GPU-based Genome-Wide SNP-SNP Interactions Detection and Pancreatic Cancer Susceptibility Analysis

the works in molecular biology proven that the Single Nucleotide Polymorphisms (SNPs) is related to complex diseases. The development of bioinformatics has made it possible to recognize a set of SNPs as factor to influence the risk about a specific disease. However, most methods ignore the possible small scale SNP-SNP interactions. Furthermore, due to the ultra-high dimension of SNP dataset, to detect the SNP-SNP interactions in the whole dataset based on CPU is difficult because of the time complexity. To change this situation, in this paper, we use the Graphics Processing Unit (GPU) to detect the SNP-SNP interactions in genome-wide sequence. And then, after matching and coding, we use this kind of information about SNP combination to analysis the disease susceptibility. Pancreatic cancer (PC) is one of the leading causes of deaths in the worldwide. In this paper we use real dataset about PC as an example, and the experimental result proven that our method is useful.