Inferring heterozygosity from ancient and low coverage genomes

While genetic diversity can be quantified accurately from high coverage sequencing, it is often desirable to obtain such estimates from low coverage data, either to save costs or because of low DNA quality as observed for ancient samples. Here we introduce a method to accurately infer heterozygosity probabilistically from very low coverage sequences of a single individual. The method relaxes the infinite sites assumption of previous methods, does not require a reference sequence and takes into account both variable sequencing errors and potential post-mortem damage. It is thus also applicable to non-model organisms and ancient genomes. Since error rates as reported by sequencing machines are generally distorted and require recalibration, we also introduce a method to infer accurately recalibration parameter in the presence of post-mortem damage. This method does also not require knowledge about the underlying genome sequence, but instead works from haploid data (e.g. from the X-chromosome from mammalian males) and integrates over the unknown genotypes. Using extensive simulations we show that a few Mb of haploid data is sufficient for accurate recalibration even at average coverages as low as 1-3x. At similar coverages, out met...Continue Reading