Paulo Carvalho
Fiocruz, Curitiba

PatternLab is a freely available, widely adopted integrated computational environment for analyzing shotgun proteomic data. It was launched in 2008 and, thanks to the continual influx of invaluable feedback from researchers,  it has undergone continual improvement as well as expansion [1].  PatternLab is very user-friendly thanks to its graphical user interface and offers a complete arsenal for analyzing all sorts of proteomic experiments, be them labeled (e.g., isobaric tags), or label-free (e.g., spec count or XIC).  In this talk, I will provide a brief overview of three of the modules that set it apart.  The first, PepExplorer [2], unlocks the quantitative proteomics of unsequenced organisms; its foundations are rooted in solid machine learning techniques that enable combining de novo sequencing results with a sequence alignment algorithm tailored for proteomics while providing dynamic and simplified reports at the protein level.  The second module, Isobaric Analyzer, enables the quantitative analysis of isobarically labeled peptides. Its hallmark is the use of a peptide-centric statistical approach; this enables the immediate spotting, in some specific cases, of only those portions of the protein that appear to have undergone changes in abundance.  This usually happens due to a mutation or PTM not considered by the search, commonly in scenarios originating from clinical proteomics.  In widely adopted approaches, such information is shadowed by a false result pointing towards the differential expression of the entire protein.  In this regard, our approach brings to the forefront the discussion of reconsidering how we do algorithms for differential proteomics.  Finally, the third module, SIM-XL, is a complete solution for analyzing data from cross-linking mass spectrometry experiments (XL-MS) [3].  This approach is invaluable for experiments targeting protein-protein interaction or aiming at further exploring protein structures.  SIM-XL is the first to provide results as an interactive graphical representation of the region (or regions) in question; for example, clicking on portions of the graph opens annotated mass spectra supporting that region.

PatternLab has been consolidated by enabling the analyses of billions of mass spectra over the years through the hands of various groups around the world.  It is freely available at http://patternlabforproteomics.org.