Updates and Results from Changes in all-features/7-transform.ipynb

[maggielee1111]

Hi Daniel!
Due to recent updates in R libraries, I've made several modifications to all-features/7-transform.ipynb and the result seems a little different. Following are the changes I made.

1. added degree_transformer = to_fxn(params['degree_transformer']) since I assumed the project is trying to evaluate transformation for degree_df too.
2. changed the funs function to (across(everything() due to funs being deprecated.
3. changed "rbind_all()" to "bind_rows()" since was removed in dplyr [(https://github.com/remove rbind_list() and rbind_all() tidyverse/dplyr#4430)].
   And in the transformation-sweep.tsv I got, the first several lines transformation are

degree_transformer	dwpc_scaler	dwpc_transformer	alpha	auroc	auroc_lower	auroc_upper	auprc	auprc_lower	auprc_upper
asinh	mean	log1p	0	0.9941835007236502	0.9938819015259823	0.9944850999213182	0.9805812551344717	0.9797400253392432	0.9814224849297002
log1p	mean	log1p	0	0.9939196526468115	0.9936136156188465	0.9942256896747764	0.9799278139925953	0.9790933266429557	0.980762301342235
asinh	mean	asinh	0	0.9939028551379303	0.9936457501750738	0.9941599601007868	0.9798320302118215	0.9791166118524781	0.9805474485711649
asinh	mean	log1p	1	0.9936890048682038	0.9933479888988564	0.9940300208375511	0.977249912523295	0.9761768963653875	0.9783229286812024
asinh	mean	asinh	1	0.9935960703477849	0.9932037859475018	0.9939883547480679	0.9773938761438711	0.976172127586398	0.9786156247013441

Considering these outcomes, do you find the results acceptable? If so, I plan to initiate a pull request. I would appreciate any feedback or insights.

[dhimmel]

Hi @maggielee1111, sorry for the slow response. I think the PR is helpful because if anyone else is looking to run the code, it could save them a lot of time!

I am curious how different the results are. Perhaps we'll be able to see in the PR commit diffs.

[maggielee1111]

Hi Daniel!
I just start a PR. I added some changes in 7-transform.ipynb like I mentioned in my last comment, and also replaced the result of transform with the result I got.
When I looked into the data, I found out the input I use primary-aurocs.tsv has a different value from summary_df = readr::read_tsv('data/auroc.tsv').
I guess that is the reason I got a different result.