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 dc.contributor.author Guo, Yan-Fang dc.contributor.author Li, Jian dc.contributor.author Chen, Yuan dc.contributor.author Zhang, Li-Shu dc.contributor.author Deng, Hong-Wen dc.date.issued 2009-12-18 dc.description.abstract Abstract 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. Conclusion Our findings indicate the improved performance of SNP permutation and thus render pathway-based analysis of GWAS more applicable and attractive. dc.description.version Peer Reviewed dc.identifier.citation BMC Bioinformatics. 2009 Dec 18;10(1):429 dc.identifier.uri http://dx.doi.org/10.1186/1471-2105-10-429 dc.identifier.uri http://hdl.handle.net/10355/15023 dc.rights.holder Yan-Fang Guo et al.; licensee BioMed Central Ltd. dc.title A new permutation strategy of pathway-based approach for genome-wide association study eng dc.type Journal Article
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