Multi-study meta-analysis of dog samples with oral diseases!

 

I'm wrapping up a meta-analysis right now that I've bugged just about every proteomic informatics person I know about in one way or another. The insanely beautiful data that I'm working on reanalyzing is from a patient study where they said "you thought CPTAC was thorough? hold my espresso". No joke 33 offline fractions at 2 hrs each on a QE HF on these priceless human samples. The data is perfect for what I'm doing, but during the uploading of data for almost 70 patients, they missed a few here and there. The PI is now retired and the team is dissolved, so I ain't getting patient 36 fraction 32 or patient 51 fraction 7. Whether to keep these patients or not is what I've been bugging people about. 

BTW, this data just provided a spreadsheet of which patient was whom and I find it just fine to work with. 😉. I didn't need a short wave radio or to learn Morse code or anything. 

Crap, that's a joke like 15 people might get, again, right? I need to get out of my house. 

The great people at the Proteomics Standards Initiative came up with a meta-data standard for data in repositories called SRDF and it's a great idea for anyone wanting to automatically pull loads of proteomics data for reanalysis. 

Since my poor sense of direction would never allow me to find the utility closet at HUPO where the PSI meeting is allowed to have their annual meeting, I missed it. When I was told I was supposed to be using this format, Google helpfully told me that it has something to do with condensed short wave radio signals. 

And....now....we're around to the topic of this post....

These researchers successfully drew conclusions from an extremely wide array of proteomic studies deposited over time for the under-studied disease that they are interested in. 

Including ELISA data - old spot cut out MALDI-TOF peptide mapping stuff and some more modern iTRAQ and TMT work.

Now -- do not get this sideways -- I'm going to figure out how to use LesSRDF this summer and be a good participating researcher to allow my data to be re-utilized by real bioinformatician later. We're all going ot need to do this to help our field be taken seriously by the outside world. 

However, I do think this is a good example of studies where this hasn't been done and no one will go back and do it later, where some interesting findings were still made.