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Generating SNP barcode to evaluate SNP-SNP interaction of disease by particle swarm optimization.

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.

journal_name

Comput Biol Chem

journal_title

Computational biology and chemistry

authors

Chang HW,Yang CH,Ho CH,Wen CH,Chuang LY

doi

10.1016/j.compbiolchem.2008.07.029

subject

Has Abstract

pub_date

2009-02-01 00:00:00

pages

114-9

issue

1

eissn

1476-9271

issn

1476-928X

pii

S1476-9271(08)00105-9

journal_volume

33

pub_type

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