Brief Communication: Generating SNP barcode to evaluate SNP-SNP interaction of disease by particle swarm optimization

Authors:
Hsueh-Wei Chang;Cheng-Hong Yang;Chang-Hsuan Ho;Cheng-Hao Wen;Li-Yeh Chuang
Affiliations:
Faculty of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan and Graduate Institute of Natural Products, College of Pharmacy, Kaohsiung Medical Universi ...;Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan;Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan;Faculty of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan;Department of Chemical Engineering, I-Shou University, Kaohsiung, Taiwan
Venue:
Computational Biology and Chemistry
Year:
2009

Citing 1
Cited 1

Odds ratio based multifactor-dimensionality reduction method for detecting gene--gene interactions

Bioinformatics

Evaluation of Breast Cancer Susceptibility Using Improved Genetic Algorithms to Generate Genotype SNP Barcodes

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

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Abstract

Genome-wide association analysis involved many single-nucleotide polymorphisms (SNPs) data is challenging mathematically and computationally. Hence, we propose the odds ratio-based discrete binary particle swarm optimization (OR-DBPSO) method that uses the OR as a new quantitative measure of disease risk among many SNP combinations with genotypes called ''SNP barcode''. DBPSO are applied to generate SNP barcode, which computes the maximal difference of occurrence between the case and control groups, to predict disease susceptibility such as osteoporosis. Different SNP barcode patterns may occur several times in either low or high bone mineral density (BMD) groups. Our results showed that a DBPSO can effectively identify a specific SNP barcode with an optimized fitness value. SNP barcodes with a low fitness value will naturally be discarded from the population. A representative SNP barcode with a variable number of SNPs is processed to OR analysis to determine the maximum difference between the low and high BMD groups in statistics manner. Therefore, this paper introduces a powerful procedure to analyze disease-associated SNP-SNP interaction in genome-wide genes.