Imputation of missing genetic markers SNP using linear regression models

Anita Kranjčevičová, Josef Přibyl


For imputation of missing SNP are used softwares which require known relationship between genotyped individuals. In common breeding business the genotypes of parents are not always known. That is why our own methodological process was used. The aim of this study is to map the current research of genetic chips and to verify the calculation process. The testing was processed at chosen loci in two datasets and in 8 models with different amount of SNPs. For the dataset A was prediction of missing values almost accurate with model reliability 100% with the exception of one homozygous locus where the reliability reached only 55%. In the dataset B the most extensive model reached the reliability of 80 - 90% even in case of homozygous loci. The prediction error value was higher than in the first case. It was proven that missing values prediction is possible to calculate using the neighbouring SNPs.

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