Quality control plays a major role in the analysis of ancient DNA (aDNA). One key step in this quality control is assessment of DNA damage: aDNA contains unique signatures of DNA damage that distinguish it from modern DNA, and so analyses of damage patterns can help confirm that DNA sequences obtained are from endogenous aDNA rather than from modern contamination. Predominant signatures of DNA damage include a high frequency of cytosine to thymine substitutions (C-to-T) at the ends of fragments, and elevated rates of purines (A & G) before the 5 strand-breaks. Existing QC procedures help assess damage by simply plotting for each sample, the C-to-T mismatch rate along the read and the composition of bases before the 5 strand-breaks. Here we present a more flexible and comprehensive model-based approach to infer and visualize damage patterns in aDNA, implemented in an R package aRchaic. This approach is based on a grade of membership model (also known as admixture or topic model) in which each sample has an estimated grade of membership in each of K damage profiles that are estimated from the data.