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PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data
With the advances of next-generation sequencing technology, the field of disease research has been revolutionized. However, pinpointing the disease-causing variants from millions of revealed variants is still a tough task. Here, we have reviewed the existing linkage analysis tools and presented PedM...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138824/ https://www.ncbi.nlm.nih.gov/pubmed/32393981 http://dx.doi.org/10.1093/bib/bbaa077 |
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author | Zhou, Jianteng Gao, Jianing Zhang, Huan Zhao, Daren Li, Ao Iqbal, Furhan Shi, Qinghua Zhang, Yuanwei |
author_facet | Zhou, Jianteng Gao, Jianing Zhang, Huan Zhao, Daren Li, Ao Iqbal, Furhan Shi, Qinghua Zhang, Yuanwei |
author_sort | Zhou, Jianteng |
collection | PubMed |
description | With the advances of next-generation sequencing technology, the field of disease research has been revolutionized. However, pinpointing the disease-causing variants from millions of revealed variants is still a tough task. Here, we have reviewed the existing linkage analysis tools and presented PedMiner, a web-based application designed to narrow down candidate variants from family based whole-exome sequencing (WES) data through linkage analysis. PedMiner integrates linkage analysis, variant annotation and prioritization in one automated pipeline. It provides graphical visualization of the linked regions along with comprehensive annotation of variants and genes within these linked regions. This efficient and comprehensive application will be helpful for the scientific community working on Mendelian inherited disorders using family based WES data. |
format | Online Article Text |
id | pubmed-8138824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-81388242021-05-25 PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data Zhou, Jianteng Gao, Jianing Zhang, Huan Zhao, Daren Li, Ao Iqbal, Furhan Shi, Qinghua Zhang, Yuanwei Brief Bioinform Problem Solving Protocol With the advances of next-generation sequencing technology, the field of disease research has been revolutionized. However, pinpointing the disease-causing variants from millions of revealed variants is still a tough task. Here, we have reviewed the existing linkage analysis tools and presented PedMiner, a web-based application designed to narrow down candidate variants from family based whole-exome sequencing (WES) data through linkage analysis. PedMiner integrates linkage analysis, variant annotation and prioritization in one automated pipeline. It provides graphical visualization of the linked regions along with comprehensive annotation of variants and genes within these linked regions. This efficient and comprehensive application will be helpful for the scientific community working on Mendelian inherited disorders using family based WES data. Oxford University Press 2020-05-11 /pmc/articles/PMC8138824/ /pubmed/32393981 http://dx.doi.org/10.1093/bib/bbaa077 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Problem Solving Protocol Zhou, Jianteng Gao, Jianing Zhang, Huan Zhao, Daren Li, Ao Iqbal, Furhan Shi, Qinghua Zhang, Yuanwei PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title | PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title_full | PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title_fullStr | PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title_full_unstemmed | PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title_short | PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
title_sort | pedminer: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138824/ https://www.ncbi.nlm.nih.gov/pubmed/32393981 http://dx.doi.org/10.1093/bib/bbaa077 |
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