Guide assignment in single-cell CRISPR screens using crispat

Pooled single cell CRISPR screens have emerged as a powerful tool in functional genomics to probe the effect of genetic interventions at scale. A crucial step in the analysis of the resulting data is the assignment of cells to gRNAs corresponding to a specific genetic intervention. However, this step is challenging due to a lack of systematic benchmarks and accessible software to apply and compare different guide assignment strategies. To address this, we here propose crispat (CRISPR guide assignment tool), a Python package to facilitate the choice of a suitable guide assignment strategy for single cell CRISPR screens. We demonstrate the package on four single cell CRISPR interference screens at low multiplicity of infection from two studies, where crispat identifies strong differences in the number of assigned cells, downregulation of the target genes and number of discoveries across different guide assignment strategies, highlighting the need for a suitable guide assignment strategy to obtain optimal power in single cell CRISPR screens. Availability and Implementation crispat is implemented in python and the source code, installation instructions and tutorials can be found at . Code to reproduce all findings in this paper is available at . Contact Britta Velten, britta.velten{at}cos.uni-heidelberg.de ### Competing Interest Statement The authors have declared no competing interest.