VAF Cutoff Filter Experiment for SNV callers

[cansavvy]

Purpose/implementation

This is a side analysis that originated from this original PR and analysis.

Note: This PR depends on changes made in #172 and shouldn't be reviewed or tested until that is merged.

After doing some initial comparisons of the callers TMB stats and finding them not well correlated to each other at all; the question from @jashapiro arose of whether increasing the VAF filter cutoff would help make the TMBs be more consistent across samples. Hence this analysis was born.

Issue

For SNV caller comparison #161, #103 and Tumor Mutation Burden #3 and sort of #11

Directions for reviewers

See the rough draft of this notebook output from this notebook here: https://cansavvy.github.io/openpbta-notebook-concept/snv-callers/vaf_cutoff_experiment.nb.html

Some questions for this PR:
What do you think of the current analyses?
Are there other analyses you would like to see added?
Should I put the custom functions in their own script in util folder as has been done for the previous functions in this analysis folder?

Results

See the rough draft of this notebook output from this notebook here: https://cansavvy.github.io/openpbta-notebook-concept/snv-callers/vaf_cutoff_experiment.nb.html

Preliminary conclusion:
It looks like increasing the VAF cutoff improves the callers' TMB calculations in how much they are related to each other. However, note that although VarDicts TMBs get recovered a bit by increasing a VAF filter cutoff, VarDict's TMBs are still the least associated with the other callers'.

Docker and continuous integration

• The dependencies required to run the code in this pull request have been added to the project Dockerfile.
  Main RPackages added to the Dockerfile:
• UpSetR
• GGally
• ggupset
• This analysis has been added to continuous integration.

PR Checklist

• Run a linter
• Set the seed- I didn't, but let me know if I should.
• Comments and/or documentation up to date
• Double check your paths
• Spell check any Rmd file or md file
• Restart R and run all notebooks fresh and save

[cbethell]

LGTM, I just have a few comments below.

[jashapiro]

Overall, looks good and gets the point across. I was confused by the variance calculations, and I am not sure whether they really are useful in this context. It isn't really a sampling question (you chose the cutoffs; they aren't random sets), so the changes in TMB aren't really something that variance makes sense for. I'd probably just eliminate that section.

[cansavvy]

It isn't really a sampling question (you chose the cutoffs; they aren't random sets), so the changes in TMB aren't really something that variance makes sense for. I'd probably just eliminate that section.

The main point I was searching for here was "how much are individual sample's TMB's changing as we change VAF cutoffs?" I get that variance is not quite appropriate for this, but wasn't sure how to show this. That being said, I am fine with dropping that whole section and moving on.

[cansavvy]

Okay, @cbethell and @jashapiro, I've removed the confusing sample TMB variance section, added a summary at the top of the file, but did not make a separate util file (I've decided I prefer to keep the functions of this notebook as separate from the other more main-line items in this analysis). How do we feel about this PR now?

[jashapiro]

Done and dusted