<p>I'm analyzing Sn-RNA seq datasets which include different brain regions and spinal cord in patients and normal controls. I would have different comparison within and between individuals. I've got a question which I could not find the answer. First, I know that in the clustering step FindConservedMarkers is the best choice when you are comparing controls &amp; patients. I was wondering does that work the same when I want to compare two different regions like the brain and spinal cord? if not what do you recommend for this comparison? as there might be different cell population in two different regions and those regions are not the same</p>

CC BY-SA 4.0
2020-09-01T14:45:18.177Z
Hi @Paria I can't quite see how this is a question, its either a 'yes'  or a 'no;' (I'd steer towards yes). Maybe if you explain how you arrived at the conclusion that FindConservedMarkers was 'best choice' an informed point of view can be forwarded.
M__
CC BY-SA 4.0
2020-09-01T16:17:23.917Z
Hi @Michael. I am saying based on the Satija lab workflow. I have single-nuclei 10X genomics datasets. FindConservedMarkers code in Seurat helps to identify the shared gene expression across condition and cell-type identification. In my case I'm comparing two different region within individuls (same condition different regions) and I am asking wether this work the same in my case?
Paria
<single-cell><clustering><10x-genomics>
which marker identifications method is recommended when single-nuclei RNA seq datasets are integrated across regions
# which marker identifications method is recommended when single-nuclei RNA seq datasets are integrated across regions

(Asked by: username_0 on 2020-09-01)

I'm analyzing Sn-RNA seq datasets which include different brain regions and spinal cord in patients and normal controls. I would have different comparison within and between individuals. I've got a question which I could not find the answer. First, I know that in the clustering step FindConservedMarkers is the best choice when you are comparing controls & patients. I was wondering does that work the same when I want to compare two different regions like the brain and spinal cord? if not what do you recommend for this comparison? as there might be different cell population in two different regions and those regions are not the same

**Tags:** single-cell, clustering, 10x-genomics
> **Comments:**
> **username_1**: Hi @Paria I can't quite see how this is a question, its either a 'yes'  or a 'no;' (I'd steer towards yes). Maybe if you explain how you arrived at the conclusion that FindConservedMarkers was 'best choice' an informed point of view can be forwarded.  
> **username_0**: Hi @Michael. I am saying based on the Satija lab workflow. I have single-nuclei 10X genomics datasets. FindConservedMarkers code in Seurat helps to identify the shared gene expression across condition and cell-type identification. In my case I'm comparing two different region within individuls (same condition different regions) and I am asking wether this work the same in my case?  

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## 0 answers

