Abstract
The rapid adoption of CRISPR technology has enabled biomedical researchers to conduct CRISPR-based genetic screens in a pooled format. The quality of results from such screens is heavily dependent on optimal screen design, which also affects cost and scalability. We present CRISPulator, a computational tool that simulates the impact of screen parameters on the robustness of screen results, thereby enabling users to build intuition and insights that will inform their experimental strategy. We illustrate its power by deriving non-obvious rules for optimal screen design.
List of abbreviations
- AUPRC
- area under the precision-recall curve
- CRISPRi
- CRISPR interference
- CRISPRn
- CRISPR nuclease
- FACS
- fluorescence-activated cell sorting
- sgRNA
- single guide RNA
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.