Include tree and text data.frame in SRCGrob #85
Merged
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Description
Closes #95. Sets up export of the final tree and text data used by the plot under
$input.data$tree
and $input.data$text`. This differs from the input data by including any replacements to default values and data transformations as a result of the internal prep functions. Exposing this data will allow users to tweak an existing plot more easily.At this point, there is no file export. I felt that including this functionality within the resulting plot object would allow users to use the data more flexibly. If CSV output is vital, it will be trivial to add - just another parameter and a standard
write.csv()
call at the end of the function.Closes #...
Checklist
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.
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.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. ↩