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Chunk #18 — Results — Key indicators of a poor imputation performance on association statistics

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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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of markers, especially the ones showing MAF very close to 0,5, have an increased odds of being biased. The barrier is probably imposed by allele misspecification and is a challenging one, since a specific allele could be wrongly imputed leading to a totally spurious association statistic. A similar result was detected by an empirical evaluation of the imputation algorithm IMPUTE regarding accuracy of genotype determination [10].