Evidence map›Paper›PMID 37741886›Full record

ArticleCommunications biology2023

GiRAFR improves gRNA detection and annotation in single-cell CRISPR screens.

Qian Yu, Paulien Van Minsel, Eva Galle, Bernard Thienpont

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Qian YuLaboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium.
Paulien Van MinselLaboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium.
Eva GalleLaboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium.ORCID http://orcid.org/0000-0001-9276-2552
Bernard ThienpontLaboratory for Functional Epigenetics, Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium. bernard.thienpont@kuleuven.be.ORCID http://orcid.org/0000-0002-8772-6845
KU Leuven · BECenter for Human Genetics · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel methods that combine single cell RNA-seq with CRISPR screens enable high-throughput characterization of transcriptional changes caused by genetic perturbations. Dedicated software is however lacking to annotate CRISPR guide RNA (gRNA) libraries and associate them with single cell transcriptomes. Here, we describe a CRISPR droplet sequencing (CROP-seq) dataset. During analysis, we observed that the most commonly used method fails to detect mutant gRNAs. We therefore developed a python tool to identify and characterize intact and mutant gRNAs, called GiRAFR. We show that mutant gRNAs are dysfunctional, and failure to detect and annotate them leads to an inflated estimate of the number of untransformed cells, attenuated downregulation of target genes, as well as an underestimated multiplet frequency. These findings are mirrored in publicly available datasets, where we find that up to 35% of cells are transduced with a mutant gRNA. Applying GiRAFR hence stands to improve the annotation and quality of single cell CRISPR screens.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsRNA, Guide, CRISPR-Cas SystemsDown-RegulationHumansResearch PersonnelSoftwareRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID37741886
PMCPMC10518011
OpenAlexW4386982925

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.