TY - JOUR
T1 - Software for detecting gene-gene interactions in genome wide association studies
AU - Koo, Ching Lee
AU - Liew, Mei Jing
AU - Mohamad, Mohd Saberi
AU - Salleh, Abdul Hakim Mohamed
AU - Deris, Safaai
AU - Ibrahim, Zuwairie
AU - Susilo, Bambang
AU - Hendrawan, Yusuf
AU - Wardani, Agustin Krisna
N1 - Publisher Copyright:
© 2015, The Korean Society for Biotechnology and Bioengineering and Springer-Verlag Berlin Heidelberg.
PY - 2015/8/29
Y1 - 2015/8/29
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - bioinformatics
KW - epitasis network
KW - gene-gene interactions
KW - genome wide association studies
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U2 - 10.1007/s12257-015-0064-6
DO - 10.1007/s12257-015-0064-6
M3 - Review article
AN - SCOPUS:84942517885
SN - 1226-8372
VL - 20
SP - 662
EP - 676
JO - Biotechnology and Bioprocess Engineering
JF - Biotechnology and Bioprocess Engineering
IS - 4
ER -
