Ant colony optimisation to identify genetic variant association with type 2 diabetes

Christmas, Jacqueline; Keedwell, Edward; Frayling, Timothy M.; Perry, John

doi:10.1016/j.ins.2010.12.005

Cited by 37 publications

(19 citation statements)

References 35 publications

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“…Once one or a set of SNPs has been selected, samples will be divided into two sets according to [3], the 'observed positive' set in which samples with a disease status of 1 are true positives (TP), the remainder false positives (FP), and the 'observed negative' set in which samples with a disease status of 0 are true negatives (TN), the remainder false negatives (FN). For example, the trail in Figure 1(b) requires that members of 'observed positive' set have both 'AT' at SNP position 2 and 'CG' at SNP position 4.…”

Section: Roulette Wheel Selection and Distance Of A Pathmentioning

confidence: 99%

A new approach to detect epistasis utilizing parallel implementation of ant colony optimization by MapReduce framework

Zhou

Liu

2015

International Journal of Computer Mathematics

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Genome-wide association studies (GWAS) involve the detection and interpretation of epistasis, which is responsible for the 'missing heritability' and influences common complex disease susceptibility. Many epistasis detection algorithms cannot be directly applied into GWAS as many combinations of genetic components are present in only a small amount of samples or even none at all. For a huge number of single nucleotide polymorphisms and inappropriate statistical tests, epistasis detection remains a computational and statistical challenge in genetic epidemiology. Here, we develop a novel method to identify epistatic interactions related to disease susceptibility utilizing an ant colony optimization strategy implemented by Google's MapReduce platform. We incorporate expert knowledge used to guide ants to make the best choice in the search process into the pheromone updating rule. We conduct sufficient experiments using simulated and real genome-wide data sets and experimental results demonstrate excellent performance of our algorithm compared with its competitors.

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Section: Roulette Wheel Selection and Distance Of A Pathmentioning

confidence: 99%

A new approach to detect epistasis utilizing parallel implementation of ant colony optimization by MapReduce framework

Zhou

Liu

2015

International Journal of Computer Mathematics

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“…There are a number of standard models of interaction between genes, for example the additive model states that the effect of one gene adds to the effect of another, in contrast in epistasis, SNPs have relatively small individual effects but the combined effect of SNPs is large. This usually implements the AN D model of combination [23], individuals will have one genotype (e.g. RH) AND another genotype (e.g.…”

Section: ) Genotypes and Logical Combinationsmentioning

confidence: 99%

“…Thus this function leads the search process of the algorithm and is therefore a key aspect of the algorithm. The fitness function is based on standard statistical measures that are implemented on a binary classification of controls and cases in genome wide association studies [16], [23] and are described below.…”

Section: ) Fitness Functionmentioning

confidence: 99%

“…Readers are referred to the GWAS literature for more information on these criteria [34], [23]. The SNPs kept are those meeting the following standard conditions in the 3,004 control samples:…”

Section: A Exclusion Criteriamentioning

confidence: 99%

“…Wrapper approaches include decision tree [19], neural networks [20], odds ratio [21] and filtering-based approaches [22] in addition to stochastic techniques such as ant colony optimisation (ACO) [23], [24], [25] that has been shown to be a promising technique. In our previous work, we have demonstrated how the ACO algorithm can be used to search for gene-gene interactions for type II diabetes [25] in a full set of GWAS data, comprising many SNPs and individuals without utilising expert knowledge.…”

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confidence: 99%

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An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier]

Sapin

Keedwell

Frayling

2015

IEEE Comput. Intell. Mag.

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In this paper, a novel ant colony optimisation and tabu list approach for the discovery of gene-gene interactions in genome-wide association study data is proposed. The method is tested on a number of diseases drawn from the large established database, the Wellcome Trust Case Control Consortium which contains hundreds of thousands of small DNA changes known as single nucleotide polymorphisms. To analyse full scale genome-wide association study data, the standard ant colony optimisation algorithm has been adapted, with tournament path selection, a subset based approach, and tabu list included in the algorithm. These modifications, in addition to the use of a statistical test of significance of single nucleotide polymorphism interactions as a fitness function, greatly increase execution speeds and permit the discovery of combinations of single nucleotide polymorphisms that can discriminate cases and controls. The methodology is applied to several large-scale genome-wide association study disease datasets namely, inflammatory bowel disease, rheumatoid arthritis, type I diabetes and type II diabetes patients to discover putative gene-gene interactions in reasonable time on modest hardware.

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Black Hole Algorithm and Its Applications

Kumar

Datta

Singh

2014

Studies in Computational Intelligence

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Ant colony optimisation to identify genetic variant association with type 2 diabetes

Cited by 37 publications

References 35 publications

A new approach to detect epistasis utilizing parallel implementation of ant colony optimization by MapReduce framework

A new approach to detect epistasis utilizing parallel implementation of ant colony optimization by MapReduce framework

An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier]

Black Hole Algorithm and Its Applications

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