Joint Estimation of Contamination,Error and Demography for Nuclear DNA from Ancient Humans

When sequencing an ancient dna sample from a hominin fossil,dna from present-day humans involved in excavation and extraction will be sequenced along with the endogenous material. this type of contamination is problematic for downstream analyses as it will introduce a bias towards the population of the contaminating individual(s). quantifying the extent of contamination is a crucial step as it allows researchers to account for possible biases that may arise in downstream genetic analyses. here,we present an mcmc algorithm to co-estimate the contamination rate,sequencing error rate and demographic parameters—including drift times and admixture rates—for an ancient nuclear genome obtained from human remains,when the putative contaminating dna comes from present-day humans. we assume we have a large panel representing the putative contaminant population (e.g. european,east asian or african). the method is implemented in a c++ program called ‘demographic inference with contamination and error’ (dice). we applied it to simulations and genome data from ancient neanderthals and modern humans. with reasonable levels of genome sequence coverage (>3x),we find we can recover accurate estimates of all these parameters,even when the contamination rate is as high as 50%. © 2016 racimo et al.