Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment.

Dasari S, Chambers MC, Martinez MA, Carpenter KL, Ham AJ, Vega-Montoto LJ, Tabb DL
J Proteome Res. 2012 11 (3): 1686-95

PMID: 22217208 · PMCID: PMC3292681 · DOI:10.1021/pr200874e

Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines.

MeSH Terms (15)

Algorithms Blood Proteins Cell Line Databases, Protein Humans Models, Statistical Neural Networks, Computer Peptide Mapping Proteome Reference Standards Search Engine Sequence Analysis, Protein Serum Albumin, Bovine Software Tandem Mass Spectrometry

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