Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)

PCAWG Tumor Subtypes and Clinical Translation Working Group; PCAWG Consortium

doi:10.1038/s41467-022-32329-6

Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)

PCAWG Tumor Subtypes and Clinical Translation Working Group
, PCAWG Consortium

University of Latvia

Ontario Institute for Cancer Research
University of Toronto
Vector Institute
Broad Institute
Harvard University
Icahn School of Medicine at Mount Sinai
Massachusetts General Hospital
University of Zagreb
Hartwig Medical Foundation
Utrecht University
Spanish National Cancer Research Centre (CNIO)
University of Glasgow
Glasgow Royal Infirmary
University of New South Wales
University of California at Los Angeles
Cambridge University Hospitals NHS Foundation Trust
University of Cambridge
Wellcome Trust Genome Campus
Cornell University
Dana-Farber Cancer Institute
University of Melbourne
University of North Carolina at Chapel Hill
University of Edinburgh
National Cancer Center Japan
University of Texas MD Anderson Cancer Center
Oregon Health and Science University
Sage Bionetworks
University of California at San Francisco
University of Bern
The University of Tokyo
Kiel University
Ulm University
Barcelona Institute of Science and Technology (BIST)
Pompeu Fabra University
European Molecular Biology Laboratory

Research output: Contribution to journal › Erratum

1 Citation (Scopus)

Abstract

In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.

Original language	English
Article number	7573
Journal	Nature Communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-32329-6
Publication status	Published - Dec 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

erratum

OECD Field of Science

3. Medical and Health Sciences

Access to Document

10.1038/s41467-022-32329-6

Cite this

PCAWG Tumor Subtypes and Clinical Translation Working Group, & PCAWG Consortium (2022). Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8). Nature Communications, 13(1), Article 7573. https://doi.org/10.1038/s41467-022-32329-6

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title = "Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)",

abstract = "In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.",

keywords = "erratum",

author = "\{PCAWG Tumor Subtypes and Clinical Translation Working Group\} and \{PCAWG Consortium\} and Wei Jiao and Gurnit Atwal and Paz Polak and Rosa Karlic and Edwin Cuppen and Fatima Al-Shahrour and Gurnit Atwal and Bailey, \{Peter J.\} and Biankin, \{Andrew V.\} and Boutros, \{Paul C.\} and Campbell, \{Peter J.\} and Chang, \{David K.\} and Cooke, \{Susanna L.\} and Vikram Deshpande and Faltas, \{Bishoy M.\} and Faquin, \{William C.\} and Levi Garraway and Gad Getz and Grimmond, \{Sean M.\} and Syed Haider and Hoadley, \{Katherine A.\} and Wei Jiao and Kaiser, \{Vera B.\} and Rosa Karlic and Mamoru Kato and Kirsten K{\"u}bler and Lazar, \{Alexander J.\} and Li, \{Constance H.\} and Louis, \{David N.\} and Adam Margolin and Sancha Martin and Nahal-Bose, \{Hardeep K.\} and Nielsen, \{G. Petur\} and Serena Nik-Zainal and Larsson Omberg and Christine P{\textquoteright}ng and Perry, \{Marc D.\} and Paz Polak and Esther Rheinbay and Rubin, \{Mark A.\} and Semple, \{Colin A.\} and Sgroi, \{Dennis C.\} and Tatsuhiro Shibata and Reiner Siebert and Jaclyn Smith and Stein, \{Lincoln D.\} and Stobbe, \{Miranda D.\} and Sun, \{Ren X.\} and Alvis Brāzma and Juris Vīksna",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2022.",

year = "2022",

month = dec,

doi = "10.1038/s41467-022-32329-6",

language = "English",

volume = "13",

journal = "Nature Communications",

issn = "2041-1723",

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number = "1",

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PCAWG Tumor Subtypes and Clinical Translation Working Group & PCAWG Consortium 2022, 'Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)', Nature Communications, vol. 13, no. 1, 7573. https://doi.org/10.1038/s41467-022-32329-6

Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8). / PCAWG Tumor Subtypes and Clinical Translation Working Group; PCAWG Consortium.
In: Nature Communications, Vol. 13, No. 1, 7573, 12.2022.

Research output: Contribution to journal › Erratum

TY - JOUR

T1 - Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)

AU - PCAWG Tumor Subtypes and Clinical Translation Working Group

AU - PCAWG Consortium

AU - Jiao, Wei

AU - Atwal, Gurnit

AU - Polak, Paz

AU - Karlic, Rosa

AU - Cuppen, Edwin

AU - Al-Shahrour, Fatima

AU - Atwal, Gurnit

AU - Bailey, Peter J.

AU - Biankin, Andrew V.

AU - Boutros, Paul C.

AU - Campbell, Peter J.

AU - Chang, David K.

AU - Cooke, Susanna L.

AU - Deshpande, Vikram

AU - Faltas, Bishoy M.

AU - Faquin, William C.

AU - Garraway, Levi

AU - Getz, Gad

AU - Grimmond, Sean M.

AU - Haider, Syed

AU - Hoadley, Katherine A.

AU - Jiao, Wei

AU - Kaiser, Vera B.

AU - Karlic, Rosa

AU - Kato, Mamoru

AU - Kübler, Kirsten

AU - Lazar, Alexander J.

AU - Li, Constance H.

AU - Louis, David N.

AU - Margolin, Adam

AU - Martin, Sancha

AU - Nahal-Bose, Hardeep K.

AU - Nielsen, G. Petur

AU - Nik-Zainal, Serena

AU - Omberg, Larsson

AU - P’ng, Christine

AU - Perry, Marc D.

AU - Polak, Paz

AU - Rheinbay, Esther

AU - Rubin, Mark A.

AU - Semple, Colin A.

AU - Sgroi, Dennis C.

AU - Shibata, Tatsuhiro

AU - Siebert, Reiner

AU - Smith, Jaclyn

AU - Stein, Lincoln D.

AU - Stobbe, Miranda D.

AU - Sun, Ren X.

AU - Brāzma, Alvis

AU - Vīksna, Juris

PY - 2022/12

Y1 - 2022/12

N2 - In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.

AB - In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortiumwere listed in the Supplementary Information; however, these members shouldhave been included in themainpaper.The originalArticle has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations and author names have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper.

KW - erratum

UR - https://www.nature.com/articles/s41467-022-32329-6

UR - https://www.scopus.com/pages/publications/85143564414

U2 - 10.1038/s41467-022-32329-6

DO - 10.1038/s41467-022-32329-6

M3 - Erratum

C2 - 36481665

SN - 2041-1723

VL - 13

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 7573

ER -

Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature Communications, (2020), 11, 1, (728), 10.1038/s41467-019-13825-8)

Abstract

UN SDGs

Keywords

OECD Field of Science

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