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Create unit tests for HTPP global data fit with tcplfit2 #63

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sedavid01 opened this issue Oct 11, 2023 · 3 comments
Open
3 tasks done

Create unit tests for HTPP global data fit with tcplfit2 #63

sedavid01 opened this issue Oct 11, 2023 · 3 comments
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enhancement New feature or request

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@sedavid01
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sedavid01 commented Oct 11, 2023

Goal: The goal of this issue is to create unit tests for high-phenotypic profiling (HTPP) data such that we ensure that as the codebase of tcplfit2 is updated that the updates do not break/alter the results previously obtained in previous analyses with tcplfit2.

Needs for finishing this ticket:

  • Choose a manageable subset of the overall data provided by the HTTR team - verify the chosen set covers many (if not all) scenarios of interest
  • Create an RData file for the package (may want to ensure we do NOT want this to be exported from the package)
  • Create a unit test ensuring that the results for HTTR remain consistent from version to version of tcplfit2
@sedavid01
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Mostly a note so I do not forget the data subset creation steps discussed in 1:1 meeting:

  1. Move the data from Derik to the data-raw sub-dir of tcplfit2 R package. (DO NOT add or commit to Git history.)
  2. Add the sub-directory & RData files with data from Derik to the '.gitignore' file in the repo so the datasets do not get tracked with Git and pushed up to the remote repo.
  3. Create an R Script to generate the sub-set of data for testing. (Make sure to add the use_data and sessionInfo call to the end of this script but comment out for now until review and green light. The use_data will want to be internal - a sys type data saved under the data sub-directory with use_data.)

Once we have the sub-set together we will want to check back with the HTPP team that it meets their criteria before we create/save the sub-set and develop the tests.

@brown-jason, please review this plan and let me know if you have any comments, questions, and/or concerns.

@sedavid01 sedavid01 added the enhancement New feature or request label Oct 20, 2023
@sedavid01
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@gracezhihuizhao, next steps on the subsets:

  • check that in the subsets - for all levels we have a good mix of strong active and borderline active cases - suggest plotting the fits, looking at BMD and top/cutoff in conjunction with hitcall.
  • please put comments in the subset R script for how the responses for each subset were chosen

Apply these to #62 and #38 as well.

@sedavid01
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Update on dropped doses for HTPP data:

  • Write a brief explanatory comment about the dropped doses
  • Verify you are dropping the appropriate doses and number of doses for the respective chemicals
    (Note, suggesting to do the dropping the unit test code not in the data prep R script.)

@USEPA USEPA deleted a comment from gracezhihuizhao Jan 3, 2024
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