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Genotype imputation for soybean nested association mapping population to improve precision of QTL detection
Genotype imputation for soybean nested association mapping population to improve precision of QTL detection

Genotype imputation is a strategy to increase marker density of existing datasets without additional genotyping. We compared imputation performance of software BEAGLE 5.0, IMPUTE 5 and AlphaPlantImpute and tested software parameters that may help to improve imputation accuracy in soybean populations. Several factors including marker density, extent of linkage disequilibrium (LD), minor allele frequency (MAF), etc.

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