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While writing tests for the incremental IO of metadata I added tests also for those metadata that we originally planned in the design doc for points but that we have only rarely used.
Specifically, points have two optional values
which specify the name of two columns with particular semantic:
feature_keycolumn is an optional column that contains the "main feature" of the points, ideally the gene_id;instance_keycolumn is an optional column that can be used to tell which point fall into which cell.The two columns above are very rarely used: I think that we never use
instance_keyand thatfeature_keyis used inaggregate()to infer a default value forvalue_keywhen this is not specified by the user.Since the practical rare usage I would consider simplify the points model and drop them; I think the effort to support and document a more complex data model is not paid off in practical terms in these cases. And while it's just little pieces of metadata, in general I think the leaner the model the better.
To be more precise, I have a preference for dropping both but I have no strong opinions for
feature_key. Instead, I believe that we should removeinstance_keyfor the following reasons:Finally, an argument for dropping
feature_keyis that if we unify points and circles, either both should have the extra column either none, and since it's not something need for circles and it is not essential for points, I would just drop it.CC @giovp@kevinyamauchi@melonora