Single cell RNASeq + Plasma Proteomics + Machine Learning!

You should check out this new preprint here! 


What a great week or 10 days for proteomics. Holy cow. January was kind of laggy and then -- BOOOOOOOOOOOM --!!

Okay -- in yet another that is going into a file called "January 2020 papers you must read!!" -- which -- is too many words for this cursed Windows 10 thing --

(BERNIE BOMB!)

Back to the paper -- if you just read the abstract, the phrasing will make you think that or friends at the Max Planck jumped on the ScoPE-MS electric Porsche into the future but you'll find inside that more standard plasma profiling (which looks a lot to me like at lot of the clinical proteomics proof - of - concept work we've seen from the Mann lab -- high fractionation, rapid HF runs [relatively affordable instrument!!] for individual patients and MBR). You can read my rambling about one of my favorite of these recent studies here.

Couple that to high throughput single cell transcriptomics and then using machine learning to link the plasma proteome features to the single cell transcripts across 31 clinically derived factors from these patients and -- it looks like the future to me, but it appears they took the Tesla.

...which...of course, that is a thing, right?

Since I'm still rambling -- this preprint was posted in medrXiV, which has some great disclaimers.