American Chemical Society, Journal of Proteome Research, 2(13), p. 890-897, 2013
DOI: 10.1021/pr400937n
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One can interpret fragmentation spectra stemming from peptides in mass spectrometry-based proteomics experiments using so called database search engines. Frequently, one also runs post-processors such as Percolator to assess the confidence, infer unique peptides and increase the number of identifications. A recent search engine, MS-GF+, has shown promising results, due to a new and efficient scoring algorithm. However, MS-GF+ provides few statistical estimates about the peptide-spectrum matches, hence limiting the biological interpretation. Here, we enabled Percolator-processing for MS-GF+ output, and observed an increased number of identified peptides for a wide variety of datasets. In addition, Percolator directly reports p values and false discovery rate estimates, such as q values and posterior error probabilities, for peptide-spectrum matches, peptides and proteins, functions that are useful for the whole proteomics community.