Sunday, February 14, 2016
SUPERQuant test number 1
So I actually read some of the SuperQuant paper and then set up the method to run like this. After multiple failures that ended up just being me running out of C:\ space, I got a couple of runs in.
At first approach, I think the darned thing totally works. I also think that it needs some further evaluation.
I'll queue up a bunch of stuff to run now that I have some space, but here are a couple of screenshots.
HeLa 1ug 120min run on 25cm EasySpray columns running in High/High mode (this is the normal HeLa file that I have used for just about every experiment you see on this blog that used to be publicly available via my old FTP site, so I know a lot of you out there have it.
Ran just like above for the SUPERQuant runs and without the 2 new nodes in the nonSuperQuant comparator.
Interesting! In the end, what do we get? 39 new proteins. Okay. Worth noting that this took approximately 50% more total processing time than what I had with the regular method.
Check out how many MS/MS spectra it thinks it looked at!!! It thinks it saw over 30,000 more MS/MS spectra after the processing. Through that Percolator actually ended up with FEWER PSMs. One thing we know about Percolator, though is that is works better the more MS/MS spectra it sees, right?
Does that mean that the matches I'm looking at after SUPERQuant are better than those before? I'm trying to come up with a good way to assess. I know for sure that the worst scoring peptide (and totally not a good match) disappears after SUPERQuanting. But the output here is just a little dense without plotting. What I do know is that I have more Protein groups ID'ed on a small quick dataset after SuperQuanting, and it didn't take long to install OR run and a really bad peptide that slipped through all my filters disappears after using these cool free nodes.
Sounds like a darned win to me. I'll feed it some more stuff and see if I can make sense out of it, but I definitely recommend you check this out!
EDIT: Another couple runs finished up! Bigger dataset (55K MS/MS scans OT/OT on a Lumos)
SuperQuant gives me 100 new protein groups from over 1,000 new PSMs and its still hard to tell, honestly if the data coming out is better, but I feel pretty confident that it isn't markedly worse. Here is a quick screenshot. PSM #s vs. XCorr (I know...if you come up with a smarter metric, let me know...)
The 1,000 new PSMs look as solid to me as the rest of the data. More data for free? Consider me all signed up!