Journal
BIOINFORMATICS
Volume 29, Issue 13, Pages 1682-1684Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt193
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Funding
- EUROTAST (Marie Curie FP7 Initial Training Network)
- Marie Curie Career Integration Grant [293845]
- Marie Curie Intra-European Fellowship [299176]
- Danish Council for Independent Research
- Natural Sciences (FNU)
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Motivation: Ancient DNA (aDNA) molecules in fossilized bones and teeth, coprolites, sediments, mummified specimens and museum collections represent fantastic sources of information for evolutionary biologists, revealing the agents of past epidemics and the dynamics of past populations. However, the analysis of aDNA generally faces two major issues. Firstly, sequences consist of a mixture of endogenous and various exogenous backgrounds, mostly microbial. Secondly, high nucleotide misincorporation rates can be observed as a result of severe post-mortem DNA damage. Such misincorporation patterns are instrumental to authenticate ancient sequences versus modern contaminants. We recently developed the user-friendly mapDamage package that identifies such patterns from next-generation sequencing (NGS) sequence datasets. The absence of formal statistical modeling of the DNA damage process, however, precluded rigorous quantitative comparisons across samples. Results: Here, we describe mapDamage 2.0 that extends the original features of mapDamage by incorporating a statistical model of DNA damage. Assuming that damage events depend only on sequencing position and post-mortem deamination, our Bayesian statistical framework provides estimates of four key features of aDNA molecules: the average length of overhangs (lambda), nick frequency (nu) and cytosine deamination rates in both double-stranded regions (delta(d)) and overhangs (delta(s)). Our model enables rescaling base quality scores according to their probability of being damaged. mapDamage 2.0 handles NGS datasets with ease and is compatible with a wide range of DNA library protocols.
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