Publication: Fast Association Tests for Genes with FAST
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Date
2013
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Public Library of Science
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Chanda, 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.
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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
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Keywords
Biology, Computational Biology, Genomics, Genome Analysis Tools, Genome Scans, Population Genetics, Genetic Polymorphism, Genetics, Human Genetics, Genetic Association Studies, Genetics of Disease, Genome-Wide Association Studies, Computer Science, Computer Applications, Software Engineering, Software Tools, Engineering
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