker with a specific phenotype. Because linkage and association analysis provide complementary information, developing a method to combine these analyses may increase the power to detect a true association. In this paper we compare a linkage score and association score test as well as a newly proposed combination of these two scores with traditional linkage and association methods. |
format | Text |
id | pubmed-2795871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27958712009-12-18 Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic Hendricks, Audrey E Zhu, Yanyan Dupuis, Josée BMC Proc Proceedings Over the past decade, genetic analysis has shifted from linkage studies, which identify broad regions containing putative trait loci, to genome-wide association studies, which detect the association of a marker with a specific phenotype. Because linkage and association analysis provide complementary information, developing a method to combine these analyses may increase the power to detect a true association. In this paper we compare a linkage score and association score test as well as a newly proposed combination of these two scores with traditional linkage and association methods. BioMed Central 2009-12-15 /pmc/articles/PMC2795871/ /pubmed/20017964 Text en Copyright ©2009 Hendricks et al; 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 Hendricks, Audrey E Zhu, Yanyan Dupuis, Josée Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title | Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title_full | Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title_fullStr | Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title_full_unstemmed | Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title_short | Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
title_sort | genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795871/ https://www.ncbi.nlm.nih.gov/pubmed/20017964 |
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