Abstract
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 language | English |
|---|---|
| Pages (from-to) | 662-676 |
| Number of pages | 15 |
| Journal | Biotechnology and Bioprocess Engineering |
| Volume | 20 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Aug 29 2015 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- 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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