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Comparisons of testing accuracies among prediction models with and without imputation across different platforms revealed that prediction models built with imputed SNPs were more accurate than those built without imputed SNPs (average accuracies of 89.61% and 88.30%, respectively, for CT = 0; Figure 2).
We also compared testing accuracies among predictive models with and without imputation across different platforms, the results revealed that predictive models built with imputed SNPs were more accurate than those without (average accuracies of 89.61% and 88.30%, respectively, for CT = 0; Figure 2).
However, there was not a clear scenario that was the "best" for genotype imputation across the two genes and three races.
Two analyses were performed using this dataset along with the UK dataset to investigate imputation across populations.
We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs.
Including one, two and four genotyped offspring increased the accuracy of imputation across all animals from 0.57 (no offspring) to 0.73, 0.82, and 0.92, respectively.
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We restricted the analysis of the associations of interest only to subjects with one or more measures of alcohol available (n = 7921), including early alcohol onset, as outcome imputations across cycles out with this sample were unstable [ 44].
Although most large studies have so far been based on meta-analysis of HapMap-based imputations across cohorts, the primary limitation is that HapMap is essentially restricted to common variation (MAF>5%).
Nevertheless, for all densities, both the haploid and diploid ADCL panels consistently outperformed their PD counterparts in terms of imputation accuracy across all sites, as well as across only the low-frequency variants.
Despite this simplistic modeling of co-expression relationships, we achieve high imputation accuracy across populations and platforms.
Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com