Ida Moltke1, Anders Albrechtsen. 1. Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA and Department of Biology, The Bioinformatics Centre, University of Copenhagen, 2200 Copenhagen N, Denmark.
Abstract
MOTIVATION: Pairwise relatedness plays an important role in a range of genetic research fields. However, currently only few estimators exist for individuals that are admixed, i.e. have ancestry from more than one population, and these estimators fail in some situations. RESULTS: We present a new software tool, RelateAdmix, for obtaining maximum likelihood estimates of pairwise relatedness from genetic data between admixed individuals. We show using simulated data that it gives rise to better estimates than three state-of-the-art software tools, REAP, KING and Plink, while still being fast enough to be applicable to large datasets. AVAILABILITY AND IMPLEMENTATION: The software tool, implemented in C and R, is freely available from www.popgen.dk/software.
MOTIVATION: Pairwise relatedness plays an important role in a range of genetic research fields. However, currently only few estimators exist for individuals that are admixed, i.e. have ancestry from more than one population, and these estimators fail in some situations. RESULTS: We present a new software tool, RelateAdmix, for obtaining maximum likelihood estimates of pairwise relatedness from genetic data between admixed individuals. We show using simulated data that it gives rise to better estimates than three state-of-the-art software tools, REAP, KING and Plink, while still being fast enough to be applicable to large datasets. AVAILABILITY AND IMPLEMENTATION: The software tool, implemented in C and R, is freely available from www.popgen.dk/software.
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