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Chunk #14 — Results — Characteristics of the false-positive signals

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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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when imputation methods were applied. Specifically, polymorphisms located at chromosomes 1, 3 and 15 showed the largest bias in favor of imputed measures. The most prominent biases are concentrated in imputed markers considered strongly associated (p < 10-10) to diabetes in contrast to their empiric frequencies, inflating considerably the number of associated markers. The number of these "low imputation quality" markers is limited especially when compared to the immense number of markers analyzed that could, consequently, pass undetected by common diagnostic analysis.