ArticleCell genomics2025
Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens using CLEANSER.
Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Characterizing and mitigating cross-library PCR chimeras in Perturb-seq using Perturb-Audit.Blood science (Baltimore, Md.) · 2026Article
- Region-Level Design and Analysis of CRISPR Perturbation Screens with FRACTEL.bioRxiv : the preprint server for biology · 2026Article
- Technical and biological sources of noise confound multiplexed enhancer AAV screening.Nature communications · 2026Article
- Reprogramming of neuronal genome function and phenotype by astrocytes.bioRxiv : the preprint server for biology · 2026Article
- AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support.Journal of translational medicine · 2026Review
- Mismatch tolerance of a gRNA for CRISPR-based gene activation confers broad activity critical for cell reprogramming.bioRxiv : the preprint server for biology · 2026Article
- Why "Where" Matters as Much as "How Much": Single-Cell and Spatial Transcriptomics in Plants.International journal of molecular sciences · 2025Review
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Abstract
Single-cell RNA sequencing CRISPR (perturb-seq) screens enable high-throughput investigation of the genome, allowing for characterization of thousands of genomic perturbations on gene expression. Ambient gRNAs, which are contaminating gRNAs, are a major source of noise in perturb-seq experiments because they result in an excess of false-positive gRNA assignments. Here, we utilize CRISPR barnyard assays to characterize ambient gRNAs in perturb-seq screens. We use these datasets to develop CRISPR Library Evaluation and Ambient Noise Suppression for Enhanced single-cell RNA-seq (CLEANSER), a mixture model that filters ambient gRNAs. CLEANSER includes both gRNA and cell-specific normalization parameters, correcting for confounding technical factors that affect individual gRNAs and cells. The output of CLEANSER is the probability that a gRNA-cell assignment is in the native distribution over the ambient distribution. We find that ambient gRNA filtering methods impact differential gene expression analysis outcomes and that CLEANSER outperforms alternate approaches by increasing gRNA-cell assignment accuracy across multiple screen formats.
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