: A Computational Workflow for Designing Libraries of Guide RNAs for CRISPR-Mediated Base Editing.

CRISPR-mediated base editors have opened unique avenues for scar-free genome-wide mutagenesis. Here, we describe a comprehensive computational workflow called that can be broadly adapted for designing guide RNA libraries with a range of CRISPR-mediated base editors, Protospacer Adjacent Motif (PAM) recognition sequences, and genomes of many species. Additionally, to assist users in selecting the best sets of guide RNAs for their experiments, estimates of editing efficiency, called scores, are calculated. These scores are intended to select guide RNAs that conform to requirements for optimal base editing: the editable base falls within maximum activity window of the CRISPR-mediated base editor and produces nonconfounding mutational effects with minimal predicted off-target effects. We demonstrate the utility of the software by designing guide RNAs for base editing to model or correct thousands of clinically important human disease mutations.