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FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies
In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, varian...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894624/ https://www.ncbi.nlm.nih.gov/pubmed/27272119 http://dx.doi.org/10.1371/journal.pcbi.1004980 |
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author | Chung, Ren-Hua Tsai, Wei-Yun Kang, Chen-Yu Yao, Po-Ju Tsai, Hui-Ju Chen, Chia-Hsiang |
author_facet | Chung, Ren-Hua Tsai, Wei-Yun Kang, Chen-Yu Yao, Po-Ju Tsai, Hui-Ju Chen, Chia-Hsiang |
author_sort | Chung, Ren-Hua |
collection | PubMed |
description | In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, variant calling, and annotation. However, fewer pipelines have been designed specifically for disease studies. Most of the current analysis pipelines for family-based disease studies using NGS data focus on a specific function, such as identifying variants with Mendelian inheritance or identifying shared chromosomal regions among affected family members. Consequently, some other useful family-based analysis tools, such as imputation, linkage, and association tools, have yet to be integrated and automated. We developed FamPipe, a comprehensive analysis pipeline, which includes several family-specific analysis modules, including the identification of shared chromosomal regions among affected family members, prioritizing variants assuming a disease model, imputation of untyped variants, and linkage and association tests. We used simulation studies to compare properties of some modules implemented in FamPipe, and based on the results, we provided suggestions for the selection of modules to achieve an optimal analysis strategy. The pipeline is under the GNU GPL License and can be downloaded for free at http://fampipe.sourceforge.net. |
format | Online Article Text |
id | pubmed-4894624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48946242016-06-23 FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies Chung, Ren-Hua Tsai, Wei-Yun Kang, Chen-Yu Yao, Po-Ju Tsai, Hui-Ju Chen, Chia-Hsiang PLoS Comput Biol Research Article In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, variant calling, and annotation. However, fewer pipelines have been designed specifically for disease studies. Most of the current analysis pipelines for family-based disease studies using NGS data focus on a specific function, such as identifying variants with Mendelian inheritance or identifying shared chromosomal regions among affected family members. Consequently, some other useful family-based analysis tools, such as imputation, linkage, and association tools, have yet to be integrated and automated. We developed FamPipe, a comprehensive analysis pipeline, which includes several family-specific analysis modules, including the identification of shared chromosomal regions among affected family members, prioritizing variants assuming a disease model, imputation of untyped variants, and linkage and association tests. We used simulation studies to compare properties of some modules implemented in FamPipe, and based on the results, we provided suggestions for the selection of modules to achieve an optimal analysis strategy. The pipeline is under the GNU GPL License and can be downloaded for free at http://fampipe.sourceforge.net. Public Library of Science 2016-06-06 /pmc/articles/PMC4894624/ /pubmed/27272119 http://dx.doi.org/10.1371/journal.pcbi.1004980 Text en © 2016 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Chung, Ren-Hua Tsai, Wei-Yun Kang, Chen-Yu Yao, Po-Ju Tsai, Hui-Ju Chen, Chia-Hsiang FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title | FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title_full | FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title_fullStr | FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title_full_unstemmed | FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title_short | FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies |
title_sort | fampipe: an automatic analysis pipeline for analyzing sequencing data in families for disease studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894624/ https://www.ncbi.nlm.nih.gov/pubmed/27272119 http://dx.doi.org/10.1371/journal.pcbi.1004980 |
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