Tp53 loss status update: bug fix

[kgaonkar6]

Purpose/implementation Section

What scientific question is your analysis addressing?

TP53 loss status was incorrectly coded in the previous PR where we converted some columns to binary but I didn't propogate the changes in the code correctly. I've now updated lines which caused the bug.

What was your approach?

Updating #922 to

• replace NA with 0 only when merging the hotspot/activating status with the full histology
• correctly summarizing and coding the conditions in TP53 status assignment chunk.

What GitHub issue does your pull request address?

#837

Directions for reviewers. Tell potential reviewers what kind of feedback you are soliciting.

Which areas should receive a particularly close look?

The summarizing binary status of hotspot/activating from SNV/indels is currently set as 1 if any SNV/indel is in hotspot and 0 if non of the multiple SNV/indels are in hotspots to keep it binary.
Or should it be comma separated as 1,0 is HGVSp_Short=X,Y and X overlaps a hotspot and Y doesn't?

Is there anything that you want to discuss further?

Is the analysis in a mature enough form that the resulting figure(s) and/or table(s) are ready for review?

Results

What types of results are included (e.g., table, figure)?

table

What is your summary of the results?

tp53_alterations_score_wide$tp53_altered %>% table()
activated      loss     Other 
       23       136       971 

Reproducibility Checklist

• The dependencies required to run the code in this pull request have been added to the project Dockerfile.
• This analysis has been added to continuous integration.

Documentation Checklist

• This analysis module has a README and it is up to date.
• This analysis is recorded in the table in analyses/README.md and the entry is up to date.
• The analytical code is documented and contains comments.

[jharenza]

Thank you @kgaonkar6 ! The fix looks good. I just have one comment - For Check if other cancer predisposition have high TP53 inactivation scores display in the HTML file looks very smushed - is it rendering that way on your end as well? Maybe a rerun and save of the HTML would fix?

[kgaonkar6]

Thank you @kgaonkar6 ! The fix looks good. I just have one comment - For Check if other cancer predisposition have high TP53 inactivation scores display in the HTML file looks very smushed - is it rendering that way on your end as well? Maybe a rerun and save of the HTML would fix?

Thanks for the review @jharenza! I added larger size param in each of the chunks to enlarge the plots.

[jharenza]

looks good now, thank you!

[jharenza]

I am going to merge this quick bug fix.