A likelihood method for estimating present-day human contamination in ancient DNA samples using low-depth haploid chromosome data

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Etat: Public
Version: de l'auteur
Licence: CC BY-NC-ND 4.0
ID Serval
serval:BIB_84C6FA3621CE
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
A likelihood method for estimating present-day human contamination in ancient DNA samples using low-depth haploid chromosome data
Périodique
bioRxiv
Auteur(s)
Moreno-Mayar J. Víctor (co-premier), Korneliussen Thorfinn Sand (co-premier), Albrechtsen Anders, Dalal Jyoti, Renaud Gabriel, Nielsen Rasmus, Malaspinas Anna-Sapfo
Statut éditorial
Publié
Date de publication
05/2019
Langue
anglais
Résumé
Motivation The presence of present-day human contaminating DNA fragments is one of the challenges defining ancient DNA (aDNA) research. This is especially relevant to the ancient human DNA field where it is difficult to distinguish endogenous molecules from human contaminants due to their genetic similarity. Recently, with the advent of high-throughput sequencing and new aDNA protocols, hundreds of ancient human genomes have become available. Contamination in those genomes has been measured with computational methods often developed specifically for these empirical studies. Consequently, some of these methods have not been implemented and tested while few are aimed at low-depth data, a common feature in aDNA datasets.
Results We develop a new X-chromosome-based maximum likelihood method for estimating present-day human contamination in low-depth sequencing data. We implement our method for general use, assess its performance under conditions typical of ancient human DNA research, and compare it to previous nuclear data-based methods through extensive simulations. For low-depth data, we show that existing methods can produce unusable estimates or substantially underestimate contamination. In contrast, our method provides accurate estimates for a depth of coverage as low as 0.5× on the X-chromosome when contamination is below 25%. Moreover, our method still yields meaningful estimates in very challenging situations, i.e., when the contaminant and the target come from closely related populations or with increased error rates. With a running time below five minutes, our method is applicable to large scale aDNA genomic studies.
Availability and implementation The method is implemented in C++ and R and is freely available in https://github.com/sapfo/contaminationX.
Contact morenomayar{at}gmail.com, annasapfo.malaspinas{at}unil.ch.
Mots-clé
ancient DNA, contamination, population genetics
Open Access
Oui
Financement(s)
Fonds national suisse / Carrières
Commission Européenne / H2020 / CAMERA
Création de la notice
16/06/2019 15:10
Dernière modification de la notice
21/08/2019 6:09
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