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Fast Association Tests for Genes with FAST

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  • Pritam Chanda
  • Hailiang Huang
  • Dan E Arking
  • Joel S Bader

Abstract

Gene-based tests of association can increase the power of a genome-wide association study by aggregating multiple independent effects across a gene or locus into a single stronger signal. Recent gene-based tests have distinct approaches to selecting which variants to aggregate within a locus, modeling the effects of linkage disequilibrium, representing fractional allele counts from imputation, and managing permutation tests for p-values. Implementing these tests in a single, efficient framework has great practical value. Fast ASsociation Tests (Fast) addresses this need by implementing leading gene-based association tests together with conventional SNP-based univariate tests and providing a consolidated, easily interpreted report. Fast scales readily to genome-wide SNP data with millions of SNPs and tens of thousands of individuals, provides implementations that are orders of magnitude faster than original literature reports, and provides a unified framework for performing several gene based association tests concurrently and efficiently on the same data. Availability: https://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Home

Suggested Citation

  • Pritam Chanda & Hailiang Huang & Dan E Arking & Joel S Bader, 2013. "Fast Association Tests for Genes with FAST," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-5, July.
    • Handle: RePEc:plo:pone00:0068585
    DOI: 10.1371/journal.pone.0068585
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