Bergada Pijuan, Judith; Pulido Quetglas, Carlos; Vancura, Adrienne; Johnson, Rory (2020). CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long noncoding RNAs. Bioinformatics, 36(6), pp. 1673-1680. Oxford University Press 10.1093/bioinformatics/btz811
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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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Medical Oncology 04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) |
Graduate School: |
Graduate School for Cellular and Biomedical Sciences (GCB) |
UniBE Contributor: |
Bergada Pijuan, Judith, Pulido Quetglas, Carlos, Vancura, Adrienne Nina, Johnson, Rory Baldwin |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1367-4803 |
Publisher: |
Oxford University Press |
Language: |
English |
Submitter: |
Rebeka Gerber |
Date Deposited: |
27 Nov 2019 17:24 |
Last Modified: |
02 Mar 2023 23:32 |
Publisher DOI: |
10.1093/bioinformatics/btz811 |
PubMed ID: |
31681950 |
BORIS DOI: |
10.7892/boris.134963 |
URI: |
https://boris.unibe.ch/id/eprint/134963 |
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