Single-cell pseudotime and gene regulatory analysis with CellOracle
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- Опубликовано: 12 июл 2024
- CellOracle is a powerful suite of tools that can perform pseudotime analysis, gene regulatory network analysis, and in silico perturbation analysis on single-cell data in python. This is a simple tutorial covering the basics of CellOracle while analyzing a developmental pancreas dataset.
Notebook:
github.com/mousepixels/sanbom...
Reference:
www.nature.com/articles/s4158...
0:00 Intro
1:07 Prepare
4:15 Pseudotime
8:56 Regulatory
14:20 Perturbation
20:22 Conclusions 
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Thank you for the informative tutorial video; it has been immensely beneficial to my scientific research!😄
Glad it was helpful!
Thank you for the video! I've noticed recently that some features of scGPT seem similar to this video. Looking forward to watching a tutorial on scGPT.
Will try this soon! Thanks a lot!
Good luck!
Thank you!
Thank you a lot!!!!
Thanks a lot for the vídeo!
No problem!
awesome! thank you!
You are welcome!
Fantastic video as always! Just wondering, can CellOracle perturb more than one gene at a time like Dynamo can? Thanks!
Yup! You can pass a list instead of an individual gene
CellOracle can only knockout transcription factors since it uses ATAC seq for basic GRN, Dynamo doesn't mention this limitation but the examples shown in the paper also only have TF KO, do you know any package that can be used to knockout any genes? or Do you think Dynamo is able to do so?
Hi! thanks for this! just wondering if you have tried comparing results of CellOracle from SCENIC?
I haven't, but there is someone in the lab working on that at the moment.
Hey! Could you please explain what these computed counts are?
How to use this method if you have a very small population of cells plus majority of cells in a different cluster