期刊
BIOINFORMATICS
卷 31, 期 16, 页码 2728-2735出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv196
关键词
-
类别
资金
- Sir Jules Thorn Charitable Trust [09/JTA]
- MRC [MR/L01629X/1]
- Medical Research Council [MR/L01629X/1] Funding Source: researchfish
- MRC [MR/L01629X/1] Funding Source: UKRI
Motivation: In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually. Results: Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据