Entering edit mode
12 months ago
Chris
▴
340
Hi Biostars,
I work on single cell data and got this issue hope you can help. I got a cluster has many ribosomal genes. So what can we say about this? I think error with sample preparation. Thank you so much! I found a relevant post here, josegarciamanteiga's comment: https://github.com/satijalab/seurat/issues/759
We don't know the organism, we don't know the context, we don't know the experimental conditions....why is it a problem if you have a cluster enriched for a certain kind of biology? Why do you think an error with sample preparation would cause this? Are there any aspects of your data set that you can verify? i.e. any clusters that do make sense, or that indicate cell types you know to exist?
I don't say it is a problem just want to know about it because normally in single cell, I see each cluster according to a cell type but not a cluster with many ribosomal genes. In sample preparation, we remove ribosome RNA because it has the most abundance but not the thing we interested in. Yes, other clusters make sense because I expected those cell type. It is the human sample, iPSC differential into other cell type.
subset
call?My mistake, ribosomal genes but not mitochondria gene. A cluster has these genes with ave_log2FC > 2: RPL39, TPT1, RPS12, RPS29, RPL26, RPS21, RPL12, RPS15A, RPL32, RPL17, FTL, FTH1, RPS13, RPS14, RPL29, RPL24.
Please edit your post content and change "mitochondrial" to "ribosomal". I don't know how to interpret the fact that some of your clusters have a large fraction of ribosomal genes, maybe someone with more knowledge of biology can help.
Yes, I did. Thank you
Doesn't look like it - I'm still seeing: "After using
subset()
to remove cells have high mitochondria percentage, I still got a cluster has many mitochondria genes"