simCRISPR: Modeling Experimental Complexity in Pooled CRISPR Screens

Area of Science:

• Genomics
• Computational Biology
• Genetic Screening

Background:

• Pooled CRISPR screens are essential for gene function and interaction studies.
• Analyzing gene-by-environment (GxE) interactions is challenging due to lack of ground truth and inadequate simulation tools.

Purpose of the Study:

• To develop a flexible simulation framework, simCRISPR, for generating pooled CRISPR screen data.
• To benchmark computational methods for GxE interaction detection using simulated data.

Main Methods:

• Developed simCRISPR, a simulation framework for complex CRISPR screen designs.
• Evaluated analysis methods, comparing safe-harbor vs. non-targeting sgRNA normalization.
• Assessed empirical log2 fold-change (FC) thresholds as an effect-size criterion.

Main Results:

• Safe-harbor normalization enhanced GxE interaction detection, especially with DNA damage effects.
• Combining safe-harbor normalization with empirical log2 FC thresholding improved DESeq2 analysis.
• Applied workflow to doxorubicin GxE screen, reducing bias and identifying relevant candidates.

Conclusions:

• simCRISPR provides a robust platform for simulating CRISPR screen data for GxE interaction analysis.
• Safe-harbor normalization is a valuable strategy for improving the accuracy of GxE interaction detection in pooled CRISPR screens.
• The developed workflow enhances the identification of biologically relevant genetic interactions under environmental stress.