Thank you for the question!
I'm Kenji, a developer of CellOracle.
That is a really important question, and happy to clarify that!
In principle, CellOracle is developed to analyze dynamic data such as developmental processes and cellular reprogramming. In our study (https://www.nature.com/articles/s41586-022-05688-9), we analyzed zebrafish embryogenesis (Figure 3 and 5), which include multiple time points data. And it is nice if we could use data that include multiple time points.
But, using single time point data is still no problem if the data includes enough heterogeneity. We analyzed mouse hematopoiesis data, which consists of single time point data (Figure1 and 2 in our paper above). In general, scRNA-seq data includes a heterogeneous population in most cases of development and tumor, and we can try to analyze that data with CellOracle.
As another critical point of the CellOracle analysis, we need to ensure the data represents a continuous process. Let me describe two examples.
Let's assume that you merge two healthy cell samples and tumor cell samples from really different two-time points and the data lacks intermediate states. In that case, the dimensional reduction result will show a discrete structure; we cannot make a trajectory for the conversion. Thus, CellOracle cannot analyze the transition due to the lack of transition state data.
Another bad case scenario is your data is too homogeneous. For example, if your data include only one pure population, such as a sorted cell population or pure cell line, there may be no dynamics or transitions, and CellOracle cannot analyze it.
In your case, I assume you make scRNA-seq data in tumor tissue. I think CellOracle analysis results make sense if the data include heterogeneous cell states, such as tumor cell type, and non-tumor cell type, and intermediate cell type between them. As a practical viewpoint, please check the cell trajectory structure. If you can make continuous dimensional reduction embedding that nicely represents the biological transition events of your interest, CellOracle works well.
Your question here is critical. Thank you for the question. I will also add this explanation to the CellOracle documentation for other users.
Nice work! Here, we construct a cross-stage development atals of cell A, such as monocle in different organ. I wondered if I just perform the GRN analysis to decode the stage-specific GRN of of cell A but not the in slico simulation analysis. Thanks
Thank you for the question! I'm Kenji, a developer of CellOracle. That is a really important question, and happy to clarify that!
In your case, I assume you make scRNA-seq data in tumor tissue. I think CellOracle analysis results make sense if the data include heterogeneous cell states, such as tumor cell type, and non-tumor cell type, and intermediate cell type between them. As a practical viewpoint, please check the cell trajectory structure. If you can make continuous dimensional reduction embedding that nicely represents the biological transition events of your interest, CellOracle works well.
Your question here is critical. Thank you for the question. I will also add this explanation to the CellOracle documentation for other users.
Best, Kenji
Originally posted by @KenjiKamimoto-wustl122 in https://github.com/morris-lab/CellOracle/issues/103#issuecomment-1426198824
Nice work! Here, we construct a cross-stage development atals of cell A, such as monocle in different organ. I wondered if I just perform the GRN analysis to decode the stage-specific GRN of of cell A but not the in slico simulation analysis. Thanks