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- Title
- Gene selection tool (GST) : a R-based tool for genetic disorders based on the sliding-window proportion test using whole-exome sequencing data
- Author(s)
- Sugi Lee; Minah Jung; Jaeeun Jung; Kunhyang Park; Jea Woon Ryu; Jeongkil Kim; Dae Soo Kim
- Bibliographic Citation
- PLoS One, vol. 12, no. 9, pp. e0185514-e0185514
- Publication Year
- 2017
- Abstract
- 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
- Publisher
- Public Library of Science
- Full Text Link
- http://dx.doi.org/10.1371/journal.pone.0185514
- Type
- Article
- Appears in Collections:
- Division of A.I. & Biomedical Research > Digital Biotech Innovation Center > 1. Journal Articles
Division of Bio Technology Innovation > Core Research Facility & Analysis Center > 1. Journal Articles
- Files in This Item:
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