iCRISEE: an integrative analysis of CRISPR screen by reducing false positive hits

Abstract

Clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR/Cas9) technology has become a popular tool for the study of genome function, and the use of this technology can achieve large-scale screening studies of specific phenotypes. Several analysis tools for CRISPR/Cas9 screening data have been developed, while high false positive rate remains a great challenge. To this end, we developed iCRISEE, an integrative analysis of CRISPR ScrEEn by reducing false positive hits. iCRISEE can dramatically reduce false positive hits and it is robust to different single guide RNA (sgRNA) library by introducing precise data filter and normalization, model selection and valid sgRNA number correction in data preprocessing, sgRNA ranking and gene ranking. Furthermore, a powerful web server has been presented to automatically complete the whole CRISPR/Cas9 screening analysis, where we integrated the main hypothesis in multiple algorithms as a full workflow, including quality control, sgRNA extracting, sgRNA alignment, sgRNA ranking, gene ranking and pathway enrichment. In addition, output of iCRISEE, including result mapping, sample clustering, sgRNA ranking and gene ranking, can be easily visualized and downloaded for publication. Taking together, iCRISEE presents to be the state-of-the-art and user-friendly tool for CRISPR screening data analysis. iCRISEE is available at https://www.icrisee.com.

Keywords: CRISPR-Cas9; gene editing; screening analysis; sgRNA.