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  3. CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long noncoding RNAs.
 

CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long noncoding RNAs.

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BORIS DOI
10.7892/boris.134963
Publisher DOI
10.1093/bioinformatics/btz811
PubMed ID
31681950
Description
MOTIVATION

CRISPR-Cas9 loss-of-function pooled screening promises to identify which long noncoding RNAs (lncRNAs), amongst the many thousands to have been annotated so far, are capable of mediating cellular functions. The two principal loss-of-function perturbations, CRISPR-inhibition and CRISPR-deletion, employ one and two guide RNAs, respectively. However, no software solution has the versatility to identify hits across both modalities, and the optimal design parameters for such screens remain poorly understood.

RESULTS

Here we present CASPR (CRISPR Analysis for Single and Paired RNA-guides), a user-friendly, end-to-end screen analysis tool. CASPR is compatible with both CRISPRi and CRISPR-del screens, and balances sensitivity and specificity by generating consensus predictions from multiple algorithms. Benchmarking on ground-truth sets of cancer-associated lncRNAs demonstrates CASPR's improved sensitivity with respect to existing methods. Applying CASPR to published screens, we identify two parameters that predict lncRNA hits: expression, and annotation quality of the transcription start site. Thus CASPR is a versatile and complete solution for lncRNA CRISPR screen analysis, and reveals principles for including lncRNAs in screening libraries.

AVAILABILITY

https://judithbergada.github.io/CASPR/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.
Date of Publication
2020-03-01
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Language(s)
en
Contributor(s)
Bergada Pijuan, Judith
Department for BioMedical Research (DBMR)
Pulido Quetglas, Carlos
Department for BioMedical Research (DBMR)
Universitätsklinik für Medizinische Onkologie
Vancura, Adrienne Nina
Universitätsklinik für Medizinische Onkologie
Department for BioMedical Research (DBMR)
Johnson, Rory Baldwin
Department for BioMedical Research (DBMR)
Universitätsklinik für Medizinische Onkologie
Additional Credits
Universitätsklinik für Medizinische Onkologie
Department for BioMedical Research (DBMR)
Series
Bioinformatics
Publisher
Oxford University Press
ISSN
1367-4803
Access(Rights)
open.access
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