Sunday, July 1, 2018
CharmeRT -- Time to get a lot more peptide IDs with advanced second searching!
Hey. Could you use -- I dunno... --60% more IDs in some of your datasets?!? I'm going to assume you said "heck yes I could, but that would be crazy to ask for."
Say hello to CharmeRT!
I've been looking at this since it came out on Thursday -- and I still don't get all of it.
What I do get? Just about every time we fragment a "peptide" in a complex dataset, we actually fragment the thing we want to -- and everything within a dalton or two from it. You don't even have to look hard in your data to find really good peptides with tons of background behind them.
Random dataset I just pulled, sorted in terms of highest XCorr and highest coisolation interference.
Look at it's MS1
The target peptide and it's two isotopes are there -- but it looks to me like there is another peptide in there, right? We just want the one, but I fragmented everything in there that is yellow.
Could we go in and remove those nice matching MS/MS fragments above and re-search this spectra knowing that something in that yellow MS1 isolation window was the parent peptide?
And that's what CharmeRT is doing. Now -- this is where I get a little lost. It's more complex than this because it utilized retention time calculation through Elutator in some way to aid in the scoring. How cool is that? My guess is that on the second round you have to open up your MS1 tolerance -- so anything to help with your confidence has gotta help. Retention time is a great place to start!
The problem with retention time calculations is that you might be doing something really weird with your chromatography. If you are handpacking with noble gases while underwater or something and you just thought that this wasn't for you -- you just need this thing!
The Elutator RT trainer lets you load up some of your own data from peptides that have eluted off that mix of 80% C-18 and 20% Camel Dental Plaque that you know does the best job of getting those hydrophilic peptides -- and lets you create the training dataset that takes this into account for your lab and your conditions.
You can get all of this right now here!
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