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Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data. ; LG was supported by the European Union 7th Framework Program (PRIME-XS project, grant agreement number 262067) and a BBSRC Strategic Longer and Larger grant (Award BB/L002817/1). LMB was supported by a BBSRC Tools and Resources Development Fund (Award BB/K00137X/1). TN was supported by a ERASMUS Placement scholarship. ; This is the final published version of the article. It was originally published in Proteomics (PROTEOMICS Special Issue: Proteomics Data Visualisation Volume 15, Issue 8, pages 1375–1389, April 2015. DOI:10.1002/pmic.201400392). The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/pmic.201400392/abstract.

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. ; The authors thank Andreas Hühmer, Philip Remes, Jesse Canterbury and Graeme McAlister of Thermo Fisher Scientific, San Jose, CA, USA, for their advice regarding operation of the Orbitrap Fusion. We also thank Mike Deery for assistance with checking sample integrity on the mass spectrometers in the Cambridge Centre for Proteomics on equipment purchased via a Wellcome Trust grant (099135/Z/12/Z ), and Brian Hendrich of the Wellcome Trust-MRC Stem Cell Institute in Cambridge and Sean Munro of the MRC Laboratory of Molecular Biology in Cambridge for insightful comments about the data. AC was supported by BBSRC grant (BB/D526088/1). C.M.M. and L.G. were supported by European Union 7th Framework Program (PRIMEXS project, grant agreement number 262067), L.M.B was supported by a BBSRC Tools and Resources Development Fund (Award BB/K00137X/1), and P.C.H. was ...

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and posttranslational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. ; Wellcome Trust grant (099135/Z/12/Z ), Wellcome Trust-MRC Stem Cell Institute in Cambridge and Sean Munro of the MRC Laboratory of Molecular Biology in Cambridge for insightful comments about the data. A.C. was supported by BBSRC grant (BB/D526088/1). European Union 7th Framework Program (PRIMEXS project, grant agreement number 262067), BBSRC Tools and Resources Development Fund (Award BB/K00137X/1), ERC Advanced Investigator, Onassis Public Benefit Foundation, the Foundation for Education and European Culture (IPEP) and the Embiricos Trust Scholarship of Jesus College Cambridge. Commonwealth Split Site. ERASMUS Placement. ; http://www.nature.com/ncomms ; hb2015