CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci

Research output: Contribution to journalJournal articlepeer-review

Standard

CRISPRCasTyper : Automated Identification, Annotation, and Classification of CRISPR-Cas Loci. / Russel, Jakob; Pinilla-Redondo, Rafael; Mayo-Muñoz, David; Shah, Shiraz A.; Sørensen, Søren J.

In: CRISPR Journal, Vol. 3, No. 6, 2020, p. 462-469.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Russel, J, Pinilla-Redondo, R, Mayo-Muñoz, D, Shah, SA & Sørensen, SJ 2020, 'CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci', CRISPR Journal, vol. 3, no. 6, pp. 462-469. https://doi.org/10.1089/crispr.2020.0059

APA

Russel, J., Pinilla-Redondo, R., Mayo-Muñoz, D., Shah, S. A., & Sørensen, S. J. (2020). CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci. CRISPR Journal, 3(6), 462-469. https://doi.org/10.1089/crispr.2020.0059

Vancouver

Russel J, Pinilla-Redondo R, Mayo-Muñoz D, Shah SA, Sørensen SJ. CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci. CRISPR Journal. 2020;3(6):462-469. https://doi.org/10.1089/crispr.2020.0059

Author

Russel, Jakob ; Pinilla-Redondo, Rafael ; Mayo-Muñoz, David ; Shah, Shiraz A. ; Sørensen, Søren J. / CRISPRCasTyper : Automated Identification, Annotation, and Classification of CRISPR-Cas Loci. In: CRISPR Journal. 2020 ; Vol. 3, No. 6. pp. 462-469.

Bibtex

@article{f9fce909528246d08b3d3f70e8f0ef2a,
title = "CRISPRCasTyper: Automated Identification, Annotation, and Classification of CRISPR-Cas Loci",
abstract = "Automated classification of CRISPR-Cas systems has been challenged by their dynamic nature and expanding classification. Here, we developed CRISPRCasTyper, an automated tool with improved capabilities for identifying and typing CRISPR arrays and cas loci based on the latest nomenclature (44 subtypes/variants). As a novel feature, CRISPRCasTyper uses a machine learning approach to subtype CRISPR arrays based on the sequences of the repeats, which allows the typing of orphan and distant arrays. CRISPRCasTyper provides a graphical output, where CRISPRs and cas operons are visualized as gene maps, thus aiding annotation of partial and novel systems through synteny. CRISPRCasTyper was benchmarked against a manually curated set of 31 subtypes with a median accuracy of 98.6% and used to explore CRISPR-Cas diversity across >3,000 metagenomes. Altogether, we present an up-to-date software for improved automated prediction of CRISPR-Cas loci. CRISPRCasTyper is available through conda and as a web server (cctyper.crispr.dk).",
author = "Jakob Russel and Rafael Pinilla-Redondo and David Mayo-Mu{\~n}oz and Shah, {Shiraz A.} and S{\o}rensen, {S{\o}ren J.}",
year = "2020",
doi = "10.1089/crispr.2020.0059",
language = "English",
volume = "3",
pages = "462--469",
journal = "CRISPR Journal",
issn = "2573-1599",
publisher = "Mary AnnLiebert, Inc. Publishers",
number = "6",

}

RIS

TY - JOUR

T1 - CRISPRCasTyper

T2 - Automated Identification, Annotation, and Classification of CRISPR-Cas Loci

AU - Russel, Jakob

AU - Pinilla-Redondo, Rafael

AU - Mayo-Muñoz, David

AU - Shah, Shiraz A.

AU - Sørensen, Søren J.

PY - 2020

Y1 - 2020

N2 - Automated classification of CRISPR-Cas systems has been challenged by their dynamic nature and expanding classification. Here, we developed CRISPRCasTyper, an automated tool with improved capabilities for identifying and typing CRISPR arrays and cas loci based on the latest nomenclature (44 subtypes/variants). As a novel feature, CRISPRCasTyper uses a machine learning approach to subtype CRISPR arrays based on the sequences of the repeats, which allows the typing of orphan and distant arrays. CRISPRCasTyper provides a graphical output, where CRISPRs and cas operons are visualized as gene maps, thus aiding annotation of partial and novel systems through synteny. CRISPRCasTyper was benchmarked against a manually curated set of 31 subtypes with a median accuracy of 98.6% and used to explore CRISPR-Cas diversity across >3,000 metagenomes. Altogether, we present an up-to-date software for improved automated prediction of CRISPR-Cas loci. CRISPRCasTyper is available through conda and as a web server (cctyper.crispr.dk).

AB - Automated classification of CRISPR-Cas systems has been challenged by their dynamic nature and expanding classification. Here, we developed CRISPRCasTyper, an automated tool with improved capabilities for identifying and typing CRISPR arrays and cas loci based on the latest nomenclature (44 subtypes/variants). As a novel feature, CRISPRCasTyper uses a machine learning approach to subtype CRISPR arrays based on the sequences of the repeats, which allows the typing of orphan and distant arrays. CRISPRCasTyper provides a graphical output, where CRISPRs and cas operons are visualized as gene maps, thus aiding annotation of partial and novel systems through synteny. CRISPRCasTyper was benchmarked against a manually curated set of 31 subtypes with a median accuracy of 98.6% and used to explore CRISPR-Cas diversity across >3,000 metagenomes. Altogether, we present an up-to-date software for improved automated prediction of CRISPR-Cas loci. CRISPRCasTyper is available through conda and as a web server (cctyper.crispr.dk).

U2 - 10.1089/crispr.2020.0059

DO - 10.1089/crispr.2020.0059

M3 - Journal article

C2 - 33275853

VL - 3

SP - 462

EP - 469

JO - CRISPR Journal

JF - CRISPR Journal

SN - 2573-1599

IS - 6

ER -

ID: 252770633