We need more statistics in proteomics. We all know that. We particularly need them in our quantification studies. This is a little easier when we're doing label free but, of course, that comes with its own set of new challenges.
I get all sorts of excited when I see a proteomics paper that looks like a listing of fraternity houses, and this new paper from Sarah Gerster, et al., definitely fits that description. In this study, the team describes SCAMPI, a protein quantification tool written in R, everyone's favorite statistics program.
Now, this is where this blogger stops. I drew your attention to it. I looked at every page. I think anything where we start to treat proteomics like every other science and do robust statistical magic is going to move us forward. I cant' really tell you if this is a good one, but it looks nice and it's got Ruedi Aebersold's name on it, so I figure it's worth checking out. At the very least it has a memorable name.
We need more statistics in proteomics. We all know that. We particularly need them in our quantification studies. This is a little easier when we're doing label free but, of course, that comes with its own set of new challenges. fengshui
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