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A power set-based statistical selection procedure to locate susceptible rare variants associated with complex traits with sequencing data
Author(s) -
Hokeun Sun,
Shuang Wang
Publication year - 2014
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/btu207
Subject(s) - selection (genetic algorithm) , biology , genetics , gene , computational biology , trait , genetic association , genetic variation , genotype , single nucleotide polymorphism , computer science , machine learning , programming language
Existing association methods for rare variants from sequencing data have focused on aggregating variants in a gene or a genetic region because of the fact that analysing individual rare variants is underpowered. However, these existing rare variant detection methods are not able to identify which rare variants in a gene or a genetic region of all variants are associated with the complex diseases or traits. Once phenotypic associations of a gene or a genetic region are identified, the natural next step in the association study with sequencing data is to locate the susceptible rare variants within the gene or the genetic region.

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