Add example notebook with JUMP UMAP processing

[d33bs]

Description

This PR adds an example notebook to help demonstrate coSMicQC use with JUMP by performing a UMAP analysis. The output generally show where outliers occur within the embeddings from a sample of BR00117012 sourced from the cpg0000-jump-pilot JUMP dataset.

Additional notes:

• I took a moment to update the cosmicqc_in_a_nutshell notebook which recently was reorganized / was lacking display of outlined cells within the CytoDataFrame.
• As a result of this modification I also noticed some unnecessary print statements which I removed.
• The coverage was changed I believe due to these print statements being removed.
• I've double checked locally and saw that the interactive Bokeh plots render properly through Sphinx (which means they should render within GitHub Pages).

Thanks for any feedback you may have!

Closes #23
Closes #83
Closes #90

What kind of change(s) are included?

• Documentation (changes docs or other related content)
• Bug fix (fixes an issue).
• Enhancement (adds functionality).
• Breaking change (these changes would cause existing functionality to not work as expected).

Checklist

Please ensure that all boxes are checked before indicating that this pull request is ready for review.

• I have read and followed the CONTRIBUTING.md guidelines.
• I have searched for existing content to ensure this is not a duplicate.
• I have performed a self-review of these additions (including spelling, grammar, and related).
• These changes pass all pre-commit checks.
• I have added comments to my code to help provide understanding
• I have added a test which covers the code changes found within this PR
• I have deleted all non-relevant text in this pull request template.

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[gwaybio]

Love this analysis! I made some (mostly minor) comments to think about and potentially improve the work

[jenna-tomkinson]

I am approving this as I don't see this needing much more changes.

I am a bit confused by how the embeddings are connected back to the cosmicqc outlier status. Maybe more clarity would help me understand, since to me that could be impacting the pattern in the UMAPs.

Other than that, exciting to get this created! Feel free to merge or ask for further feedback after addressing comments.

[d33bs]

Thanks @gwaybio and @jenna-tomkinson for your earlier reviews! I've added a bunch of changes based on what you mentioned and this could use another look when there's a moment.

[gwaybio]

LGTM! 🤩

No need to address the following comment (and the three comments below), I think you're good to go:

FWIW, my "killer app" idea involved aggregating data with and without outliers, then applying UMAP to both of these aggregated datasets.

[jenna-tomkinson]

LGTM! I left some minor comments for you to address but feel free to merge when ready!

[d33bs]

Thanks so much @jenna-tomkinson and @gwaybio for your reviews! I've addressed all comments and added new figures based on the results. I'll now merge this in.