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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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Bibliographic Details
Published in:PloS one 2017-09, Vol.12 (9), p.e0185514-e0185514
Main Authors: Lee, Sugi, Jung, Minah, Jung, Jaeeun, Park, Kunhyang, Ryu, Jea-Woon, Kim, Jeongkil, Kim, Dae-Soo
Format: Article
Language:English
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0185514