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'''Warning''': Imputation involving masked datasets should be performed separately for imputation quality estimation. For production, one should use all available information.
'''Warning''': Imputation involving masked datasets should be performed separately for imputation quality estimation. For production, one should use all available information.
== How do I interpret the imputation quality estimates? ==
In the simple approach, you will only get concordance/error estimates. There are two aspects to check. (1) the ratio between the genotypic error and allelic error. We expect that only a small proportion of errors where one homozygote is imputed as the other homozygote. Therefore, a ~2:1 ratio is expected. (2) the absolute error rate. There are several factors influencing imputation quality including the population to be imputed, the reference population and the genotyping panel used. Typically, we expect <2% allelic error rate among Caucasians and East Asians; 3-5% among Africans and African Americans. Figure below show imputation quality from the Human Genome Diversity Project (HGDP) for 52 populations across the world and by different HapMap reference panel.
[[File:http://www.sph.umich.edu/csg/yli/figure3.gif]]
Table 3 in the MaCH 1.0 paper tabulates imputation quality by commercial panel in CEU, YRI, and CHB+JPT.
== Shall I apply QC before or after imputation? If so, how? ==
== Shall I apply QC before or after imputation? If so, how? ==
