1. Model-based understanding of single-cell CRISPR screening
- Author
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Yifei Yu, Chi Zhou, Shen Qu, Shihua Zhang, Bin Duan, Zhiyuan Zhang, Ping Wang, Xiangyun Ye, Qi Liu, Hanhui Ma, Chengyu Zhu, Chao Zhang, Gaoyang Li, and Shuyang Sun
- Subjects
0301 basic medicine ,Screening techniques ,Individual gene ,Bioinformatics ,Computer science ,Science ,Datasets as Topic ,General Physics and Astronomy ,02 engineering and technology ,Computational biology ,Article ,General Biochemistry, Genetics and Molecular Biology ,Jurkat Cells ,03 medical and health sciences ,Humans ,CRISPR ,Clustered Regularly Interspaced Short Palindromic Repeats ,lcsh:Science ,Multidisciplinary ,Models, Genetic ,Sequence Analysis, RNA ,Gene Expression Profiling ,Computational Biology ,General Chemistry ,021001 nanoscience & nanotechnology ,Computational biology and bioinformatics ,030104 developmental biology ,Gene Knockdown Techniques ,Feasibility Studies ,lcsh:Q ,Single-Cell Analysis ,K562 Cells ,0210 nano-technology ,RNA, Guide, Kinetoplastida - Abstract
The recently developed single-cell CRISPR screening techniques, independently termed Perturb-Seq, CRISP-seq, or CROP-seq, combine pooled CRISPR screening with single-cell RNA-seq to investigate functional CRISPR screening in a single-cell granularity. Here, we present MUSIC, an integrated pipeline for model-based understanding of single-cell CRISPR screening data. Comprehensive tests applied to all the publicly available data revealed that MUSIC accurately quantifies and prioritizes the individual gene perturbation effect on cell phenotypes with tolerance for the substantial noise that exists in such data analysis. MUSIC facilitates the single-cell CRISPR screening from three perspectives, i.e., prioritizing the gene perturbation effect as an overall perturbation effect, in a functional topic-specific way, and quantifying the relationships between different perturbations. In summary, MUSIC provides an effective and applicable solution to elucidate perturbation function and biologic circuits by a model-based quantitative analysis of single-cell-based CRISPR screening data., Single-cell CRISPR screening combines pooled CRISPR screening with scRNA-seq analysis to expand the resolution power of genetic screening. Here, the authors develop MUSIC, a computational pipeline for analyzing single-cell CRISPR screening data.
- Published
- 2019
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