Add PILOT

[mehdijoodaki]

Checklist

• Name of the tool: PILOT
• Short description: PILOT is a Python library for Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport.Transport (PILOT)
• How does the package use scverse data structures (please describe in a few sentences): PILOT utilizes AnnData for single-cell data representation and processing.
• The code is publicly available under an OSI-approved license
• The package provides versioned releases
• The package can be installed from a standard registry (e.g. PyPI, conda-forge, bioconda)
• The package uses automated software tests and runs them via continuous integration (CI)
• The package provides API documentation via a website or README
• The package uses scverse datastructures where appropriate (i.e. AnnData, MuData or SpatialData and their modality-specific extensions)
• I am an author or maintainer of the tool and agree on listing the package on the scverse website

[grst]

Hi @mehdijoodaki,

thanks for submitting! This is certainly a cool method and I like the detailled tutorials you have on your website.
I have a couple of comments regading the checklist that would need to be addressed before we can merge this:

The package provides API documentation via a website or README

I have seen you list function parameters for some of your functions in your tutorial, but what we mean by "API documentation" as a full overview of all (public) functions and their parameters, e.g https://scirpy.scverse.org/en/latest/api.html. There are sphinx plugins to generate such a page easily.

The package uses automated software tests and runs them via continuous integration (CI)

I don't think the repo has continuous integration, e.g. using github actions? You can find an example in our cookiecutter template: https://github.com/scverse/cookiecutter-scverse/blob/main/%7B%7Bcookiecutter.project_name%7D%7D/.github/workflows/test.yaml

The tests are also very minimal - while we don't have strict requirements on the test coverage at the moment, it would be good to test all public functions. At the very least to make sure they don't fail on example data, even better would be to also test their correctness, e.g. by running them on toy data with known expected results or by comparing against snapshots of the results run on example data.

[mehdijoodaki]

Hi @grst
Thanks for the helpful comments, I have fixed the requested changes, could you please look into it?
Thanks

[grst]

Sorry for the delay, this LGTM now!