PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data. Issue 3 (11th May 2020)

• Record Type: Journal Article
• Authors: Zhou, Jianteng; Gao, Jianing; Zhang, Huan; Zhao, Daren; Li, Ao; Iqbal, Furhan; Shi, Qinghua; Zhang, Yuanwei
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 3(2021)
• Publication Date: 2020-05-11
• Subjects: pathogenic variants -- linkage analysis -- whole-exome sequencing (WES) -- web-server; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa077
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: 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.