Provide tutorial for mars.name_cell_types

[Winbuntu]

Hi, I am wondering if you could provide more guidance for how to generate interpretable names for discovered clusters by calling: mars.name_cell_types(adata, landmarks, cell_type_name_map).

This was not included in any available tutorial, and the help/comments in the source code are not detailed enough.

[mbrbic]

Hi! I now updated the code with better description.

Naming function takes as argument:

• adata: anndata object returned by function train
• landmarks: cell type landmarks also returned by function train
• cell_type_name_map: dictionary with cell type name of previously seen cell types as key, and their cluster idx as value

This function will return dictionary with novel cell type cluster index as key and probabilities to all previously seen cell types as value.

You can check example of calling this function in main_TM for Tabula Muris data.

[Winbuntu]

Thanks for the quick reply! To my understanding, main_TM is the code for the leave-one-tissue-out analysis described in the Nature Methods manuscript? And by using adata, landmarks, scores = mars.train(evaluation_mode=True) , scores are the performance scores?

[mbrbic]

That is correct.