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Testing Genetic Association by Regressing Genotype over Multiple Phenotypes
Complex disorders are typically characterized by multiple phenotypes. Analyzing these phenotypes jointly is expected to be more powerful than dealing with one of them at a time. A recent approach (O'Reilly et al. 2012) is to regress the genotype at a SNP marker on multiple phenotypes and apply...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4164437/ https://www.ncbi.nlm.nih.gov/pubmed/25221983 http://dx.doi.org/10.1371/journal.pone.0106918 |
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author | Wang, Kai |
author_facet | Wang, Kai |
author_sort | Wang, Kai |
collection | PubMed |
description | Complex disorders are typically characterized by multiple phenotypes. Analyzing these phenotypes jointly is expected to be more powerful than dealing with one of them at a time. A recent approach (O'Reilly et al. 2012) is to regress the genotype at a SNP marker on multiple phenotypes and apply the proportional odds model. In the current research, we introduce an explicit expression for the score test statistic and its non-centrality parameter that determines its power. Same simulation studies as those reported in Galesloot et al. (2014) were conducted to assess its performance. We demonstrate by theoretical arguments and simulation studies that, despite its potential usefulness for multiple phenotypes, the proportional odds model method can be less powerful than regular methods for univariate traits. We also introduce an implementation of the proposed score statistic in an R package named iGasso. |
format | Online Article Text |
id | pubmed-4164437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41644372014-09-19 Testing Genetic Association by Regressing Genotype over Multiple Phenotypes Wang, Kai PLoS One Research Article Complex disorders are typically characterized by multiple phenotypes. Analyzing these phenotypes jointly is expected to be more powerful than dealing with one of them at a time. A recent approach (O'Reilly et al. 2012) is to regress the genotype at a SNP marker on multiple phenotypes and apply the proportional odds model. In the current research, we introduce an explicit expression for the score test statistic and its non-centrality parameter that determines its power. Same simulation studies as those reported in Galesloot et al. (2014) were conducted to assess its performance. We demonstrate by theoretical arguments and simulation studies that, despite its potential usefulness for multiple phenotypes, the proportional odds model method can be less powerful than regular methods for univariate traits. We also introduce an implementation of the proposed score statistic in an R package named iGasso. Public Library of Science 2014-09-15 /pmc/articles/PMC4164437/ /pubmed/25221983 http://dx.doi.org/10.1371/journal.pone.0106918 Text en © 2014 Kai Wang http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wang, Kai Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title | Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title_full | Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title_fullStr | Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title_full_unstemmed | Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title_short | Testing Genetic Association by Regressing Genotype over Multiple Phenotypes |
title_sort | testing genetic association by regressing genotype over multiple phenotypes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4164437/ https://www.ncbi.nlm.nih.gov/pubmed/25221983 http://dx.doi.org/10.1371/journal.pone.0106918 |
work_keys_str_mv | AT wangkai testinggeneticassociationbyregressinggenotypeovermultiplephenotypes |