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

Author:

Zhang Tengbo1,Li Yaxu2,Yang Yanrong2,Weng Linjun3,Wu Zhiqiang1,Zhu Jiali2,Qin Jieling3ORCID,Liu Qi4,Wang Ping3

Affiliation:

1. Tongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China

2. School of Medicine, Tongji University, Shanghai 200092, China

3. Tongji University Cancer Center, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200092, China

4. School of Life Sciences and Technology, Tongji University, Shanghai 200092, China

Abstract

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.

Funder

National Natural Science Foundation of China

Shanghai International Science and Technology Cooperation Fund

Shanghai Sailing Program

Fundamental Research Funds for the Central Universities

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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