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Chunk #1 — Background

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An empirical evaluation of imputation accuracy for association statistics reveals increased type-I error rates in genome-wide associations.
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ranging from hundreds of thousands to millions of typed markers [5]. This diversity in panels of markers limits even further the full potential of genome-wide association studies to uncover variants putatively implicated in the susceptibility to diseases or other complex phenotypes of interest. This heterogeneity transforms the comparison, as well as, the combination of data results generated from distinct genome-wide panels into a challenging endeavor [6].