Rosace is a Bayesian framework developed for analyzing growth-based deep mutational scanning (DMS) data. It effectively controls for the false discovering rate and increases power in DMS experiments with small sample sizes by leveraging amino acid residue information and mean-variance shrinkage. Rosace also contains a simulation framework Rosette that simulates the distributional properties of DMS, providing a reliable benchmark for evaluating DMS analysis tools.

Rosace is developed and maintained by the Pimentel lab. Details about the program can be found at:

Rosace is avaliable as a an R package. To get started, download the software and explore the vignettes page for guidance on its usage.