Rna Seq Cell Type Specificity

Question

[k.nirmalraman]

Hello,

I now have RNA-Seq data from different cell types and ideally the idea was to perform DE. However, I was wondering if it would be possible to identify cell type specific marker genes for these cell types.

What do you think is the ideal way to approach this question.

I am using DESeq for differential analysis.

Thanks in advance!

[David]

I don't really understand what is the question here. The answer is in your question. Performing DE analysis will give you cell type specific markers for the cell type you compare.

[k.nirmalraman]

I have atleast 5 different cell types and wanted to know if there is any other kind of approach/better approach can one take other than DESEq

[Sean Davis]

The definition of differential expression is pretty clear. However, the definition of cell-type-specific is not. If you can come up with a clear definition of that concept for your system, it might be easier to answer your question.

[k.nirmalraman]

Cell Type Specific: Genes that are predominantly expressed in a particular cell type and not in other (of course when performing DE Analysis, one would get this contrast with respect to two cell types.) But in this case, when one has many cell types, my approach would be to contrast all combinations.

My question is to find out if there are any direct method that is available to do this.

In other words, to identify a set of features that explicitly identify a cell type ie a sample from a given count data.... like clustering! Hope this helps to understand!

[Sean Davis]

See my answer below.

[Megh]

Hi,

I am looking to solve similar problem. I have been referring to the CellCODE enter link description here package but haven't been able to utilize it for my dataset.

Please let me know if you were able to figure it out and what approach did you use?

Thanks.

Answer 1

[David]

There are more than one way to go for it but the first step is to extract the 5 DE gene lists from your 5 cell types.

As a quick test I would do a Venn diagram. If you are lucky you will obtain genes that you declared "DE" and that are specific for the cell types.

After that you can try a PCA, for example, and looks at the gene ordering in the component capturing the most variance citation

This is one way to go for it.

Answer 2

[Sean Davis]

Assuming that what you are looking for is a set of genes that is differentially expressed in only one condition compared to all others, you could:

1. Apply voom from the limma package to transform your counts
2. Perform DE testing in the standard way using limma
3. Use the decideTests function in limma, which results in each gene being classified as up-or-down regulated while "conditioning" on other tests. There are some parameters to control how this is done, so you'll want to read the docs.

OR

1. Perform DE testing in edgeR
2. Use decideTestsDGE analogously to #3 above.