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Implement MCP methods #90

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Zethson opened this issue Dec 8, 2021 · 1 comment
Open

Implement MCP methods #90

Zethson opened this issue Dec 8, 2021 · 1 comment
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enhancement New feature or request

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@Zethson
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Zethson commented Dec 8, 2021

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.

@Zethson Zethson added the enhancement New feature or request label Dec 8, 2021
@Zethson Zethson assigned yugeji and mumichae and unassigned antschum Oct 27, 2022
@Zethson
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Zethson commented Feb 8, 2023

TODO list

  • Implement DIALOGUE 2
  • Add DIALOGUE 3
  • 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)

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