Re-assess quantiseq results at tumor purity threshold

[sjspielman]

Closes #1628

This PR updates the quanTIseq module to assess to what extent key results (indicated in issue #1628) might change if we perform deconvolution only on tumors that pass a purity threshold.

Punchline: Results are consistent, but I did identify a place where we might want to make a general revision in the manuscript regarding quanTIseq interpretations. Specifically, we reference HGGs broadly in this sentence, but only DMGs are plotted in the figure. So, we may just want to focus on talking about DMGs. https://github.com/AlexsLemonade/OpenPBTA-manuscript/blob/b0fdf6f24fe9c021f22e8b7da348708f68877ee5/content/03.results.md?plain=1#L283

Surprisingly, the classically immunologically-cold HGG and DMG tumors [@doi:10.1186/s40478-018-0553-x; @doi:10.1093/brain/awab155] contained higher overall fractions of immune cells, where monocytes, dendritic cells, and NK cells were the most prevalent (Figure {@fig:Fig5}C).

There are several key code changes:

• Added an flag in the module crux script to generate results from thresholded data. I re-organized the script a tiny amount to avoid having to write duplicated code in this update.
• Added a notebook to process these results and evaluate if they are consistent with original results. In this case, we just use data visualization. This notebook is documented in the README.
• The module run script will call all of the above ^

Here is the rendered notebook! 03-quantiseq-at-threshold.nb.html.zip

[sjspielman]

In https://github.com/AlexsLemonade/OpenPBTA-analysis/pull/1660/commits/ec9cab75531de583e69f1443eb2f2c809edda7b0, I incorporated the tumor purity filtering function and re-ran the module. There were no diffs from re-running.