Extracts MS/MS ID data from mzIdentML (leveraging mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximal identifications at a user specified false discovery rate. Additional utilities include:
post-experimental recalibration of mass measurement accuracy
assessment of irregular and missed cleavages given the enzyme cleavage pattern
assessment of false discovery rates at peptide-to-spectrum match, unique peptide and protein levels
leverages brute-force and sophisticated optimization routines (Nelder-Mead and simulated annealing) for finding the filtering criteria that provide the maximum spectrum, peptide or protein identifications while not exceeding a corresponding preset threshold of false discovery rate
converts the results into MSnSet class object as spectral counting data
Vladislav A. Petyuk (email@example.com)
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