Emil Jørsboe1, Kristian Hanghøj2,3, Anders Albrechtsen1. 1. Department of Biology, The Bioinformatics Centre, University of Copenhagen, 2200 Copenhagen N, Denmark. 2. Center for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark. 3. Université de Toulouse, University Paul Sabatier (UPS), Laboratoire AMIS, CNRS UMR 5288, Toulouse, France.
Abstract
MOTIVATION: Estimation of admixture proportions and principal component analysis (PCA) are fundamental tools in populations genetics. However, applying these methods to low- or mid-depth sequencing data without taking genotype uncertainty into account can introduce biases. RESULTS: Here we present fastNGSadmix, a tool to fast and reliably estimate admixture proportions and perform PCA from next generation sequencing data of a single individual. The analyses are based on genotype likelihoods of the input sample and a set of predefined reference populations. The method has high accuracy, even at low sequencing depth and corrects for the biases introduced by small reference populations. AVAILABILITY AND IMPLEMENTATION: The admixture estimation method is implemented in C ++ and the PCA method is implemented in R. The code is freely available at http://www.popgen.dk/software/index.php/FastNGSadmix. CONTACT: emil.jorsboe@bio.ku.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Estimation of admixture proportions and principal component analysis (PCA) are fundamental tools in populations genetics. However, applying these methods to low- or mid-depth sequencing data without taking genotype uncertainty into account can introduce biases. RESULTS: Here we present fastNGSadmix, a tool to fast and reliably estimate admixture proportions and perform PCA from next generation sequencing data of a single individual. The analyses are based on genotype likelihoods of the input sample and a set of predefined reference populations. The method has high accuracy, even at low sequencing depth and corrects for the biases introduced by small reference populations. AVAILABILITY AND IMPLEMENTATION: The admixture estimation method is implemented in C ++ and the PCA method is implemented in R. The code is freely available at http://www.popgen.dk/software/index.php/FastNGSadmix. CONTACT: emil.jorsboe@bio.ku.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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