Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements.The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware.The large number of SNPs available provides opportunities for detecting DNA variations associated with complex traits through GWAS using SNP markers. This is because an increased number of SNPs increases the chance that some SNPs may be DNA variations affecting phenotypes (direct SNP effects) or results in increased linkage disequilibrium (LD) with DNA variations that have direct effects on the phenotypes (indirect SNP effects). With high throughput SNP genotyping technology, SNP genotyping of a large number of individuals is becoming increasingly practical. Such large scale SNP genotyping increases the effectiveness of SNP association studies and provides an unprecedented opportunity to study complex genetic