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Published on: June 25, 2017
Characterizing and mitigating cross-library PCR chimeras in Perturb-seq using Perturb-Audit
Xin Song1,2, Jiayi Lu1,2, Ping Zhu1,2
1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China.
Blood Science (Baltimore, Md.)
|August 11, 2026
Summary
Perturb-Audit improves CRISPR screens by accurately assigning single-guide RNAs (sgRNAs) to cells. This enhances the analysis of immune cell responses and gene functions in single-cell sequencing data.
Area of Science:
- Single-cell genomics
- CRISPR screening
- Immunology
Background:
- Perturb-seq links CRISPR perturbations to single-cell phenotypes, but accuracy relies on correct single-guide RNA (sgRNA) assignment.
- Standard processing methods can introduce errors due to ambient RNA, overloaded droplets, and PCR chimeras, failing to resolve molecular collisions.
Purpose of the Study:
- To develop a diagnostic and denoising framework, Perturb-Audit, to improve sgRNA assignment fidelity in Perturb-seq data.
- To evaluate the impact of improved assignment on biological interpretability and signal recovery in immune cell studies.
Main Methods:
- Developed Perturb-Audit, integrating molecule-level collision auditing and statistical background suppression.
- Applied targeted collision removal and global denoising (CellBender) to Perturb-seq datasets.
- Validated findings by recapitulating known phenotypes and identifying novel gene functions.
Main Results:
- Perturb-Audit effectively removes molecular collisions, enhancing sgRNA assignment specificity.
- Global denoising with CellBender improved overall assignment quality and phenotypic separation.
- Improved assignment fidelity increased detectable perturbation effect sizes and recovered biologically relevant immune cell signals.
Conclusions:
- An audit-first strategy using Perturb-Audit enhances the accuracy and biological interpretability of single-cell CRISPR screens.
- The framework successfully identified gene-specific effects on T-cell exhaustion and differentiation.
- This approach is crucial for robust analysis of complex single-cell perturbation data.
