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Add diagram #83
Add diagram #83
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As a note, I didn't add PlantUML at this point since there were some edits done outside of PlantUML for this flowchart |
Welp the latest pylint has a lot of issues with the |
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Why not add an SVG instead?
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I edited the PNG for the manuscript so I kept that for now; once I add the PlantUML, I'll switch it to the SVG
Description
Adding flowchart of validation
Checklist
File Commits
This PR does NOT contain Protected Health Information (PHI). A repo may need to be deleted if such data is uploaded.
Disclosing PHI is a major problem1 - Even a small leak can be costly2.
This PR does NOT contain germline genetic data3, RNA-Seq, DNA methylation, microbiome or other molecular data4.
.png
, .jpeg
),.pdf
,.RData
,.xlsx
,.doc
,.ppt
, or other output files.To automatically exclude such files using a .gitignore file, see here for example.
Code Review Best Practices
I have read the code review guidelines and the code review best practice on GitHub check-list.
I have set up or verified the
main
branch protection rule following the github standards before opening this pull request.The name of the branch is meaningful and well formatted following the standards, using [AD_username (or 5 letters of AD if AD is too long)]-[brief_description_of_branch].
I have added the major changes included in this pull request to the
CHANGELOG.md
under the next release version or unreleased, and updated the date.Testing
I have added unit tests for the new feature(s).
I modified the integration test(s) to include the new feature.
All new and previously existing tests passed locally and/or on the cluster.
The docker image built successfully on the cluster.
Footnotes
UCLA Health reaches $7.5m settlement over 2015 breach of 4.5m patient records ↩
The average healthcare data breach costs $2.2 million, despite the majority of breaches releasing fewer than 500 records. ↩
Genetic information is considered PHI.
Forensic assays can identify patients with as few as 21 SNPs ↩
RNA-Seq, DNA methylation, microbiome, or other molecular data can be used to predict genotypes (PHI) and reveal a patient's identity. ↩