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Detecting multiple causal rare variants in exome sequence data
Author(s) -
Ye Kenny Q.,
Engelman Corinne D.
Publication year - 2011
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20644
Subject(s) - strengths and weaknesses , exome , exome sequencing , computational biology , sequence (biology) , whole genome sequencing , statistical power , computer science , biology , genetics , genome , data mining , gene , mutation , statistics , psychology , mathematics , social psychology
Recent advances in sequencing technology have presented both opportunities and challenges, with limited statistical power to detect a single causal rare variant with practical sample sizes. To overcome this, the contributors to Group 1 of Genetic Analysis Workshop 17 sought to develop methods to detect the combined signal of multiple causal rare variants in a biologically meaningful way. The contributors used genes, genome location proximity, or genetic pathways as the basic unit in combining the information from multiple variants. Weaknesses of the exome sequence data and the relative strengths and weaknesses of the five approaches are discussed. Genet. Epidemiol . 35:S18–S21, 2011. © 2011 Wiley Periodicals, Inc.