Entering edit mode
8 months ago
camillab.
▴
160
Hi,
Not sure if it is appropriate to ask so if it is not, please cancel the post!
Briefly I have to integrated 2 scRNA-seq datasets (damage vs damage+treatment) which are so similar that I could not see much differences between them (e.g., I get max 100 DEGs). I believe this is because of the nature of the dataset. However experimentally my colleagues observed differences between the same 2 conditions but when I look at the distribution of the DEGs. How do you think I should proceed? What would be the best practice?
Not sure if it is appropriate post! apologies if it is no!
Camilla
Can you specify what you mean by that? Did they look at the expression of individual candidate genes?
no, the conditions are damage vs damage+treatment. So they induce both the damage and damage+ treamtnet and they see an improvement in the phenotype and potentially at cellular level. So they then did scRNAseq to identify key genes involved in this positive effect of the treatment and I am supposed to analyze the dataset but I don't see difference between the 2 conditions. And obviously this could be due to the dissociation of the tissue to get the single cells as well as issue with the sequencing (eg. droplets). So I am wondering how should I treat those datasets?
100 DEGs is pretty different...