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I have RNA-seq .bam files for 3 patients, tumour and its matched derived model, namely organoid, but I don't have any matched normal sample.

Differentially expressed genes between a tumour and its model mainly come from the presence and lack of microenvironment in cancers and organoids respectively and response to stimuli (artificial environment in organoid culture vs cancer.

How I can get the differentially expressed genes specific to microenvironment?

Any intuition please?

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    $\begingroup$ Sauret package for unsupervised learning is a start, lots of discussion on this board about it $\endgroup$
    – M__ ♦
    Mar 15, 2019 at 13:10
  • $\begingroup$ I can't find a package named Sauret, if you refer to Seurat it is for scRNA-seq which this question is not tagged with it so I think it won't work well in this case. $\endgroup$
    – llrs
    Mar 15, 2019 at 15:50

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The genes related to the environment can be identified using a linear model where each organoid is compared to the correspondent original tumor. This is assuming that the environment for all the organoids is the same and that the differences between tumors is just from different patient but are from the same organ/region.

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