Novel generating protective single nucleotide polymorphism barcode for breast cancer using particle swarm optimization.
BACKGROUND
High-throughput single nucleotide polymorphism (SNP) genotyping generates a huge amount of SNP data in genome-wide association studies. Simultaneous analyses for multiple SNP interactions associated with many diseases and cancers are essential; however, these analyses are still computationally challenging.


METHODS
In this study, we propose an odds ratio-based binary particle swarm optimization (OR-BPSO) method to evaluate the risk of breast cancer.


RESULTS
BPSO provides the combinational SNPs with their corresponding genotype, called SNP barcodes, with the maximal difference of occurrence between the control and breast cancer groups. A specific SNP barcode with an optimized fitness value was identified among seven SNP combinations within the space of one minute. The identified SNP barcodes with the best performance between control and breast cancer groups were found to be control-dominant, suggesting that these SNP barcodes may prove protective against breast cancer. After statistical analysis, these control-dominant SNP barcodes were processed for odds ratio analysis for quantitative measurement with regard to the risk of breast cancer.


CONCLUSIONS
This study proposes an effective high-speed method to analyze the SNP-SNP interactions for breast cancer association study.
Yang
Cheng-Hong
CH
Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan. chyang@cc.kuas.edu.tw
Chang
Hsueh-Wei
HW
Cheng
Yu-Huei
YH
Chuang
Li-Yeh
LY
D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D016022:Case-Control Studies; D001330:Electronic Data Processing / Q000379:methods*; D005260:Female; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016017:Odds Ratio; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*