Motivation: Mutation accumulation (MA) is the most widely used method for directly studying the effects of mutation. Modern sequencing technologies have led to an increased interest in MA experiments. By sequencing whole genomes from MA lines, researchers can directly study the rate and molecular spectra of spontaneous mutations and use these results to understand how mu- tation contributes to biological processes. At present there is no software designed specifically for identifying mutations

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... rom MA lines. Studies that combine MA with whole genome sequencing use custom bioinformatic pipelines that implement heuristic rules to identify putative mutations. Results: Here we describe accuMUlate, a program that is designed to detect mutations from MA experiments. accuMUlate implements a probabilistic model that reflects the design of a typical MA experiments while being flexible enough to accommodate properties unique to any particular experiment. For each putative mutation identified from this model accuMUlate calculates a set of summary statistics that can be used to filter sites that may be false positives. A companion tool, denominate, can be used to apply filtering rules based on these statistics to simulated mutations and thus identify the number of callable sites per sample. Availability: Source code and releases available from https://github.com/dwinter/accuMUlate.