Chanda, PritamHuang, HailiangArking, Dan E.Bader, Joel S.2014-03-012013Chanda, Pritam, Hailiang Huang, Dan E. Arking, and Joel S. Bader. 2013. “Fast Association Tests for Genes with FAST.” PLoS ONE 8 (7): e68585. doi:10.1371/journal.pone.0068585. http://dx.doi.org/10.1371/journal.pone.0068585.1932-6203http://nrs.harvard.edu/urn-3:HUL.InstRepos:11855891Gene-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/Homeen-USBiologyComputational BiologyGenomicsGenome Analysis ToolsGenome ScansPopulation GeneticsGenetic PolymorphismGeneticsHuman GeneticsGenetic Association StudiesGenetics of DiseaseGenome-Wide Association StudiesComputer ScienceComputer ApplicationsSoftware EngineeringSoftware ToolsEngineeringJournal Article2014-03-0110.1371/journal.pone.0068585