Benchmarking of the id dda workflow (ms2rescore, percolator, SNR)

[ypriverol]

PXD001819 Analysis

Currently, we have a workflow that can perform peptide identification using: -> ms2rescore -> SNR + spectrum properties -> percolator

Here the results can be found (https://ftp.pride.ebi.ac.uk/pub/databases/pride/resources/proteomes/quantms-benchmark/PXD001819-id-ms2rescore/).

Total number of PMSs

Comet only + Percolator: 495306 Comet + MSGF + Percolator: 572496 (15.58% increase) Comet + MSGF + ms2rescore: 589200 (18.95% increase) Comet + MSGF + (SNR + ms2rescore): 587972 (18.71% increase) Comet + MSGF + SAGE + (SNR + ms2rescore): 592918 (19.68% increase)

Total number of PSMs by RAW file and combination

Currently, the combination of ms2rescore alone has more PSMs identifications, followed by ms2rescore + SNR.

The following questions would be interesting to understand:

• When the spectrum quality metrics are introduced, are the PSMs more high-quality meaning that while we have fewer PSMs for ms2rescore + SNR they have more quality than ms2rescore?
• Do we see the same results in other datasets?
• What is the impact at peptide level?