Erratum: Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature communications (2020) 11 1 (728)): A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

PCAWG Tumor Subtypes and Clinical Translation Working Group; PCAWG Consortium

doi:10.1038/s41467-022-32329-6

Erratum: Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature communications (2020) 11 1 (728)): A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

PCAWG Tumor Subtypes and Clinical Translation Working Group
, PCAWG Consortium

Onderzoeksoutput: Bijdrage aan tijdschrift › Opmerking/debat

1 Citaat (Scopus)

Samenvatting

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.

Originele taal-2	Engels
Artikelnummer	7573
Pagina's (van-tot)	7573
Tijdschrift	Nature communications
Volume	13
Nummer van het tijdschrift	1
DOI's	https://doi.org/10.1038/s41467-022-32329-6
Status	Gepubliceerd - 8 dec 2022
Extern gepubliceerd	Ja

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10.1038/s41467-022-32329-6

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

PCAWG Tumor Subtypes and Clinical Translation Working Group ; PCAWG Consortium. / Erratum: Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature communications (2020) 11 1 (728)) : A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns. In: Nature communications. 2022 ; Vol. 13, Nr. 1. blz. 7573.

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title = "Erratum: Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature communications (2020) 11 1 (728)): A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns",

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 Sun, \{Ren X.\} and Marcel Kool and Stunnenberg, \{Henk G.\}",

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

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

Erratum: Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns (Nature communications (2020) 11 1 (728)): A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns. / PCAWG Tumor Subtypes and Clinical Translation Working Group; PCAWG Consortium.
In: Nature communications, Vol. 13, Nr. 1, 7573, 08.12.2022, blz. 7573.

Onderzoeksoutput: Bijdrage aan tijdschrift › Opmerking/debat

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T2 - A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

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 - Kool, Marcel

AU - Stunnenberg, Henk G.

PY - 2022/12/8

Y1 - 2022/12/8

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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.

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