Abstract
BackgroundGenome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS.ResultsThe 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.ConclusionThe 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.
Highlights
Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect
Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS due to the large number of SNP combinations
A parallel computing program named EPISNPmpi and a serial computing program named EPISNP were developed for genome-wide pairwise epistasis testing
Summary
Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. 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 (page number not for citation purposes). Assuming HWE and LE, Cockerham [10] and Kempthorne [11] partitioned Fisher's epistasis effect into four components using two different methods: additive × additive (A × A), additive × dominance (A × D), dominance × additive (D × A), and dominance × dominance (D × D) epistasis effects with the genetic interpretation of allele × allele, allele × genotype, genotype × allele, and genotype × genotype interactions respectively This partitioning can be used as a tool for identifying the exact mode of a gene interaction effect. The parallel and serial computing software developed in this research is intended to provide computational tools for pairwise epistasis testing in GWAS on various parallel and serial computing platforms with the capability of pairwise epistasis testing for any large GWAS currently in existence
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