Protocol for obtaining cancer type and subtype predictions using subSCOPE

Summary: We present a protocol for obtaining cancer type and subtype predictions using a machine learning method (subSCOPE). We describe steps for data preparation, subSCOPE setup, and running subSCOPE inference on prepared data. The protocol supports five -omics data types as input (DNA methylation...

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Main Authors: Jasleen K. Grewal, A. Gordon Robertson, Kyle Ellrott, Christopher K. Wong, Jordan A. Lee, Christina Yau, Bahar Tercan, Mauro A.A. Castro, Christopher C. Benz, Jean C. Zenklusen, Andrew D. Cherniack, Peter W. Laird, Steven J.M. Jones, Theo A. Knijnenburg, Vinicius S. Chagas, Victor H. Apolonio, Verena Friedl, Joshua M. Stuart, Vladislav Uzunangelov, Jesper B. Andersen, Galen F. Gao, Gad Getz, Stephanie H. Hoyt, Whijae Roh, Lindsay Westlake, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Anab Kemal, Roy Tarnuzzer, Zhining Wang, Liming Yang, Rehan Akbani, Bradley M. Broom, Zhenlin Ju, Andre Schultz, Akinyemi I. Ojesina, Katherine A. Hoadley, Avantika Lal, Daniele Ramazzotti, Chen Wang, Alexander J. Lazar, Lewis R. Roberts, Taek-Kyun Kim, Ilya Shmulevich, Paulos Charonyktakis, Vincenzo Lagani, Ioannis Tsamardinos, Esther Drill, Ronglai Shen, Martin L. Ferguson, Kami E. Chiotti, Brian J. Karlberg, Eve Lowenstein, Adam Struck, Paul T. Spellman, Toshinori Hinoue
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:STAR Protocols
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Online Access:http://www.sciencedirect.com/science/article/pii/S266616672500111X
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author Jasleen K. Grewal
A. Gordon Robertson
Kyle Ellrott
Christopher K. Wong
Jordan A. Lee
Christina Yau
Bahar Tercan
Mauro A.A. Castro
Christopher C. Benz
Jean C. Zenklusen
Andrew D. Cherniack
Peter W. Laird
Steven J.M. Jones
Theo A. Knijnenburg
Mauro A.A. Castro
Vinicius S. Chagas
Victor H. Apolonio
Verena Friedl
Joshua M. Stuart
Vladislav Uzunangelov
Christopher K. Wong
Jesper B. Andersen
Andrew D. Cherniack
Galen F. Gao
Gad Getz
Stephanie H. Hoyt
Whijae Roh
Lindsay Westlake
Christopher C. Benz
Jasleen K. Grewal
Steven J.M. Jones
A. Gordon Robertson
Samantha J. Caesar-Johnson
John A. Demchok
Ina Felau
Anab Kemal
Roy Tarnuzzer
Zhining Wang
Liming Yang
Jean C. Zenklusen
Rehan Akbani
Bradley M. Broom
Zhenlin Ju
Andre Schultz
Akinyemi I. Ojesina
Katherine A. Hoadley
Avantika Lal
Daniele Ramazzotti
Chen Wang
Alexander J. Lazar
Lewis R. Roberts
Taek-Kyun Kim
Ilya Shmulevich
Bahar Tercan
Paulos Charonyktakis
Vincenzo Lagani
Ioannis Tsamardinos
Esther Drill
Ronglai Shen
Martin L. Ferguson
Kami E. Chiotti
Kyle Ellrott
Brian J. Karlberg
Jordan A. Lee
Eve Lowenstein
Adam Struck
Paul T. Spellman
Christina Yau
Toshinori Hinoue
Peter W. Laird
author_facet Jasleen K. Grewal
A. Gordon Robertson
Kyle Ellrott
Christopher K. Wong
Jordan A. Lee
Christina Yau
Bahar Tercan
Mauro A.A. Castro
Christopher C. Benz
Jean C. Zenklusen
Andrew D. Cherniack
Peter W. Laird
Steven J.M. Jones
Theo A. Knijnenburg
Mauro A.A. Castro
Vinicius S. Chagas
Victor H. Apolonio
Verena Friedl
Joshua M. Stuart
Vladislav Uzunangelov
Christopher K. Wong
Jesper B. Andersen
Andrew D. Cherniack
Galen F. Gao
Gad Getz
Stephanie H. Hoyt
Whijae Roh
Lindsay Westlake
Christopher C. Benz
Jasleen K. Grewal
Steven J.M. Jones
A. Gordon Robertson
Samantha J. Caesar-Johnson
John A. Demchok
Ina Felau
Anab Kemal
Roy Tarnuzzer
Zhining Wang
Liming Yang
Jean C. Zenklusen
Rehan Akbani
Bradley M. Broom
Zhenlin Ju
Andre Schultz
Akinyemi I. Ojesina
Katherine A. Hoadley
Avantika Lal
Daniele Ramazzotti
Chen Wang
Alexander J. Lazar
Lewis R. Roberts
Taek-Kyun Kim
Ilya Shmulevich
Bahar Tercan
Paulos Charonyktakis
Vincenzo Lagani
Ioannis Tsamardinos
Esther Drill
Ronglai Shen
Martin L. Ferguson
Kami E. Chiotti
Kyle Ellrott
Brian J. Karlberg
Jordan A. Lee
Eve Lowenstein
Adam Struck
Paul T. Spellman
Christina Yau
Toshinori Hinoue
Peter W. Laird
author_sort Jasleen K. Grewal
collection DOAJ
description Summary: We present a protocol for obtaining cancer type and subtype predictions using a machine learning method (subSCOPE). We describe steps for data preparation, subSCOPE setup, and running subSCOPE inference on prepared data. The protocol supports five -omics data types as input (DNA methylation, gene expression, microRNA [miRNA] expression, point mutations, and copy-number variants) and allows individual cancer type and data type selection. For non-The Cancer Genome Atlas (TCGA) cancer samples, it provides subtype-level classification across 26 different TCGA cancer cohorts and 106 subtypes.For complete details on the use and execution of this protocol, please refer to Ellrott et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
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spelling doaj-art-467b2f5af5744591a89c30de2dc1ccb02025-08-20T02:11:36ZengElsevierSTAR Protocols2666-16672025-06-016210370510.1016/j.xpro.2025.103705Protocol for obtaining cancer type and subtype predictions using subSCOPEJasleen K. Grewal0A. Gordon Robertson1Kyle Ellrott2Christopher K. Wong3Jordan A. Lee4Christina Yau5Bahar Tercan6Mauro A.A. Castro7Christopher C. Benz8Jean C. Zenklusen9Andrew D. Cherniack10Peter W. Laird11Steven J.M. Jones12Theo A. KnijnenburgMauro A.A. CastroVinicius S. ChagasVictor H. ApolonioVerena FriedlJoshua M. StuartVladislav UzunangelovChristopher K. WongJesper B. AndersenAndrew D. CherniackGalen F. GaoGad GetzStephanie H. HoytWhijae RohLindsay WestlakeChristopher C. BenzJasleen K. GrewalSteven J.M. JonesA. Gordon RobertsonSamantha J. Caesar-JohnsonJohn A. DemchokIna FelauAnab KemalRoy TarnuzzerZhining WangLiming YangJean C. ZenklusenRehan AkbaniBradley M. BroomZhenlin JuAndre SchultzAkinyemi I. OjesinaKatherine A. HoadleyAvantika LalDaniele RamazzottiChen WangAlexander J. LazarLewis R. RobertsTaek-Kyun KimIlya ShmulevichBahar TercanPaulos CharonyktakisVincenzo LaganiIoannis TsamardinosEsther DrillRonglai ShenMartin L. FergusonKami E. ChiottiKyle EllrottBrian J. KarlbergJordan A. LeeEve LowensteinAdam StruckPaul T. SpellmanChristina YauToshinori HinouePeter W. LairdCanada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada; Corresponding authorCanada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, CanadaOregon Health and Science University, Portland, OR 97239, USAUC Santa Cruz Genomics Institute and Department of Biomolecular Engineering, Santa Cruz, CA 95060, USAOregon Health and Science University, Portland, OR 97239, USAUniversity of California, San Francisco, Department of Surgery, San Francisco, CA 94158, USA; Buck Institute for Research on Aging, Novato, CA 94945, USAInstitute of Systems Biology, 401 Terry Avenue North, Seattle, WA 98109, USABioinformatics and Systems Biology Laboratory, Federal University of Paraná, Curitiba, Paraná 81520-260, BrazilBuck Institute for Research on Aging, Novato, CA 94945, USACenter for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USAThe Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Corresponding authorDepartment of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA; Corresponding authorCanada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada; Corresponding authorSummary: We present a protocol for obtaining cancer type and subtype predictions using a machine learning method (subSCOPE). We describe steps for data preparation, subSCOPE setup, and running subSCOPE inference on prepared data. The protocol supports five -omics data types as input (DNA methylation, gene expression, microRNA [miRNA] expression, point mutations, and copy-number variants) and allows individual cancer type and data type selection. For non-The Cancer Genome Atlas (TCGA) cancer samples, it provides subtype-level classification across 26 different TCGA cancer cohorts and 106 subtypes.For complete details on the use and execution of this protocol, please refer to Ellrott et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.http://www.sciencedirect.com/science/article/pii/S266616672500111XBioinformaticsCancerGenomicsComputer sciences
spellingShingle Jasleen K. Grewal
A. Gordon Robertson
Kyle Ellrott
Christopher K. Wong
Jordan A. Lee
Christina Yau
Bahar Tercan
Mauro A.A. Castro
Christopher C. Benz
Jean C. Zenklusen
Andrew D. Cherniack
Peter W. Laird
Steven J.M. Jones
Theo A. Knijnenburg
Mauro A.A. Castro
Vinicius S. Chagas
Victor H. Apolonio
Verena Friedl
Joshua M. Stuart
Vladislav Uzunangelov
Christopher K. Wong
Jesper B. Andersen
Andrew D. Cherniack
Galen F. Gao
Gad Getz
Stephanie H. Hoyt
Whijae Roh
Lindsay Westlake
Christopher C. Benz
Jasleen K. Grewal
Steven J.M. Jones
A. Gordon Robertson
Samantha J. Caesar-Johnson
John A. Demchok
Ina Felau
Anab Kemal
Roy Tarnuzzer
Zhining Wang
Liming Yang
Jean C. Zenklusen
Rehan Akbani
Bradley M. Broom
Zhenlin Ju
Andre Schultz
Akinyemi I. Ojesina
Katherine A. Hoadley
Avantika Lal
Daniele Ramazzotti
Chen Wang
Alexander J. Lazar
Lewis R. Roberts
Taek-Kyun Kim
Ilya Shmulevich
Bahar Tercan
Paulos Charonyktakis
Vincenzo Lagani
Ioannis Tsamardinos
Esther Drill
Ronglai Shen
Martin L. Ferguson
Kami E. Chiotti
Kyle Ellrott
Brian J. Karlberg
Jordan A. Lee
Eve Lowenstein
Adam Struck
Paul T. Spellman
Christina Yau
Toshinori Hinoue
Peter W. Laird
Protocol for obtaining cancer type and subtype predictions using subSCOPE
STAR Protocols
Bioinformatics
Cancer
Genomics
Computer sciences
title Protocol for obtaining cancer type and subtype predictions using subSCOPE
title_full Protocol for obtaining cancer type and subtype predictions using subSCOPE
title_fullStr Protocol for obtaining cancer type and subtype predictions using subSCOPE
title_full_unstemmed Protocol for obtaining cancer type and subtype predictions using subSCOPE
title_short Protocol for obtaining cancer type and subtype predictions using subSCOPE
title_sort protocol for obtaining cancer type and subtype predictions using subscope
topic Bioinformatics
Cancer
Genomics
Computer sciences
url http://www.sciencedirect.com/science/article/pii/S266616672500111X
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