GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles
Author(s) -
Agne Antanaviciute,
Catherine Daly,
Laura A. Crinnion,
Alexander F. Markham,
Christopher M. Watson,
David T. Bonthron,
Ian Carr
Publication year - 2015
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btv196
Subject(s) - candidate gene , gene , computational biology , prioritization , computer science , inference , biology , genetics , data mining , bioinformatics , artificial intelligence , management science , economics
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.
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