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

Ontario Institute for Cancer Research
University of Toronto
Vector Institute
Broad Institute
Harvard University
Massachusetts General Hospital
Icahn School of Medicine at Mount Sinai
University of Zagreb
Hartwig Medical Foundation
Utrecht University
Spanish National Cancer Research Centre (CNIO)
University of Glasgow
University of New South Wales
NHS Greater Glasgow and Clyde
University of California at Los Angeles
Wellcome Trust Genome Campus
University of Cambridge
Cambridge University Hospitals NHS Foundation Trust
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
Washington University St. Louis
BGI-Shenzhen
The First Affiliated Hospital of Xi’an Jiaotong University
MRC-University of Glasgow Centre for Virus Research
Cancer Research UK Cambridge Institute
Radboud University Nijmegen
Erasmus University Rotterdam
Netherlands Cancer Institute
University of Helsinki
Memorial Sloan-Kettering Cancer Center
The University of Chicago
Keimyung University
Gachon University
Hiroshima University
King Faisal Specialist Hospital and Research Centre
University of Hamburg
Heinrich Pette Institute - Leibniz Institute for Experimental Virology
National Institutes of Health
University of California at San Diego
Provincial Health Services Authority
University of Santiago de Compostela
University of Vigo
Royal National Orthopaedic Hospital NHS Trust
Baylor College of Medicine
Jackson Laboratory
University of Queensland
Northern Care Alliance NHS Group
University and Hospital Trust of Verona
University College London
German Aerospace Center
Tokyo Women's Medical University
Computational Earth Science, Earth and Environmental Sciences Division, Los Alamos National Laboratory
Toronto General Hospital
Nottingham University Hospitals NHS Trust
German Cancer Research Center
University of Oslo
University of Barcelona
University of Leeds
Princess Alexandra Hospital
Case Western Reserve University
Gloucestershire Hospitals NHS Foundation Trust
European Molecular Biology Laboratory
Barcelona Supercomputing Center (BSC)
University of Calgary
Johns Hopkins University
University Hospital Southampton NHS Foundation Trust
University Hospitals of North Midlands NHS Trust
Human Longevity, Inc.
Olivia Newton-John Cancer Research Institute
CAS - Computer Network Information Center
Genome Canada
Buck Institute for Age Research
Duke University
Hannover Medical School
Cedars-Sinai Medical Center
Hebrew University of Jerusalem
Queen Mary University of London
Leipzig University
University of Southern California
Aarhus University
Instituto Carlos Slim de la Salud
Berlin Institute of Health and Charitè - Universitätsmedizin Berlin
National Institute of Biomedical Genomics
The Institute of Cancer Research
Duke-NUS Medical School
Lund University
Heinrich Heine University Düsseldorf
RIKEN
Friedrich-Ebert-Hospital
Yale University
University of Oxford
McGill University
Tampere University
Leeds Teaching Hospitals NHS Trust
Centre Léon Bérard
Fox Chase Cancer Center
International Agency for Research on Cancer
The Earlham Institute
University of East Anglia
University of Manchester
Princess Margaret Cancer Centre
University of California at Santa Cruz
Technical University of Denmark
University of Copenhagen
Heidelberg University
Federal Ministry of Education and Research
The University of Sydney
University of Münster
Foundation Medicine, Inc.
Stanford University
Royal Marsden NHS Foundation Trust
Institut Gustave Roussy
Spanish Ministry of Science and Innovation
University of Michigan, Ann Arbor
University of Pavia
University of Alabama at Birmingham
University of Tasmania
University of Ottawa
Mayo Clinic Rochester, MN
South Eastern Sydney and Illawarra Area Health Service
INRAE
Westmead Hospital
PDXen Biosystems Co. Ltd.
Korea Advanced Institute of Science and Technology
Electronics and Telecommunications Research Institute
Institut National du Cancer
National Cancer Centre
University Hospital Schleswig-Holstein
University Health Network
The University of Auckland
Department of Surgery
Royal Children's Hospital Melbourne
Walter and Eliza Hall Institute of Medical Research
Vancouver Prostate Centre
Norfolk and Norwich University Hospitals NHS Foundation Trust
Victorian Institute of Forensic Medicine
University of Cologne
International Genomics Consortium
Barking, Havering and Redbridge University Hospitals NHS Trust
Swiss Federal Institute of Technology Zurich
Swiss Institute of Bioinformatics
Seven Bridges Genomics Inc
Annai Systems
University of Padua
University of Lausanne
University of Geneva
The Francis Crick Institute
KU Leuven
University of Tübingen
Agency for Science, Technology and Research, Singapore
National University of Singapore
Université libre de Bruxelles
Institute for Research in Biomedicine
University of Pittsburgh
Independent Consultant
Uppsala University
Hefei University of Technology
University of Antwerp
Simon Fraser University
University of Pennsylvania
The University of Vic - Central University of Catalonia
Wellcome Trust
Queensland Institute of Medical Research
Prostate Cancer Canada
CIBER Epidemiología y Salud Pública (CIBERESP)
Econometrics and Health (GRECS)
Quantitative Genomics Laboratories (qGenomics)
Icelandic Cancer Society
Xijing Hospital
University of Montreal
James Cook University Queensland
IRCCS Fondazione Istituto Neurologico Carlo Besta - Milano
Bioplatforms Australia
University of Porto
HCA Laboratories
University of Liverpool
Bar-Ilan University
University of Florida
University of Milan - Bicocca
University of Würzburg
University of Miami
Hospital del Mar
St. Thomas’s Hospital
Osaka International Cancer Institute
Beatson Oncology Centre
Partner Site Hamburg-Borstel-Lübeck-Riems
Department of Biotechnology
Brandeis University
University of British Columbia
University of Texas Health Science Center at Houston
Imperial College Healthcare NHS Trust
Goethe University Frankfurt
Oxford Nanopore Technologies
Wakayama Medical University
University of Tennessee Health Science Center
Peking University
Children's Hospital of Philadelphia
Karolinska Institutet
Hallym University
Hokkaido University
Leibniz Institute on Aging - Fritz Lipmann Institute
University of Nebraska Medical Center
Syntekabio, Inc.
Academic Medical Center
China National GeneBank
Hong Kong University of Science and Technology
Geneplus Beijing Institute
Xi'an Jiaotong University
AbbVie
Charité – Universitätsmedizin Berlin
Edinburgh Royal Infirmary
Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM)
New York Genome Center
Department of Veterans Affairs
Hanyang University
University of Ulsan
Science Writer
University of Ljubljana
NorthShore University HealthSystem
Hopp Children’s Cancer Center (KiTZ)
Cancer Research UK
Indivumed GmbH
University of Zurich
SA Pathology
Russian Academy of Sciences
Dmitry Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology
Skolkovo Institute of Science and Technology
George Washington University
Macquarie University
Massachusetts Institute of Technology
Royal Prince Alfred Hospital
Khon Kaen University
Controlled Department and Institution
National Cancer Center Korea
Ewha Womans University
National Cancer Centre Korea
Sungkyunkwan University
Samsung
Brigham and Women’s Hospital
University of Bergen
Seoul National University
Institute of Computer Science of the Polish Academy of Sciences
University of Göttingen
University of Duisburg-Essen
Guy's and St Thomas' NHS Foundation Trust
Van Andel Institute
University of Gothenburg
Children's Medical Research Institute
ILSbio, LLC
Academia Sinica - Institute of Biomedical Sciences
Max Planck Institute for Molecular Genetics
Biobyte Solutions
New York University
Leidos Inc
Naval Medical University
Chinese Cancer Genome Consortium
Beijing Hospital
University of St Andrews
Institute for Systems Biology
University of Oviedo
Centre Georges-François Leclerc
Children's Hospital Los Angeles
Australian National University
PraxisClinic am Johannisplatz
Ghent University
Nationwide Children’s Hospital
ICREA
Autonomous University of Barcelona
August Pi i Sunyer Biomedical Research Institute
Imperial College London
Oxford Nanopore Technologies
University of California at Davis
Western Sydney University
Henry Ford Health System
Kyushu University
Heidelberg Academy of Sciences and Humanities
Department of Clinical Pathology
Roswell Park Cancer Institute
Penrose St. Francis Health Services
German Cancer Aid
Chinese University of Hong Kong
Air Force Medical University
St. Jude Children Research Hospital
Carleton College
HudsonAlpha Institute for Biotechnology
Keio University
Robert Bosch Foundation
Samsung Medical Center, Sungkyunkwan university
Sangmyung University
Cleveland Clinic Foundation
Christiana Care Health System
General Dynamics
King’s College London School of Medicine
Hôpital Jean Minjoz
Fundeni Clinical Institute
Cureline, Inc
Royal Surrey County Hospital NHS Foundation Trust
NHS Tayside
Medical College of Wisconsin
Emory University
Princeton University
Vanderbilt University
Ohio State University
Yokohama City University
Washington State University Pullman
Justus Liebig University Giessen
Centre régional de lutte du cancer Val d'Aurelle
North Bristol NHS Trust
Singapore Health Services
New York Presbyterian Hospital
Vall d'Hebron Institute of Oncology
Tata Institute of Fundamental Research
Indiana University Bloomington
GZA-ZNA Hospitals
Analytical Biological Services Inc
Tata Memorial Hospital
University of Newcastle
Beth Israel Deaconess Medical Center
Japan Agency for Medical Research and Development
Korea University
Walter Reed National Military Medical Center
University Hospitals Coventry and Warwickshire NHS Trust
St.-Antonius-Hospital Eschweiler
University of Iceland
Institut Curie
Singapore General Hospital
Columbia University
Centre Léon Bérard
IRCCS Istituto tumori Giovanni Paolo II - Bari
Italy
University of Verona
CEA - Institute de Génomique
Maastricht University
Universite Claude Bernard Lyon 1
Japan Science and Technology Agency
Institute of Science Tokyo
University Hospitals Birmingham NHS Foundation Trust
Queen's University Belfast
University of Southampton
Tallinn University of Technology
Norwegian University of Science and Technology
Argmix Consulting
Interuniversitair Micro-Elektronica Centrum
University of Latvia
Augusta University
Manchester University NHS Foundation Trust
Leibniz Institute for Baltic Sea Research
International Institute for Molecular Oncology
University of Medical Sciences Poznan
Huazhong University of Science and Technology
The University of Osaka
Shanghai Jiao Tong University
Monash University
Epworth HealthCare
Northwestern University

Research output: Contribution to journal › Comment/debate

1 Scopus citations

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
State	Published - Dec 2022

UN SDGs

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

SDG 3 Good Health and Well-being

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

@article{e6c946816cbe45189555001fa834969b,

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.",

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 Jiayin Wang and Huanming Yang and Kai Ye",

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

year = "2022",

month = dec,

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

language = "英语",

volume = "13",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

number = "1",

}

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 › Comment/debate

TY - JOUR

T1 - Author Correction

T2 - 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 - Wang, Jiayin

AU - Yang, Huanming

AU - Ye, Kai

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.

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

U2 - 10.1038/s41467-022-32329-6

DO - 10.1038/s41467-022-32329-6

M3 - 评论/辩论

C2 - 36481665

AN - SCOPUS:85143564414

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

Access to Document

Other files and links

Fingerprint

Cite this