title: Identifying interacting genetic variations by fish-swarm logic regression.
abstract: Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds.
authors.affiliation: Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
authors.forename: Xuanping
authors.initials: X
authors.lastname: Zhang
authors.forename: Jiayin
authors.initials: J
authors.lastname: Wang
authors.forename: Aiyuan
authors.initials: A
authors.lastname: Yang
authors.forename: Chunxia
authors.initials: C
authors.lastname: Yan
authors.forename: Feng
authors.initials: F
authors.lastname: Zhu
authors.forename: Zhongmeng
authors.initials: Z
authors.lastname: Zhao
authors.forename: Zhi
authors.initials: Z
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D056726:Genetic Association Studies; D014644:Genetic Variation; D006801:Humans; D016015:Logistic Models; D009154:Mutation / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics