alexa Evaluating HapMap SNP data transferability in a large-scale genotyping project involving 175 cancer-associated genes.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Ribas G, GonzlezNeira A, Salas A, Milne RL, Vega A,

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Abstract One of the many potential uses of the HapMap project is its application to the investigation of complex disease aetiology among a wide range of populations. This study aims to assess the transferability of HapMap SNP data to the Spanish population in the context of cancer research. We have carried out a genotyping study in Spanish subjects involving 175 candidate cancer genes using an indirect gene-based approach and compared results with those for HapMap CEU subjects. Allele frequencies were very consistent between the two samples, with a high positive correlation (R) of 0.91 (P<<1x10(-6)). Linkage disequilibrium patterns and block structures across each gene were also very similar, with disequilibrium coefficient (r (2)) highly correlated (R=0.95, P<<1x10(-6)). We found that of the 21 genes that contained at least one block larger than 60 kb, nine (ATM, ATR, BRCA1, ERCC6, FANCC, RAD17, RAD50, RAD54B and XRCC4) belonged to the GO category "DNA repair". Haplotype frequencies per gene were also highly correlated (mean R=0.93), as was haplotype diversity (R=0.91, P<<1x10(-6)). "Yin yang" haplotypes were observed for 43\% of the genes analysed and 18\% of those were identical to the ancestral haplotype (identified in Chimpazee). Finally, the portability of tagSNPs identified in the HapMap CEU data using pairwise r (2) thresholds of 0.8 and 0.5 was assessed by applying these to the Spanish and current HapMap data for 66 genes. In general, the HapMap tagSNPs performed very well. Our results show generally high concordance with HapMap data in allele frequencies and haplotype distributions and confirm the applicability of HapMap SNP data to the study of complex diseases among the Spanish population. This article was published in Hum Genet and referenced in Journal of Proteomics & Bioinformatics

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