Handling "Non-Standard" AnnData Zarr Data about vitessce-python HOT 8 CLOSED

I will close this now that we have vitessce/vitessce#807 and open a new issue for integrating it here

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Yes 'CellType' is just specific to one .h5ad file I was working with at the time. I started to move away from it on this branch https://github.com/vitessce/vitessce-python/blob/keller-mark/widget-method/vitessce/wrappers.py#L315 where I added a parameter for the AnnDataWrapper contructor to identify which column of adata.obs to use for cell sets. This is still a bit limiting though since as you point out there can be multiple columns with categorical data and we may want to output all of them as multiple cell set hierarchies. Maybe we can instead support a list of columns, like cell_set_obs_cols = [] and then the user could write something like AnnDataWrapper(adata, cell_set_obs_cols=["CellType", "leiden"]) based on the columns they want to use for cell sets.

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When reading straight from JS, I think it may be helpful if the options object is reversed:

{
          "type": "cell-sets",
          "fileType": "anndata-cell-sets.zarr",
          "url": "http://127.0.0.1:8081/habib.zarr",
          "options": {
            "sets": ["obs.cellType", "obs.leiden"]
          }

and

{
          "type": "cells",
          "fileType": "anndata-cells.zarr",
          "url": "http://127.0.0.1:8081/habib.zarr",
          "options": {
            "xy": "obsm.spatial",
            "poly": "obsm.polygon",
            "mappings": {
                 "UMAP": {
                      "key": "obsm.X_umap",
                      "dims": [0, 1],
                   },
                 "PCA": {
                      "key": "obsm.X_pca",
                      "dims": [3, 5], // use principal components 4 and 6
                   },
            }
          }
        },

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I was just typing that...the sets example was making me think that the direction was wrong in how I laid things out... I am still not a fan of magic strings but I like where it's headed. I think we should try to cover our bases in Python around customization as much as possible and then port it to Javascript/JSON since once it's out in JS, we can't take it back whereas here we have a bit of a sandbox here to play in. I'll try loading Matt's datasets as well as going out and looking for others on the internet.

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When these are the values rather than the keys, we don't need to use magic strings, we can use arrays like ["obsm", "X_umap"] which would mean obsm.X_umap

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Maybe

{
          "type": "cell-sets",
          "fileType": "anndata-cell-sets.zarr",
          "url": "http://127.0.0.1:8081/habib.zarr",
          "options": {
            "sets": [["obs","CellType"], ["obs", "leiden"]]
          }

where each element of "sets" is a path to the column that should be used to define each cell set hierarchy

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When these are the values rather than the keys, we don't need to use magic strings, we can use arrays like ["obsm", "X_umap"] which would mean obsm.X_umap

I was referring more to sets as a key as opposed to xy and poly for example, but perhaps I am being too nit-picky. sets does not exist in our json schema but xy and poly do.

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Ah I see. Actually then something more like the cell-sets-tabular schema may be better https://github.com/hubmapconsortium/vitessce/blob/master/src/schemas/cell-sets-tabular.schema.json

Maybe

{
          "type": "cell-sets",
          "fileType": "anndata-cell-sets.zarr",
          "url": "http://127.0.0.1:8081/habib.zarr",
          "options": [
              {
                   "group_name": "Cell Type",
                   "set_name": ["obs", "CellType"],
                    "prediction_score": ["obs", "CellTypeScore"]
               },
              {
                   "group_name": "Leiden Clustering",
                   "set_name": ["obs", "leiden"]
               }
          ]

where set_name and prediction_score are assumed to be paths to AnnData columns, and group_name is assumed to be the name of the hierarchy, and cell_id is not needed since it would be automatically assigned based on the Cell IDs in the AnnData index.

This has the benefit of easily supporting the prediction score/confidence values as well.

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