Anyway, in every complex MS/MS experiment we ultimately select for fragmentation some ions that we didn't mean to. Increasing sample complexity, increasing the isolation window and decreasing the chromatographic separation all exacerbate this fact. There have been a number of different approaches to estimating or dealing with this. ProteinLasso is a new approach described in this recent paper from Ting Huang et. al., out of the Dalian University of Technology. The approach here, as far as I can tell is some high level statistics called lasso regression. My expert eye can pull a lot of very large capital letter Sigmas in both the figures and the text. The end point, however, is pretty clear -- false discovery rates calculations that appear to work with the same degree of efficiency whether the sample is simple or incredibly complex.
We'll spend some more time on FDR in the near future, but you should check out this paper. The software is also available through sourceforge if you just want to plunge right in.
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