A new permutation strategy of pathway-based approach for genome-wide association study.
BACKGROUND
Recently introduced pathway-based approach is promising and advantageous to improve the efficiency of analyzing genome-wide association scan (GWAS) data to identify disease variants by jointly considering variants of the genes that belong to the same biological pathway. However, the current available pathway-based approaches for analyzing GWAS have limited power and efficiency.


RESULTS
We proposed a new and efficient permutation strategy based on SNP randomization for determining significance in pathway analysis of GWAS. The developed permutation strategy was evaluated and compared to two previously available methods, i.e. sample permutation and gene permutation, through simulation studies and a study on a real dataset. Results showed that the proposed permutation strategy is more powerful and efficient with greatly reducing the computational complexity.


CONCLUSIONS
Our findings indicate the improved performance of SNP permutation and thus render pathway-based analysis of GWAS more applicable and attractive.
Guo
Yan-Fang
YF
1School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, PR China. guoyanfang@gmail.com
Li
Jian
J
Chen
Yuan
Y
Zhang
Li-Shu
LS
Deng
Hong-Wen
HW
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D020641:Polymorphism, Single Nucleotide