Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0

Paulo C. Carvalho, Diogo B. Lima, Felipe V. Leprevost, Marlon D.M. Santos, Juliana S.G. Fischer, Priscila F. Aquino, James J. Moresco, John R. Yates, Valmir C. Barbosa

Research output: Contribution to journalArticlepeer-review

176 Scopus citations


PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from.

Original languageEnglish (US)
Pages (from-to)102-117
Number of pages16
JournalNature Protocols
Issue number1
StatePublished - Jan 3 2016
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


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