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Proteomics. 2013 Mar;13(5):766-70. doi: 10.1002/pmic.201200096. Epub 2013 Feb 4.

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

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Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA99352, USA.


For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.

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