Maximum complexity of trees [question]

[vitkl]

Hi @LouisFaure

I am interested in using scFates to identify the tree of cell populations - but I am concerned about the complexity of the data. How complex can the tree be?
For example, imagine a neurogenesis dataset where multiple region-specific stem cells (RG) give rise to 3 trees of developing neurons:

Can the entire tree be analysed, or should it be pre-segmented into simpler parts?

[LouisFaure]

Hi @vitkl, SimplePPT or Elpigraph tree algorithms could quite capture the whole tree. The question is whether all segments of the tree is explained by cellular differentiation. If that is not the case (for example the source of variation of the RG base region could be cell location instead), then this path should not be included in the main tree. On the other hand, if all is explained by cellular differentiation, what would be the point of origin in the stem cell population? It might be that there is no clear point of origin, in that case scFates won't be able to resolve it. Finally, in my opinion it is fine to split the tree into multiple subtree/paths, that would facilitate analysis and visualisations. You can use build-in related functions

Hope that helps!

[vitkl]

Thank you for explaining. It sounds like you need to know quite a lot about the tree, in particular, you need to separate parallel differentiation processes that cannot be traced back to a shared starting point in a given dataset (such as the shared being point present in previous but unprofiled time points).