Evidence map›Paper›PMID 32619467›Full record

ReviewMolecular cell2020

Technologies and Computational Analysis Strategies for CRISPR Applications.

Kendell Clement, Jonathan Y Hsu, Matthew C Canver, J Keith Joung, Luca Pinello

Open access · bronzeAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Molecular cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

27 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
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  8. Review
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  10. MAFin: motif detection in multiple alignment files.Bioinformatics (Oxford, England) · 2025
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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

5 authors at 2 institutions in 1 country.

Kendell ClementMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Jonathan Y HsuMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Matthew C CanverMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Pathology and Laboratory Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
J Keith JoungMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA.
Luca PinelloMolecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: lpinello@mgh.harvard.edu.
Broad Institute · USHarvard University · US

Funding

Center for Genomic Editing and Recording: Development and Application of Next-Generation Genome and Epigenome Editing Methods to Advance the Study and Treatment of Human DiseaseRM1HG009490 · NHGRI · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · PI Brittany S. Adamson, Martin Joseph Ankrah Aryee · 2017 to 2026
$22.7M
Evolution, Optimization, and Application of Genome Editing TechnologiesR35GM118158 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI JOUNG, J. KEITH · 2016 to 2023
$4.7M
Multiscale exploration of the functional non-coding genomeR35HG010717 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI PINELLO, LUCA · 2019 to 2023
$2.6M
Discovering disease-causal variants by linking genetic and epigenetic variationR00HG008399 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI PINELLO, LUCA · 2017 to 2019
$747k
NHGRI NIH HHS R00 HG008399NHGRI NIH HHS R35 HG010717NHGRI NIH HHS RM1 HG009490NIGMS NIH HHS R35 GM118158
6 · The paper itself

Abstract

The CRISPR-Cas system offers a programmable platform for eukaryotic genome and epigenome editing. The ability to perform targeted genetic and epigenetic perturbations enables researchers to perform a variety of tasks, ranging from investigating questions in basic biology to potentially developing novel therapeutics for the treatment of disease. While CRISPR systems have been engineered to target DNA and RNA with increased precision, efficiency, and flexibility, assays to identify off-target editing are becoming more comprehensive and sensitive. Furthermore, techniques to perform high-throughput genome and epigenome editing can be paired with a variety of readouts and are uncovering important cellular functions and mechanisms. These technological advances drive and are driven by accompanying computational approaches. Here, we briefly present available CRISPR technologies and review key computational advances and considerations for various CRISPR applications. In particular, we focus on the analysis of on- and off-target editing and CRISPR pooled screen data.

Indexed as

CRISPR-Cas SystemsEpigenomicsGene EditingGenome, HumanComputational BiologyHumans

Identifiers

PMID32619467
PMCPMC7497852
OpenAlexW3038339843

What OpenQuestion holds

Textmetadata
LicenceTDM
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.