A benchmark of algorithms for the analysis of pooled CRISPR screens

Bodapati, Sunil; Daley, Timothy; Lin, Xueqiu; Zou, James; Qi, Lei

doi:10.1186/s13059-020-01972-x

Cited by 61 publications

(63 citation statements)

References 58 publications

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“…We also simulated data using a tool recently developed by Bodapati et al [27]. Using the data from these simulations RELICS again outperformed all other methods in AP, precision, recall and BP accuracy (see methods, S4 Fig).…”

Section: Plos Computational Biologymentioning

confidence: 85%

Discovering functional sequences with RELICS, an analysis method for CRISPR screens

Fiaux

Chen

et al. 2020

PLoS Comput Biol

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CRISPR screens are a powerful technology for the identification of genome sequences that affect cellular phenotypes such as gene expression, survival, and proliferation. By targeting non-coding sequences for perturbation, CRISPR screens have the potential to systematically discover novel functional sequences, however, a lack of purpose-built analysis tools limits the effectiveness of this approach. Here we describe RELICS, a Bayesian hierarchical model for the discovery of functional sequences from CRISPR screens. RELICS specifically addresses many of the challenges of non-coding CRISPR screens such as the unknown locations of functional sequences, overdispersion in the observed single guide RNA counts, and the need to combine information across multiple pools in an experiment. RELICS outperforms existing methods with higher precision, higher recall, and finer-resolution predictions on simulated datasets. We apply RELICS to published CRISPR interference and CRISPR activation screens to predict and experimentally validate novel regulatory sequences that are missed by other analysis methods. In summary, RELICS is a powerful new analysis method for CRISPR screens that enables the discovery of functional sequences with unprecedented resolution and accuracy.

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Section: Plos Computational Biologymentioning

confidence: 85%

Discovering functional sequences with RELICS, an analysis method for CRISPR screens

Fiaux

Chen

et al. 2020

PLoS Comput Biol

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“…The P -values are determined by the RSA algorithm for the genes that are most enriched in the PARP14-knockout condition compared to the wildtype condition. Separately from the RSA analyses, we also analyzed the screen results using MAGeCK, which takes into consideration raw gRNA read counts to test if individual guides vary significantly between the conditions ( 36 , 37 ). The MAGeCK software and instructions on running it were obtained from https://sourceforge.net/p/mageck/wiki/libraries/ .…”

Section: Methodsmentioning

confidence: 99%

Genome-wide CRISPR synthetic lethality screen identifies a role for the ADP-ribosyltransferase PARP14 in DNA replication dynamics controlled by ATR

Dhoonmoon

Schleicher

Clements

et al. 2020

Nucleic Acids Research

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The DNA damage response is essential to maintain genomic stability, suppress replication stress, and protect against carcinogenesis. The ATR-CHK1 pathway is an essential component of this response, which regulates cell cycle progression in the face of replication stress. PARP14 is an ADP-ribosyltransferase with multiple roles in transcription, signaling, and DNA repair. To understand the biological functions of PARP14, we catalogued the genetic components that impact cellular viability upon loss of PARP14 by performing an unbiased, comprehensive, genome-wide CRISPR knockout genetic screen in PARP14-deficient cells. We uncovered the ATR-CHK1 pathway as essential for viability of PARP14-deficient cells, and identified regulation of DNA replication dynamics as an important mechanistic contributor to the synthetic lethality observed. Our work shows that PARP14 is an important modulator of the response to ATR-CHK1 pathway inhibitors.

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“…They try to address those issues that still influence them, such as the variability in guide RNA efficiency, variation in gene effect size and false-positive rate due to cell death from excessive cutting in high copy number regions [6,[54][55][56][57][58]. These algorithms include BAGEL [59], CERES [6], CRISPhieRmix [56], CRISPRcleanR [57], HiTSelect [60], JACKS [61], MAGeCK MLE [54], MAGeCK RRA [62] and RSA [63], that showed good performance according to the different experimental settings used [64].…”

Section: Dropout Screening Approaches To Dissect Gene Vulnerabilitiesmentioning

confidence: 99%

Global View of Candidate Therapeutic Target Genes in Hormone-Responsive Breast Cancer

Salvati

Gigantino

Nassa

et al. 2020

IJMS

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Breast cancer (BC) is a heterogeneous disease characterized by different biopathological features, differential response to therapy and substantial variability in long-term-survival. BC heterogeneity recapitulates genetic and epigenetic alterations affecting transformed cell behavior. The estrogen receptor alpha positive (ERα+) is the most common BC subtype, generally associated with a better prognosis and improved long-term survival, when compared to ERα-tumors. This is mainly due to the efficacy of endocrine therapy, that interfering with estrogen biosynthesis and actions blocks ER-mediated cell proliferation and tumor spread. Acquired resistance to endocrine therapy, however, represents a great challenge in the clinical management of ERα+ BC, causing tumor growth and recurrence irrespective of estrogen blockade. Improving overall survival in such cases requires new and effective anticancer drugs, allowing adjuvant treatments able to overcome resistance to first-line endocrine therapy. To date, several studies focus on the application of loss-of-function genome-wide screenings to identify key (hub) “fitness” genes essential for BC progression and representing candidate drug targets to overcome lack of response, or acquired resistance, to current therapies. Here, we review the biological significance of essential genes and relative functional pathways affected in ERα+ BC, most of which are strictly interconnected with each other and represent potential effective targets for novel molecular therapies.

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A benchmark of algorithms for the analysis of pooled CRISPR screens

Cited by 61 publications

References 58 publications

Discovering functional sequences with RELICS, an analysis method for CRISPR screens

Discovering functional sequences with RELICS, an analysis method for CRISPR screens

Genome-wide CRISPR synthetic lethality screen identifies a role for the ADP-ribosyltransferase PARP14 in DNA replication dynamics controlled by ATR

Global View of Candidate Therapeutic Target Genes in Hormone-Responsive Breast Cancer

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