TY - JOUR
T1 - CCRaVAT and QuTie - enabling analysis of rare variants in large-scale case control and quantitative trait association studies
AU - Lawrence, Robert
AU - Day-Williams, Aaron G.
AU - Elliott, Katherine S.
AU - Morris, Andrew P.
AU - Zeggini, Eleftheria
N1 - Funding Information:
Funding: This work was funded by the Wellcome Trust (WT088885/Z/09/Z and 079557MA).
PY - 2010/10/21
Y1 - 2010/10/21
N2 - Background: Genome-wide association studies have been successful in finding common variants influencing common traits. However, these associations only account for a fraction of trait heritability. There has been a shift in the field towards studying low frequency and rare variants, which are now widely recognised as putative complex trait determinants. Despite this increasing focus on examining the role of low frequency and rare variants in complex disease susceptibility, there is a lack of user-friendly analytical packages implementing powerful association tests for the analysis of rare variants.Results: We have developed two software tools, CCRaVAT (Case-Control Rare Variant Analysis Tool) and QuTie (Quantitative Trait), which enable efficient large-scale analysis of low frequency and rare variants. Both programs implement a collapsing method examining the accumulation of low frequency and rare variants across a locus of interest that has more power than single variant analysis. CCRaVAT carries out case-control analyses whereas QuTie has been developed for continuous trait analysis.Conclusions: CCRaVAT and QuTie are easy to use software tools that allow users to perform genome-wide association analysis on low frequency and rare variants for both binary and quantitative traits. The software is freely available and provides the genetics community with a resource to perform association analysis on rarer genetic variants.
AB - Background: Genome-wide association studies have been successful in finding common variants influencing common traits. However, these associations only account for a fraction of trait heritability. There has been a shift in the field towards studying low frequency and rare variants, which are now widely recognised as putative complex trait determinants. Despite this increasing focus on examining the role of low frequency and rare variants in complex disease susceptibility, there is a lack of user-friendly analytical packages implementing powerful association tests for the analysis of rare variants.Results: We have developed two software tools, CCRaVAT (Case-Control Rare Variant Analysis Tool) and QuTie (Quantitative Trait), which enable efficient large-scale analysis of low frequency and rare variants. Both programs implement a collapsing method examining the accumulation of low frequency and rare variants across a locus of interest that has more power than single variant analysis. CCRaVAT carries out case-control analyses whereas QuTie has been developed for continuous trait analysis.Conclusions: CCRaVAT and QuTie are easy to use software tools that allow users to perform genome-wide association analysis on low frequency and rare variants for both binary and quantitative traits. The software is freely available and provides the genetics community with a resource to perform association analysis on rarer genetic variants.
UR - http://www.scopus.com/inward/record.url?scp=77958067631&partnerID=8YFLogxK
U2 - 10.1186/1471-2105-11-527
DO - 10.1186/1471-2105-11-527
M3 - Article
C2 - 20964851
AN - SCOPUS:77958067631
SN - 1471-2105
VL - 11
JO - BMC Bioinformatics
JF - BMC Bioinformatics
M1 - 527
ER -