Tools for Testing SNP Effects in Genetic Studies
Author Information
Author(s): Ma Li, Runesha H Birali, Dvorkin Daniel, Garbe John R, Da Yang
Primary Institution: University of Minnesota
Hypothesis
Can parallel and serial computing tools effectively test single-locus and epistatic SNP effects on quantitative traits in genome-wide association studies?
Conclusion
The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, while the epiSNP serial computing programs are convenient for small scale analyses.
Supporting Evidence
- The EPISNPmpi program achieved excellent scalability for large scale analysis.
- The EPISNP program is designed for small scale GWAS on commonly available computer hardware.
- The study provides tools for testing all possible pairwise epistasis effects.
Takeaway
This study created computer programs to help scientists find out how different genes work together to affect traits, making it easier to analyze large amounts of genetic data.
Methodology
The study developed EPISNPmpi for parallel computing and EPISNP for serial computing to test SNP effects using a general linear model and the extended Kempthorne model.
Limitations
The computational difficulty increases significantly with the number of SNPs, making large-scale three-SNP epistasis testing currently infeasible.
Participant Demographics
The study involved 2000 individuals for the analysis.
Digital Object Identifier (DOI)
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