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Detailed information on the imputation procedure and population characteristics based on the original data set and the imputed data sets are presented in Supplemental Material, Tables S1 and S2 (http://dx.doi.org/10.1289/ehp.1204918).org/10.1289/ehp.1204918
These criteria were: (1) without any filtering options on SNPs, (2) filtering on the imputation quality of R > 0.8, leaving only the high quality imputed SNPs and (3) filtering with R > 0.8 and MAF > 0.01, additionally excluding alleles with low minor allele frequency.
Two iterations of GD are applied on the imputation of CCGs.
This work also considers three different mechanisms governing the distribution of missing values in a dataset, and examines the impact of noise on the imputation process.
The average performance of classifiers has been listed based on the imputation by K-nearest neighbor (Knn = 1, Knn = 3, Knn = 5, and Knn = 7), mean, and medoid, respectively.
qRegression analyses based on the non-imputed data deliver only marginally different results, which is why I consider details on the imputation procedure and the imputation model to be of little interest to the reader.
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For k-NN imputations, selection of k has an influence on the accuracy of the imputation.
To assess the impact of sample size on the imputation-based estimation of diversity parameters, we performed extra simulations on the wheat data set with the PP imputation method for four sample size combinations of breeding lines (130, 260) and SNP markers (1000, 10,000).
The results based on the imputations are only valid if the data were MAR, and we had specified appropriate imputation models.
In all the scenarios the accuracies of DGV from imputed genotypes are higher than from the actual smaller subset of SNPs on which the imputation is based.
Researchers should spend efforts on specifying the imputation model correctly, rather than expecting predictive mean matching or local residual draws to do the work.
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Justyna Jupowicz-Kozak
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