Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,631

The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.

SHERLOCK: nucleic acid detection with CRISPR nucleases

Open access
Kellner, Max J., Koob, Jeremy G., Gootenberg, Jonathan S., Abudayyeh, Omar O., Zhang, Feng·2019·Nature Protocols

Abstract

Rapid detection of nucleic acids is integral to applications in clinical diagnostics and biotechnology. We have recently established a CRISPR-based diagnostic platform that combines nucleic acid pre-amplification with CRISPR–Cas enzymology for specific recognition of desired DNA or RNA sequences. This platform, termed specific high-sensitivity enzymatic reporter unlocking (SHERLOCK), allows multiplexed, portable, and ultra-sensitive detection of RNA or DNA from clinically relevant samples. Here, we provide step-by-step instructions for setting up SHERLOCK assays with recombinase-mediated polymerase pre-amplification of DNA or RNA and subsequent Cas13- or Cas12-mediated detection via fluorescence and colorimetric readouts that provide results in <1 h with a setup time of less than 15 min. We also include guidelines for designing efficient CRISPR RNA (crRNA) and isothermal amplification primers, as well as discuss important considerations for multiplex and quantitative SHERLOCK detection assays. Specific high-sensitivity enzymatic reporter unlocking (SHERLOCK) allows multiplexed, portable, and ultra-sensitive detection of RNA or DNA from clinically relevant samples.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41596-019-0210-2

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 33 references

Cited by

See all 1,631

Metadata

Authors
Kellner, M. J., Koob, J. G., Gootenberg, J. S., Abudayyeh, O. O., & Zhang, F.
Venue
Nature Protocols
Published
2019-09-23
Volume
14
Issue
10
Pages
2986-3012
ISSN
  • 1750-2799 (ISSN-L)
  • 1754-2189
OpenAlex
W2973445868
Cited by
1,631
References
33
FWCI
40.96
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: SHERLOCK: nucleic acid detection with CRISPR nucleases. https://app.cochat.ai/papers/10.1038/s41596-019-0210-2
The paper
Kellner, M. J., Koob, J. G., Gootenberg, J. S., Abudayyeh, O. O., & Zhang, F. (2019). SHERLOCK: nucleic acid detection with CRISPR nucleases. Nature Protocols. https://doi.org/10.1038/s41596-019-0210-2

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.