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

Author:

Bergadà-Pijuan Judith12,Pulido-Quetglas Carlos123,Vancura Adrienne12,Johnson Rory12

Affiliation:

1. Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland

2. Department for BioMedical Research, University of Bern, Bern, Switzerland

3. Graduate School of Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland

Abstract

Abstract 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.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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