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

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  • 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
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    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).
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