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Minimac Diagnostics

955 bytes added, 09:10, 31 January 2013
Leave One Out Statistics
== Leave One Out Statistics ==
 
To evaluate imputation quality, Minimac hides data for each genotyped SNP in turn and calculates 3 statistics, described below.
=== looRsq : Estimated R-squared in Leave-One-Out Analysis ===
 
This first statistic is calculated by hiding all known genotypes for the SNP, imputing it and then estimating imputation accuracy. It doesn't use the known genotypes for the SNP at all.
=== empR : Correlation Between Imputed and True Genotypes ===
 
Whereas looRsq statistic completely ignores experimental genotypes, this one is based on a comparison of imputed and experimental genotypes. A negative correlation between imputed and experimental genotypes can indicate allele flips.
=== empRsq : Squared Correlation Between Imputed and True Genotypes ===
 
Whereas looRsq statistic reports the estimated imputation accuracy, this one reports the ''actual'' imputation accuracy - as estimated by comparing genotypes generated using imputation (after hiding any known genotypes for the marker) and the previously hidden known genotypes. By comparing empRsq and looRsq it should be possible to tell whether estimates of imputation accuracy are well calibrated.