MTHSA-DHEI: multitasking harmony search algorithm for detecting high-order SNP epistatic interactions

作者：Shouheng Tuo, Chao Li, Fan Liu, Aimin Li, Lang He, Zong Woo Geem, Junliang Shang, Haiyan Liu, YanLing Zhu, Zengyu Feng, TianRui Chen · 发表于：Complex & Intelligent Systems · 年份：2022 · DOI：10.1007/s40747-022-00813-7 · 被引用次数：34 · 研究领域：Genetic Associations and Epidemiology、Bioinformatics and Genomic Networks、Machine Learning in Bioinformatics

Abstract Genome-wide association studies have succeeded in identifying genetic variants associated with complex diseases, but the findings have not been well interpreted biologically. Although it is widely accepted that epistatic interactions of high- order single nucleotide polymorphisms (SNPs) [(1) Single nucleotide polymorphisms (SNP) are mainly deoxyribonucleic acid (DNA) sequence polymorphisms caused by variants at a single nucleotide at the genome level. They are the most common type of heritable variation in humans.] are important causes of complex diseases, the combinatorial explosion of millions of SNPs and multiple tests impose a large computational burden. Moreover, it is extremely challenging to correctly distinguish high- order SNP epistatic interactions from other high- order SNP combinations due to small sample sizes. In this study, a multitasking harmony search algorithm (MTHSA-DHEI) is proposed for detecting high- order epistatic interactions [(2) In classical genetics, if genes X1 and X2 are mutated and each mutation by itself produces a unique disease status (phenotype) but the mutations together cause the same disease status as the gene X1 mutation, gene X1 is epistatic and gene X2 is hypostatic, and gene X1 has an epistatic effect (main effect) on disease status. In this work, a high-order epistatic interaction occurs when two or more SNP loci have a joint influence on disease status.], with the goal of simultaneously detecting multiple types of high- ord...