Gene set analysis: A step-by-step guide

Michael A. Mooney, Beth Wilmot

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)517-527
Number of pages11
JournalAmerican Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
Issue number7
StatePublished - Oct 1 2015


  • Complex traits
  • Gene set analysis
  • Genome-wide association studies
  • Polygenic effects

ASJC Scopus subject areas

  • Genetics(clinical)
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience


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