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ABSTRACT: Motivation
Pairwise relatedness estimation is important in many contexts such as disease mapping and population genetics. However, all existing estimation methods are based on called genotypes, which is not ideal for next-generation sequencing (NGS) data of low depth from which genotypes cannot be called with high certainty.Results
We present a software tool, NgsRelate, for estimating pairwise relatedness from NGS data. It provides maximum likelihood estimates that are based on genotype likelihoods instead of genotypes and thereby takes the inherent uncertainty of the genotypes into account. Using both simulated and real data, we show that NgsRelate provides markedly better estimates for low-depth NGS data than two state-of-the-art genotype-based methods.Availability
NgsRelate is implemented in C++ and is available under the GNU license at www.popgen.dk/software.
SUBMITTER: Korneliussen TS
PROVIDER: S-EPMC4673978 | biostudies-literature | 2015 Dec
REPOSITORIES: biostudies-literature
Korneliussen Thorfinn Sand TS Moltke Ida I
Bioinformatics (Oxford, England) 20150830 24
<h4>Motivation</h4>Pairwise relatedness estimation is important in many contexts such as disease mapping and population genetics. However, all existing estimation methods are based on called genotypes, which is not ideal for next-generation sequencing (NGS) data of low depth from which genotypes cannot be called with high certainty.<h4>Results</h4>We present a software tool, NgsRelate, for estimating pairwise relatedness from NGS data. It provides maximum likelihood estimates that are based on g ...[more]