Bope, c. D.; Kalyanasundaram, S.; Rand, K. D.; Lingjaerde, O. C.; Hovig, E.; Nakken, S.

All cell lineages accumulate mutations over time, increasing the probability that some lineages eventually become malignant. Many of the processes responsible for generating mutations are leaving a characteristic footprint in the genome that allows their presence to be detected. However, the mutational pattern in a tumor is usually the combined result of multiple mutational processes being at work simultaneously, and the problem of disentangling the different footprints and their relative impact then becomes a deconvolution problem. Several algorithms have been developed for this purpose, most of them involving a factorization of the mutation count matrix into two nonnegative matrices, representing respectively the underlying mutational signatures and the relative weighting of (or exposure to) these signatures. Here, we introduce the StarSignDNA algorithm for mutational signature analysis, which offers efficient refitting and de novo mutational signature extraction. StarSignDNA is capable of deciphering well-differentiated signatures linked to known mutagenic mechanisms and suggesting clinically relevant predictions for a single patient. The package offers a command line-based interface and data visualization routines.