A list of human cell cycle genes for Seurat
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5.2 years ago
Pestudkaru ▴ 40

Hi!

First of all I apologize if this question has already been asked. I googled the hell out it but couldn't find any help.

So my exact question is: where can I get a list of human cell cycle genes (the more recent the better) with annotations to which part of the cycle they belong to, so that I could use them in Seurat::CellCycleScoring In the vignette they are using mouse genes and if I try to use those genes on my data I get only one of my cells assigned to G2M and the rest are S (1 out of 500!)- so basically it doesn't work. I can use SCRAN package's Cyclone function just fine but principle there seems to be a bit different so I can't just copy the cell cycle info from there to Seurat package. I also found 2-3 pages/databases with lists of cell cycle genes (KEGG for example) but it's just a list of genes and I have no idea which one's are G1/G1/M/S. Has anyone tried using Seurat::CellCycleScoring on human data? How did you do it?

Thank you!

RNA-Seq Cell Cycle Single Cell • 4.9k views
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Thank you genomax but I've already seen both of those links and neither has the complete information I need. Qiagen (and KEGG as well) only has a list of genes that are Cell Cycle related but no information as to which part of the cycle (G1/2,S). And the link to the paper has some helpful information but they were more interested in periodic genes than what part of the cycle any of those genes really was.

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It would be good to add some information about where and how did you generate this list since it seems to be hosted in your personal space without any reference.

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The list of Shicheng Guo seems to originate from A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer Table S2 (67 core genes).

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2.5 years ago
vps767 ▴ 20

Sorry for the very delayed response, but this may be helpful for someone searching for an answer to the question. Seurat v3 comes with human sets of cell cycle genes (there is an older version besides one listed below). This will get you what you need.

s.genes <- cc.genes.updated.2019$s.genes
g2m.genes <- cc.genes.updated.2019$g2m.genes
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