Motivation: Despite recent advances of modern GWAS methods, it is still remains an important problem of addressing calculation an effect size and corresponding p-value for the whole gene rather than for single variant.
Results: We developed an R package rqt, which offers gene-level GWAS meta-analysis. The package can be easily included into bioinformatics pipeline or used stand-alone. We applied this tool to the analysis of Alzheimer's disease data from three datasets CHS, FHS and LOADFS. Test results from meta-analysis of three Alzheimer studies show its applicability for association testing.
Availability And Implementation: The package rqt is freely available under the following link: https://github.com/izhbannikov/rqt.
Contact: ilya.zhbannikov@duke.edu.
Supplementary Information: Supplementary data are available at Bioinformatics online.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860520 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/btx395 | DOI Listing |
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