In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy

Part of the Methods in Molecular Biology book series (MIMB, volume 2120)


Several computational methods have been proposed to infer the cellular composition from bulk RNA-seq data of a tumor biopsy sample. Elucidating interactions in the tumor microenvironment can yield unique insights into the status of the immune system. In immuno-oncology, this information can be crucial for deciding whether the immune system of a patient can be stimulated to target the tumor. Here, we shed a light on the working principles, capabilities, and limitations of the most commonly used methods for cell-type deconvolution in immuno-oncology and offer guidelines for method selection.

Key words

Cell-type deconvolution Immuno-oncology Spillover Gene signatures 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Biocenter, Institute of BioinformaticsMedical University of InnsbruckInnsbruckAustria
  2. 2.Big Data in BioMedicine Group, TUM School of Life SciencesTechnical University of MunichFreisingGermany

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