TY - JOUR

T1 - NGSremix

T2 - A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

AU - Nøhr, Anne Krogh

AU - Hanghøj, Kristian

AU - Garcia-Erill, Genís

AU - Li, Zilong

AU - Moltke, Ida

AU - Albrechtsen, Anders

N1 - © The Author(s) (2021). Published by Oxford University Press on the Genetics Society of America.

PY - 2021

Y1 - 2021

N2 - Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

AB - Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

U2 - 10.1093/g3journal/jkab174

DO - 10.1093/g3journal/jkab174

M3 - Journal article

C2 - 34015083

VL - 11

JO - G3: Genes, Genomes, Genetics (Bethesda)

JF - G3: Genes, Genomes, Genetics (Bethesda)

SN - 2160-1836

IS - 8

M1 - jkab174

ER -