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Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data

Whole-exome sequencing (WES) can identify causative mutations in hereditary diseases. However, WES data might have a large candidate variant list, including false positives. Moreover, in families, it is more difficult to select disease-associated variants because many variants are shared among membe...

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Autores principales: Lee, Sugi, Jung, Minah, Jung, Jaeeun, Park, Kunhyang, Ryu, Jea-Woon, Kim, Jeongkil, Kim, Dae-soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5619773/
https://www.ncbi.nlm.nih.gov/pubmed/28957403
http://dx.doi.org/10.1371/journal.pone.0185514
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author Lee, Sugi
Jung, Minah
Jung, Jaeeun
Park, Kunhyang
Ryu, Jea-Woon
Kim, Jeongkil
Kim, Dae-soo
author_facet Lee, Sugi
Jung, Minah
Jung, Jaeeun
Park, Kunhyang
Ryu, Jea-Woon
Kim, Jeongkil
Kim, Dae-soo
author_sort Lee, Sugi
collection PubMed
description Whole-exome sequencing (WES) can identify causative mutations in hereditary diseases. However, WES data might have a large candidate variant list, including false positives. Moreover, in families, it is more difficult to select disease-associated variants because many variants are shared among members. To reduce false positives and extract accurate candidates, we used a multilocus variant instead of a single-locus variant (SNV). We set up a specific window to analyze the multilocus variant and devised a sliding-window approach to observe all variants. We developed the gene selection tool (GST) based on proportion tests for linkage analysis using WES data. This tool is R program coded and has high sensitivity. We tested our code to find the gene for hereditary spastic paraplegia using SNVs from a specific family and identified the gene known to cause the disease in a significant gene list. The list identified other genes that might be associated with the disease.
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spelling pubmed-56197732017-10-17 Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data Lee, Sugi Jung, Minah Jung, Jaeeun Park, Kunhyang Ryu, Jea-Woon Kim, Jeongkil Kim, Dae-soo PLoS One Research Article Whole-exome sequencing (WES) can identify causative mutations in hereditary diseases. However, WES data might have a large candidate variant list, including false positives. Moreover, in families, it is more difficult to select disease-associated variants because many variants are shared among members. To reduce false positives and extract accurate candidates, we used a multilocus variant instead of a single-locus variant (SNV). We set up a specific window to analyze the multilocus variant and devised a sliding-window approach to observe all variants. We developed the gene selection tool (GST) based on proportion tests for linkage analysis using WES data. This tool is R program coded and has high sensitivity. We tested our code to find the gene for hereditary spastic paraplegia using SNVs from a specific family and identified the gene known to cause the disease in a significant gene list. The list identified other genes that might be associated with the disease. Public Library of Science 2017-09-28 /pmc/articles/PMC5619773/ /pubmed/28957403 http://dx.doi.org/10.1371/journal.pone.0185514 Text en © 2017 Lee 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
Lee, Sugi
Jung, Minah
Jung, Jaeeun
Park, Kunhyang
Ryu, Jea-Woon
Kim, Jeongkil
Kim, Dae-soo
Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title_full Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title_fullStr Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title_full_unstemmed Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title_short Gene selection tool (GST): A R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
title_sort gene selection tool (gst): a r-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5619773/
https://www.ncbi.nlm.nih.gov/pubmed/28957403
http://dx.doi.org/10.1371/journal.pone.0185514
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