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Assessing sources of inconsistencies in genotypes and their effects on genome-wide association studies with HapMap samples

2010; Springer Nature; Volume: 10; Issue: 4 Linguagem: Inglês

10.1038/tpj.2010.24

1473-1150

Huixiao Hong, Leming Shi, Ziying Su, Wenxuan Ge, Wendell Jones, Wendy Czika, Kelci Miclaus, Christophe G Lambert, Silvia C. Vega, J Zhang, Baitang Ning, Jie Liu, Baocun Green, Lang Xu, Hong Fang, Roger Perkins, Simon Lin, Nadereh Jafari, K Park, Tae Jin Ahn, Marco Chierici, Cesare Furlanello, L Zhang, Russ Wolfinger, Federico Goodsaid, Weida Tong,

Genomics and Rare Diseases

The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.