IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1008769.html
   My bibliography  Save this article

COMSUC: A web server for the identification of consensus molecular subtypes of cancer based on multiple methods and multi-omics data

Author

Listed:
  • Song He
  • Xinyu Song
  • Xiaoxi Yang
  • Jijun Yu
  • Yuqi Wen
  • Lianlian Wu
  • Bowei Yan
  • Jiannan Feng
  • Xiaochen Bo

Abstract

Extensive amounts of multi-omics data and multiple cancer subtyping methods have been developed rapidly, and generate discrepant clustering results, which poses challenges for cancer molecular subtype research. Thus, the development of methods for the identification of cancer consensus molecular subtypes is essential. The lack of intuitive and easy-to-use analytical tools has posed a barrier. Here, we report on the development of the COnsensus Molecular SUbtype of Cancer (COMSUC) web server. With COMSUC, users can explore consensus molecular subtypes of more than 30 cancers based on eight clustering methods, five types of omics data from public reference datasets or users’ private data, and three consensus clustering methods. The web server provides interactive and modifiable visualization, and publishable output of analysis results. Researchers can also exchange consensus subtype results with collaborators via project IDs. COMSUC is now publicly and freely available with no login requirement at http://comsuc.bioinforai.tech/ (IP address: http://59.110.25.27/). For a video summary of this web server, see S1 Video and S1 File.Author summary: A number of methods have been developed for omics data-based subtyping, which has been widely accepted as a relevant source of cancer classification. However, discrepant results hamper the translational and clinical utility of these methods. In this study, we have developed the COnsensus Molecular SUbtype of Cancer (COMSUC) web server to provide a user-friendly tool for integrating discrepant clustering results based on multiple platform, multiple omics data and multiple methods. COMSUC provides powerful support to users to decipher the cancer Consensus Molecular Subtypes (CMSs), a consensus classification system integrating different clustering results.

Suggested Citation

  • Song He & Xinyu Song & Xiaoxi Yang & Jijun Yu & Yuqi Wen & Lianlian Wu & Bowei Yan & Jiannan Feng & Xiaochen Bo, 2021. "COMSUC: A web server for the identification of consensus molecular subtypes of cancer based on multiple methods and multi-omics data," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-10, March.
    • Handle: RePEc:plo:pcbi00:1008769
    DOI: 10.1371/journal.pcbi.1008769
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008769
    Download Restriction: no
    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008769&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pcbi.1008769?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Bank business models, size, and profitability," Finance Research Letters, Elsevier, vol. 53(C).
    2. Reder, Maik & Yürüşen, Nurseda Y. & Melero, Julio J., 2018. "Data-driven learning framework for associating weather conditions and wind turbine failures," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 554-569.
    3. Marcin Gąsior, 2021. "Environmental Attitudes and Willingness to Purchase Online—Classification Approach," Sustainability, MDPI, vol. 13(15), pages 1-17, August.
    4. Roopam Shukla & Ankit Agarwal & Kamna Sachdeva & Juergen Kurths & P. K. Joshi, 2019. "Climate change perception: an analysis of climate change and risk perceptions among farmer types of Indian Western Himalayas," Climatic Change, Springer, vol. 152(1), pages 103-119, January.
    5. Saemi Shin & Won Suck Yoon & Sang-Hoon Byeon, 2022. "Trends in Occupational Infectious Diseases in South Korea and Classification of Industries According to the Risk of Biological Hazards Using K-Means Clustering," IJERPH, MDPI, vol. 19(19), pages 1-19, September.
    6. Jihane El Ouadi & Hanae Errousso & Nicolas Malhene & Siham Benhadou & Hicham Medromi, 2022. "A machine-learning based hybrid algorithm for strategic location of urban bundling hubs to support shared public transport," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3215-3258, October.
    7. Cyril Atkinson-Clement & Eléonore Pigalle, 2021. "What can we learn from Covid-19 pandemic’s impact on human behaviour? The case of France’s lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    8. Kreitmair, Ursula & Bower-Bir, Jacob, 2021. "Too different to solve climate change? Experimental evidence on the effects of production and benefit heterogeneity on collective action," Ecological Economics, Elsevier, vol. 184(C).
    9. Getaneh Addis Tessema & Jan van der Borg & Anton Van Rompaey & Steven Van Passel & Enyew Adgo & Amare Sewnet Minale & Kerebih Asrese & Amaury Frankl & Jean Poesen, 2022. "Benefit Segmentation of Tourists to Geosites and Its Implications for Sustainable Development of Geotourism in the Southern Lake Tana Region, Ethiopia," Sustainability, MDPI, vol. 14(6), pages 1-25, March.
    10. Wu, Tong & Rocha, Juan C. & Berry, Kevin & Chaigneau, Tomas & Hamann, Maike & Lindkvist, Emilie & Qiu, Jiangxiao & Schill, Caroline & Shepon, Alon & Crépin, Anne-Sophie & Folke, Carl, 2024. "Triple Bottom Line or Trilemma? Global Tradeoffs Between Prosperity, Inequality, and the Environment," World Development, Elsevier, vol. 178(C).
    11. Petricli, Gulcan & Inkaya, Tulin & Gokay Emel, Gul, 2024. "Identifying green citizen typologies by mining household-level survey data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    12. Young Hyun Kim & Kug Jin Jeon & Chena Lee & Yoon Joo Choi & Hoi-In Jung & Sang-Sun Han, 2021. "Analysis of the mandibular canal course using unsupervised machine learning algorithm," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-13, November.
    13. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2017. "Simulation-based exploration of high-dimensional system models for identifying unexpected events," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 317-330.
    14. Ben Beck & Meghan Winters & Trisalyn Nelson & Chris Pettit & Simone Z Leao & Meead Saberi & Jason Thompson & Sachith Seneviratne & Kerry Nice & Mark Stevenson, 2023. "Developing urban biking typologies: Quantifying the complex interactions of bicycle ridership, bicycle network and built environment characteristics," Environment and Planning B, , vol. 50(1), pages 7-23, January.
    15. Haytham Mohamed Salem & Linda R. Schott & Julia Piaskowski & Asmita Chapagain & Jenifer L. Yost & Erin Brooks & Kendall Kahl & Jodi Johnson-Maynard, 2024. "Evaluating Intra-Field Spatial Variability for Nutrient Management Zone Delineation through Geospatial Techniques and Multivariate Analysis," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    16. Raquel Lourenço Carvalhal Monteiro & Valdecy Pereira & Helder Gomes Costa, 2019. "Analysis of the Better Life Index Trough a Cluster Algorithm," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 477-506, April.
    17. Yürüşen, Nurseda Y. & Rowley, Paul N. & Watson, Simon J. & Melero, Julio J., 2020. "Automated wind turbine maintenance scheduling," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    18. Magacho, Guilherme & Espagne, Etienne & Godin, Antoine & Mantes, Achilleas & Yilmaz, Devrim, 2023. "Macroeconomic exposure of developing economies to low-carbon transition," World Development, Elsevier, vol. 167(C).
    19. Peter Radchenko & Gourab Mukherjee, 2017. "Convex clustering via l 1 fusion penalization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1527-1546, November.
    20. Federica Scucchia & Paul Zaslansky & Chloë Boote & Annabelle Doheny & Tali Mass & Emma F. Camp, 2023. "The role and risks of selective adaptation in extreme coral habitats," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1008769. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.