Premium
Gene set analysis: A step‐by‐step guide
Author(s) -
Mooney Michael A.,
Wilmot Beth
Publication year - 2015
Publication title -
american journal of medical genetics part b: neuropsychiatric genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 126
eISSN - 1552-485X
pISSN - 1552-4841
DOI - 10.1002/ajmg.b.32328
Subject(s) - set (abstract data type) , computer science , field (mathematics) , two step , trait , computational biology , data science , data mining , biology , mathematics , programming language , pure mathematics
To maximize the potential of genome‐wide association studies, many researchers are performing secondary analyses to identify sets of genes jointly associated with the trait of interest. Although methods for gene‐set analyses (GSA), also called pathway analyses, have been around for more than a decade, the field is still evolving. There are numerous algorithms available for testing the cumulative effect of multiple SNPs, yet no real consensus in the field about the best way to perform a GSA. This paper provides an overview of the factors that can affect the results of a GSA, the lessons learned from past studies, and suggestions for how to make analysis choices that are most appropriate for different types of data. © 2015 Wiley Periodicals, Inc.