Building flexible and robust analysis frameworks for molecular subtyping of cancers

Christina Bligaard Pedersen, Benito Campos, Lasse Rene, Helene Scheel Wegener, Neeraja M Krishnan, Binay Panda, Kristoffer Vitting-Seerup, Maria Rossing, Frederik Otzen Bagger, Lars Rønn Olsen*

*Corresponding author for this work


Molecular subtyping is essential to infer tumor aggressiveness and predict prognosis. In practice, tumor profiling requires in-depth knowledge of bioinformatics tools involved in the processing and analysis of the generated data. Additionally, data incompatibility (e.g., microarray versus RNA sequencing data) and technical and uncharacterized biological variance between training and test data can pose challenges in classifying individual samples. In this article, we provide a roadmap for implementing bioinformatics frameworks for molecular profiling of human cancers in a clinical diagnostic setting. We describe a framework for integrating several methods for quality control, normalization, batch correction, classification and reporting, and develop a use case of the framework in breast cancer.

Original languageEnglish
JournalMolecular Oncology
Issue number3
Pages (from-to)606-619
Number of pages14
Publication statusPublished - Mar 2024


  • Breast Neoplasms/diagnosis
  • Computational Biology/methods
  • Female
  • Gene Expression Profiling/methods
  • Gene Expression Regulation, Neoplastic
  • Humans
  • RNA


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