Genetic diversity analysis of highly incomplete SNP genotype data with imputations: an empirical assessment.

ABSTRACT: Genotyping by sequencing (GBS) recently has emerged as a promising genomic approach for assessing genetic diversity on a genome-wide scale. However, concerns are not lacking about the uniquely large unbalance in GBS genotype data. Although some genotype imputation has been proposed to infer missing observations, little is known about the reliability of a genetic diversity analysis of GBS data, with up to 90% of observations missing. Here we performed an empirical assessment of accuracy in genetic diversity analysis of highly incomplete single nucleotide polymorphism genotypes with imputations. Three large single-nucleotide polymorphism genotype data sets for corn, wheat, and rice were acquired, and missing data with up to 90% of missing observations were randomly generated and then imputed

SUBMITTER: Fu YB 

PROVIDER: S-EPMC4025488 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature