TY - JOUR
T1 - NgsRelate
T2 - a software tool for estimating pairwise relatedness from next-generation sequencing data
AU - Korneliussen, Thorfinn Sand
AU - Moltke, Ida
N1 - © The Author 2015. Published by Oxford University Press.
PY - 2015/7/3
Y1 - 2015/7/3
N2 - 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.
AB - 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.
U2 - 10.1093/bioinformatics/btv509
DO - 10.1093/bioinformatics/btv509
M3 - Journal article
C2 - 26323718
SN - 1367-4803
VL - 31
SP - 4009
EP - 4011
JO - Bioinformatics (Oxford, England)
JF - Bioinformatics (Oxford, England)
IS - 24
ER -