Estimation of kinship coefficient in structured and admixed populations using sparse sequencing data.

ABSTRACT: Knowledge of biological relatedness between samples is important for many genetic studies. In large-scale human genetic association studies, the estimated kinship is used to remove cryptic relatedness, control for family structure, and estimate trait heritability. However, estimation of kinship is challenging for sparse sequencing data, such as those from off-target regions in target sequencing studies, where genotypes are largely uncertain or missing. Existing methods often assume accurate genotypes at a large number of markers across the genome. We show that these methods, without accounting for the genotype uncertainty in sparse sequencing data, can yield a strong downward bias in kinship estimation. We develop a computationally efficient method called SEEKIN to estimate kinship for bot

SUBMITTER: Dou J 

PROVIDER: S-EPMC5636172 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature