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Genotype imputation can be used to increase sample sizes by imputation of sequence variants (from a sequencing study) into large numbers of samples with genome-wide array data.
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Variation due to differences in template length can be overcome in part by greater depth of sequencing or by imputation of missing data [ 10, 15].
Imputation of sequence variants from related individuals or extended pedigrees can also boost imputation accuracy.
Haplotype scans were refined by imputation with the catalogue of sequence variation segregating in the CC to suggest potential candidate genes.
Variation in template copy number among pooled genotypes can be compensated for by deeper sequencing, imputation of missing data, or by rerunning samples sequenced at low depth.
The incomplete data set is completed by iterative imputation of the missing values with the corresponding imputation model.
Thus, if the genotypes of validation animals were affected by imputation errors, accuracies of GEBV may increase as a result of an increased imputation accuracy.
Imputation reliability was also affected by the MAF of the imputed SNPs and by the number of sequenced individuals.
The most strongly associated SNPs identified in this study by imputation reside within ERAP1 regulatory sequences.
By sequencing the whole genomes of 2,630 Icelanders, followed by imputation into large sets of GWAS data, novel associations between rare variants in APP and Alzheimer's disease and between rare variants in PDX1 and T2D were identified [ 39, 75].
In contrast to crops and livestock, human sequence data are available and accuracy of imputation to sequence data has been investigated e.g. [ 14- 16], which showed that accuracy of imputation was influenced by reference group composition (e.g. size or populations included), number of markers on the lower density marker panel, and MAF of imputed SNPs.
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