Cas-analyzer: an online tool for assessing genome editing results using NGS data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Genome editing technologies, including CRISPR-Cas9, are increasingly vital in research and medicine.
• Next-generation sequencing (NGS) is the standard for quantifying mutations induced by genome editing tools.

Purpose of the Study:

• To introduce Cas-Analyzer, a novel, client-side JavaScript tool for analyzing NGS data from genome editing experiments.
• To provide a user-friendly and efficient solution for assessing mutation frequencies induced by programmable nucleases.

Main Methods:

• Development of Cas-Analyzer as a JavaScript-based, client-side web application.
• Implementation of on-the-fly analysis within the user's web browser, avoiding server-side data uploads.
• Support for analyzing data from various programmable nucleases, including single and paired nucleases.

Main Results:

• Cas-Analyzer enables rapid, on-the-fly analysis of NGS data for genome editing.
• The client-side approach circumvents the need for uploading large datasets, saving time and resources.
• The tool is versatile, accommodating different types of programmable nucleases.

Conclusions:

• Cas-Analyzer offers an efficient and accessible method for analyzing genome editing outcomes via NGS.
• The tool simplifies the process of mutation frequency assessment, accelerating research in genome editing.
• Its web-based, client-side nature makes it a valuable resource for researchers worldwide.