@inbook{d003a7e7fbb2480c9aaa337abfa2e787,
title = "In silico cell-type deconvolution methods in cancer immunotherapy",
abstract = "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.",
keywords = "Cell-type deconvolution, Gene signatures, Immuno-oncology, Spillover",
author = "Gregor Sturm and Francesca Finotello and Markus List",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC, part of Springer Nature 2020.",
year = "2020",
doi = "10.1007/978-1-0716-0327-7_15",
language = "English",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "213--222",
booktitle = "Methods in Molecular Biology",
}