Fast association tests for genes with FAST.
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.


BACKGROUND
https://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Home.
Department of Biomedical Engineering and Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
Pritam
P
Chanda
Hailiang
H
Huang
Dan E
DE
Arking
Joel S
JS
Bader
D003198:Computer Simulation; D030541:Databases, Genetic; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012984:Software