Àá½Ã¸¸ ±â´Ù·Á ÁÖ¼¼¿ä. ·ÎµùÁßÀÔ´Ï´Ù.
KMID : 1094720150200040662
Biotechnology and Bioprocess Engineering
2015 Volume.20 No. 4 p.662 ~ p.676
Software for detecting gene-gene interactions in genome wide association studies
Koo Ching Lee

Liew Mei Jing
Mohamad Mohd Saberi
Salleh Abdul Hakim Mohamed
Deris Safaai
Ibrahim Zuwairie
Susilo Bambang
Hendrawan Yusuf
Wardani Agustin Krisna
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.
KEYWORD
epitasis network, gene-gene interactions, genome wide association studies, artificial intelligence, bioinformatics
FullTexts / Linksout information
 
Listed journal information
SCI(E) ÇмúÁøÈïÀç´Ü(KCI)