A review on methods for detecting SNP interactions in high-dimensional genomic data
Access Status
Authors
Date
2016Type
Metadata
Show full item recordCitation
Source Title
ISSN
School
Collection
Abstract
In this era of genome-wide association studies (GWAS), the quest for understanding the genetic architecture of complex diseases is rapidly increasing more than ever before. The development of high throughput genotyping and next generation sequencing technologies enables genetic epidemiological analysis of large scale data. These advances have led to the identification of a number of single nucleotide polymorphisms (SNPs) responsible for disease susceptibility. The interactions between SNPs associated with complex diseases are increasingly being explored in the current literature. These interaction studies are mathematically challenging and computationally complex. These challenges have been addressed by a number of data mining and machine learning approaches. This paper reviews the current methods and the related software packages to detect the SNP interactions that contribute to diseases. The issues that need to be considered when developing these models are addressed in this review. The paper also reviews the achievements in data simulation to evaluate the performance of these models. Further, it discusses the future of SNP interaction analysis
Related items
Showing items related by title, author, creator and subject.
-
Takechi, Ryusuke (2010)It has been reported that lifestyle including diet is associated with Alzheimer’s disease (AD) risk and progression. Population studies indicate that the chronic consumption of diets enriched in saturated fats (SFA) and ...
-
Global Burden of Disease Study 2013 Collaborators; Miller, Ted (2015)Background: Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the ...
-
Miller, Ted (2015)Summary Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health ...