JACKS: joint analysis of CRISPR/Cas9 knockout screens

Area of Science:

• Mammalian functional genomics
• CRISPR/Cas9 technology
• Statistical genetics

Background:

• Genome-wide CRISPR/Cas9 knockout screens are powerful tools for mammalian functional genomics.
• Variability in guide RNA efficacy confounds gene effect estimation and necessitates large experimental scales.

Purpose of the Study:

• To develop a robust statistical method for analyzing multiple CRISPR/Cas9 screens simultaneously.
• To improve the accuracy of gene effect estimation and reduce the required scale of experiments.

Main Methods:

• Developed JACKS, a Bayesian method for joint analysis of CRISPR/Cas9 screens.
• Modeled variable guide RNA efficacies within the Bayesian framework.
• Compared JACKS performance against single-screen analysis and existing methods.

Main Results:

• JACKS significantly improves hit identification compared to single-screen analyses.
• The method outperforms existing approaches for analyzing CRISPR/Cas9 screen data.
• JACKS enables a 2.5-fold reduction in cell numbers without compromising performance.

Conclusions:

• JACKS offers a more efficient and accurate method for analyzing genome-wide CRISPR/Cas9 screens.
• The approach enhances the discovery of gene functions in mammalian systems.
• This facilitates the design of more resource-efficient functional genomics experiments.