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

机译:评估基因型不一致的来源及其对与HapMap样本进行的全基因组关联研究的影响

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摘要

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 wasobserved 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.
机译:独立的全基因组关联研究(GWAS)的结果不一致表明了I型和II型错误的可能性。我们评估了支持GWAS的当前Affymetrix技术的可重复性。原始强度和基因型/拷贝数变异均观察到了合理的可重复性。我们还评估了不同SNP阵列之间以及基因型调用算法之间的一致性。我们观察到基因型的不一致在样本水平上通常很小。为了进一步检查与基因分型和基因型调用的差异是否可能是GWAS结果变异的来源,应用了关联分析来比较相关的SNP。我们观察到基因型的不一致不仅传播到关联分析,而且在相关的SNP中被放大。我们的研究表明,SNP阵列之间以及基因型调用算法之间的不一致是导致GWAS结果缺乏可重复性的潜在原因。

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