On Combining Reference Data to Improve Imputation Accuracy

On Combining Reference Data to Improve Imputation Accuracy

Genotype imputation is an important tool in human genetics studies, which uses reference sets with known genotypes and prior knowledge on linkage disequilibrium and recombination rates to infer un-typed alleles for human genetic variations at a low cost. The reference sets used by current imputation approaches are based on HapMap data, and/or based on recently available next-generation sequenci...

Effect of Reference Population Size and Imputation Methods on the Accuracy of Imputation in Pure and Mixed Populations

    Imputation as a method of creating low-density chips to high-density chips has been introduced to increase the accuracy of genomic selection in animals. In the current study, to investing imputation accuracy, three populations of mixed (scenario 1), pure (scenario 2) and mixed + pure (scenario 3) were simulated using QMSim. Two methods of imputation including Beagle and Flmpute were used fo...

Genotype imputation accuracy with different reference panels in admixed populations

Genome-wide association studies have successfully identified common variants that are associated with complex diseases. However, the majority of genetic variants contributing to disease susceptibility are yet to be discovered. It is now widely believed that multiple rare variants are likely to be associated with complex diseases. Using custom-made chips or next-generation sequencing to uncover ...

Multiple imputation can improve data quality

managing Multiple imputation can improve data quality.

Impacts of combining meteorological and hydrometric data on the accuracy of streamflow modeling