Identifying cancer subtypes
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3.4 years ago
glady ▴ 320

Hello,

A bulk tumor data is made up of a complex microenvironment: stromal cells, fibroblasts, tumor cells, etc.

Are there any machine learning or clustering methods that can perform a separation within a Tumor microenvironment, For example, if I pass on a dataset of the whole tumor from PDAC/lung/breast. As results, can I get different clusters of genes associated with: 1) tumor cancer cells 2) stromal cells (normal stroma and cancer stroma) 3) fibroblasts (cancer-associated fibroblast and normal fibroblasts)

Thank you.

RNA-Seq gene • 597 views
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By bulk tumor data - you mean bulk RNA-Seq data from a whole tumor, correct? When you say a data set of whole tumor from (three tissue types) does that mean you plan to mine several sets? Will you also have matching non-cancerous tissue? If you have many data sets, some basic clustering can help you define rough groups associated with your different conditions. If you have a single data sets and want to extract data on complex mixtures of cells...not so easy.

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bulk tumor = RNA-seq data from the whole tumor. Not multiple datasets, I mean to say a single dataset (PDAC). is it possible to perform a separation of the tumor microenvironment in one dataset with some machine learning or clustering methods?

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