Hi,

I have 6 RNA-seq samples like this

4 patients (005, 036, 121, 013)

I have 3 tumour samples and 3 cancer models (organoid)

This is PCA of log transformed data by DESeq2 (tumour Vs. organoid)

In this paper https://www.nature.com/articles/s41467-018-05190-9

They are saying

Finally, for each patient, the genes that are specifically up- or down regulated in each patient’s organoid (1 vs. all comparison, p ≤ 0.05 and abs (log2-FoldChange) ≤ 1) and that are among the top-50 genes with highest base mean expression were selected.

They have tumour and organoid like my case; My confusion is what they mean by "each patient’s organoid (1 vs. all comparison"? Because like them I need up or down regulated genes in each patient's organoid but I can not figure out I should compare each organoid versus what?

The ultimate goal would finding a signature of genes specific to each organoid as each organoid originates from tumour of a patient by these signatures one would be able to classify cancer to sub types

Any help please to an intuition

This support site is intended to help people with questions about Bioconductor packages. Your question is really 'what do the authors mean by this statement' and 'how should I analyze my data?', both of which are off-topic. For the first question, why don't you contact the authors and ask what they meant by that? I can't imagine anybody on this support site would have any more insight than the authors would.

As for your other question, that's a complex question that isn't easily answered in a support site. The conventional path is to either know what you want to do, and have an understanding of the tradeoffs you are making, or to find somebody local who does.