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Review of Computer Engineering Research

December 2021, Volume 8, 2, pp 27-40

Two-Stage Model with Rough Cluster and Salp Optimization Technique for Epistasis Detection

S Priya


R Manavalan

S Priya 1

R Manavalan 2

  1. Research Scholar, Department of Computer Science, Arignar Anna Government Arts College, Villupuram, Tamilnadu, India. 1

  2. Assistant Professor, Department of Computer Science, Arignar Anna Government Arts College, Villupuram, Tamilnadu, India. 2

on Google Scholar
on PubMed

Pages: 27-40

DOI: 10.18488/journal.76.2021.82.27.40

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Article History:

Received: 12 July, 2021
Revised: 16 August, 2021
Accepted: 07 September, 2021
Published: 23 September, 2021


The discovery of gene-gene interactions to identify complex diseases is one of the primary challenges in genome-wide association studies (GWAS). Genetic interactions (Epistasis) are typically seen as interactions between various single nucleotide polymorphisms (SNPs). Genetic interactions discovery can assist the researchers in identifying gene pathways, recognizing gene activity, and discovering potential drug targets. Rough Cluster based Salp Optimization for Epistasis detection (RCSalp-Epi) is a two-stage epistasis model that has been evaluated on a variety of simulated disease models. In the screening stage, the rough clustering algorithm is employed to partition the genotype data into different clusters. The selection stage presents Salp optimization with a single objective function (SalpEpi-SO) and multiple objective functions (SalpEpi-MO) over the clusters to find disease-related SNP combinations. RCSalp-performance Epi's is evaluated in comparison with SalpEpi-SO and SalpEpi-MO. The outcome of the experimental analysis revealed that RCSalp-Epi-MO is superior to SalpEpi-SO and SalpEpi-MO in terms of power and execution time.
Contribution/ Originality
The paper's primary contribution is finding the higher order genetic interactions with high detection power and minimal computational effort.


Epistasis, Genetic interactions, Salp optimization, Cluster, Rough k-means, Single nucleotide polymorphism (SNPs).



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This study received no specific financial support.

Competing Interests:

The authors declare that they have no competing interests.


Both authors contributed equally to the conception and design of the study.

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