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Separate load and calculate_multifactor_PMD calculation -> have two separate function calls for these; load should store stuff in the AnnData object already
Rename the MCPs to something better and not just 0, 1, ...
Rewrite the MCP concatenation to ensure that we're not returning an AnnData object but modifying inplace
Write tests for the functions
Solve TODOs
Add plotting functions from DIALOGUE R
Think about factoring all DIALOGUE 1, DIALOGUE 2 and DIALOGUE 3 steps into their own Python files aka create a private _dialogue module
remove new_mcp_scores from multilevel_modeling and expose calculate_cca_sig
ensure calculate_cca_sig and multilevel_modeling can be called separately
Store the most used parameters in the DIALOGUE object -> e.g. sample etc
hierarchical modeling only returns results for 1 cell type -> why?!? Is the result being overwritten?
results from hierarchical modeling should not return sig_genes per cell type pair but rather per cell type
make sure user is aware that n_UMI needs to be logged if .X is logged
multilevel_modeling does not allow for confounder to be None -> code breaks (ignore type hints)
A reimplementation of https://github.com/livnatje/DIALOGUE could be awesome.
Then we could also talk to @davidsebfischer et al. to see how far their MCP method is.
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