Software for detecting gene-gene interactions in genome wide association studies

Ching Lee Koo, Mei Jing Liew, Mohd Saberi Mohamad, Abdul Hakim Mohamed Salleh, Safaai Deris, Zuwairie Ibrahim, Bambang Susilo, Yusuf Hendrawan, Agustin Krisna Wardani

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)


Nowadays, genome-wide association studies (GWAS) have offered hundreds of thousands of single nucleotide polymorphism (SNPs). The studies of epistatic interactions of SNPs (denoted as gene-gene interactions or epitasis) are particularly important to unravel the genetic basis to complex multifactorial diseases. However, the greatest challenging and unsolved issue in GWAS is to discover epistatic interactions among large amount of SNPs data. Besides, traditional statistical approaches cannot solve such epistasis phenomenon due to possessing high dimensional data and the occurring of multiple polymorphisms. Hence, various kinds of promising software have been extensively investigated in order to solve these problems. This paper gives an overview on the software that had been used to detect gene-gene interactions that bring the effect on common and multifactorial diseases. Furthermore, sources, link, and functions description to the software are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of software that had been widely used in detecting epistatic interactions in complex human diseases.

Original languageEnglish
Pages (from-to)662-676
Number of pages15
JournalBiotechnology and Bioprocess Engineering
Issue number4
Publication statusPublished - Aug 29 2015
Externally publishedYes


  • artificial intelligence
  • bioinformatics
  • epitasis network
  • gene-gene interactions
  • genome wide association studies

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology
  • Biomedical Engineering


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