An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens

Area of Science:

• Genomics
• Bioinformatics
• CRISPR Technology

Background:

• Pooled CRISPR-Cas9 screens are powerful for identifying essential genes but suffer from high false-positive rates.
• Copy-number-amplified genomic regions often lead to inaccurate essentiality calls in CRISPR screens.
• Existing computational tools require significant bioinformatics expertise.

Purpose of the Study:

• To introduce CRISPRcleanR, a user-friendly web application for analyzing pooled CRISPR-Cas9 screening data.
• To provide an accessible platform for detecting and correcting biases in CRISPR screens, particularly those caused by genomic amplifications.
• To improve the accuracy and sensitivity of essential gene identification in CRISPR screens.

Main Methods:

• Development of a web application interface for the existing CRISPRcleanR computational method.
• Implementation of an unsupervised algorithm to detect and correct biased CRISPR-Cas9 responses.
• Integration of support for diverse CRISPR guide RNA libraries and automated data processing.

Main Results:

• CRISPRcleanR web application offers an intuitive interface, eliminating the need for R/python programming.
• The platform provides a complete analytical pipeline with no pre-processing required.
• Users receive gene-level essentiality summaries with statistical scores and interactive plots.
• Enhanced support for a wider range of CRISPR guide RNA libraries compared to the original package.

Conclusions:

• CRISPRcleanR web application democratizes the use of advanced CRISPR screen analysis.
• The tool effectively reduces false positives, improving the reliability of essential gene identification.
• This accessible platform facilitates more accurate and comprehensive genetic dependency studies.