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Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data

Current family-based association tests for sequencing data were mainly developed for identifying rare variants associated with a complex disease. As the disease can be influenced by the joint effects of common and rare variants, common variants with modest effects may not be identified by the method...

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Autores principales: Chung, Ren-Hua, Tsai, Wei-Yun, Martin, Eden R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4171487/
https://www.ncbi.nlm.nih.gov/pubmed/25244564
http://dx.doi.org/10.1371/journal.pone.0107800
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author Chung, Ren-Hua
Tsai, Wei-Yun
Martin, Eden R.
author_facet Chung, Ren-Hua
Tsai, Wei-Yun
Martin, Eden R.
author_sort Chung, Ren-Hua
collection PubMed
description Current family-based association tests for sequencing data were mainly developed for identifying rare variants associated with a complex disease. As the disease can be influenced by the joint effects of common and rare variants, common variants with modest effects may not be identified by the methods focusing on rare variants. Moreover, variants can have risk, neutral, or protective effects. Association tests that can effectively select groups of common and rare variants that are likely to be causal and consider the directions of effects have become important. We developed the Ordered Subset - Variable Threshold - Pedigree Disequilibrium Test (OVPDT), a combination of three algorithms, for association analysis in family sequencing data. The ordered subset algorithm is used to select a subset of common variants based on their relative risks, calculated using only parental mating types. The variable threshold algorithm is used to search for an optimal allele frequency threshold such that rare variants below the threshold are more likely to be causal. The PDT statistics from both rare and common variants selected by the two algorithms are combined as the OVPDT statistic. A permutation procedure is used in OVPDT to calculate the p-value. We used simulations to demonstrate that OVPDT has the correct type I error rates under different scenarios and compared the power of OVPDT with two other family-based association tests. The results suggested that OVPDT can have more power than the other tests if both common and rare variants have effects on the disease in a region.
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spelling pubmed-41714872014-09-25 Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data Chung, Ren-Hua Tsai, Wei-Yun Martin, Eden R. PLoS One Research Article Current family-based association tests for sequencing data were mainly developed for identifying rare variants associated with a complex disease. As the disease can be influenced by the joint effects of common and rare variants, common variants with modest effects may not be identified by the methods focusing on rare variants. Moreover, variants can have risk, neutral, or protective effects. Association tests that can effectively select groups of common and rare variants that are likely to be causal and consider the directions of effects have become important. We developed the Ordered Subset - Variable Threshold - Pedigree Disequilibrium Test (OVPDT), a combination of three algorithms, for association analysis in family sequencing data. The ordered subset algorithm is used to select a subset of common variants based on their relative risks, calculated using only parental mating types. The variable threshold algorithm is used to search for an optimal allele frequency threshold such that rare variants below the threshold are more likely to be causal. The PDT statistics from both rare and common variants selected by the two algorithms are combined as the OVPDT statistic. A permutation procedure is used in OVPDT to calculate the p-value. We used simulations to demonstrate that OVPDT has the correct type I error rates under different scenarios and compared the power of OVPDT with two other family-based association tests. The results suggested that OVPDT can have more power than the other tests if both common and rare variants have effects on the disease in a region. Public Library of Science 2014-09-22 /pmc/articles/PMC4171487/ /pubmed/25244564 http://dx.doi.org/10.1371/journal.pone.0107800 Text en © 2014 Chung et al 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
Chung, Ren-Hua
Tsai, Wei-Yun
Martin, Eden R.
Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title_full Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title_fullStr Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title_full_unstemmed Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title_short Family-Based Association Test Using Both Common and Rare Variants and Accounting for Directions of Effects for Sequencing Data
title_sort family-based association test using both common and rare variants and accounting for directions of effects for sequencing data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4171487/
https://www.ncbi.nlm.nih.gov/pubmed/25244564
http://dx.doi.org/10.1371/journal.pone.0107800
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