Prof. Alexey Nesvizhskii (left) of University of Michigan receives a thank-you gift from David Chiang after his talk.
If you really want to understand how peptide and protein identification is done, this video talk is a must-see!
Professor Alexey Nesvizhskii of the University of Michigan is one of the co-inventors (with Dr. Andy Keller) of the popular PeptideProphet/ProteinProphet algorithm for turning search engine results into statistically consistent peptide and protein identifications. (This algorithm is also the basis for the popular Scaffold software.)
At the “Translational Proteomics 2.0″ meeting, we were privileged to have Alexey give his insightful talk that reviews the various steps involved in inferring peptide and protein identifications from large spectra datasets.
In this talk, you will learn why False Discovery Rates are preferred over P-values, why you probably should not run more than 4 replicates of a MudPIT experiment, how FDR estimations from decoy differ from Peptide/ProteinProphet, how “The Two Prophets” compute probabilities by curve-fitting the score distributions, how sensitivity and FDR are computed, and the what and why of some advanced TPP options.
The talk is available at: http://www.scivee.tv/node/12671 (45 minutes).
I recommend using the “full screen” mode so you can view the slides, which are also available as a download from the site. (Please be aware that the slideset order is different from that in the presentation.)
(Note: Both Trans-Proteomic Pipeline and Scaffold Batch software are integrated into the SORCERER platforms.)