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Interactive Peptide Spectral Annotator: A Versatile Web-based Tool for Proteomic Applications*

  • Dain R. Brademan
    Affiliations
    Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706

    Genome Center of Wisconsin, Madison, WI 53706
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  • Nicholas M. Riley
    Affiliations
    Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706

    Genome Center of Wisconsin, Madison, WI 53706
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  • Nicholas W. Kwiecien
    Affiliations
    Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706

    Genome Center of Wisconsin, Madison, WI 53706
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  • Joshua J. Coon
    Correspondence
    To whom correspondence should be addressed.
    Affiliations
    Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706

    Morgridge Institute for Research, Madison, WI 53715

    Genome Center of Wisconsin, Madison, WI 53706

    Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706
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  • Author Footnotes
    * This work was supported by NIH grants R35 GM118110, P41 GM108538, and DOE Great Lakes Bioenergy Research Center Office of Science BER Award Number DE-SC0018409. DRB was funded through an NHGRI training grant awarded to the Genomic Sciences Training Program (5T32HG002760). NMR was funded by an NIH Predoctoral to Postdoctoral Transition Award (F99 CA212454).
Open AccessPublished:May 14, 2019DOI:https://doi.org/10.1074/mcp.TIR118.001209
      Here we present IPSA, an innovative web-based spectrum annotator that visualizes and characterizes peptide tandem mass spectra. A tool for the scientific community, IPSA can visualize peptides collected using a wide variety of experimental and instrumental configurations. Annotated spectra are customizable via a selection of interactive features and can be exported as editable scalable vector graphics to aid in the production of publication-quality figures. Single spectra can be analyzed through provided web forms, whereas data for multiple peptide spectral matches can be uploaded using the Proteomics Standards Initiative file formats mzTab, mzIdentML, and mzML. Alternatively, peptide identifications and spectral data can be provided using generic file formats. IPSA provides supports for annotating spectra collecting using negative-mode ionization and facilitates the characterization of experimental MS/MS performance through the optional export of fragment ion statistics from one to many peptide spectral matches. This resource is made freely accessible at http://interactivepeptidespectralannotator.com, whereas the source code and user guides are available at https://github.com/coongroup/IPSA for private hosting or custom implementations.

      Graphical Abstract

      Tandem mass spectrometry (MS/MS)
      The abbreviations used are: MS/MS, tandem mass spectrometry; CSV, comma-separated value; MGF, mascot generic format; IPSA, interactive peptide spectral annotator; PSM, peptide spectral match; m/z, mass to charge ratio; ETD, electron transfer dissociation; EThcD, electron transfer and higher-energy collision dissociation; ETciD, electron transfer and collision-induced dissociation; AI-ETD, activated ion electron transfer dissociation; AI-NETD, activated ion negative electron transfer dissociation; UVPD, ultraviolet photodissociation; SVG, scalable vector graphic; ACN, acetonitrile; TFA, trifluoroacetic acid; PPM, parts per million; PTM, post-translational modification; FDR, false discovery rate; JSON, JavaScript Object Notation.
      1The abbreviations used are: MS/MS, tandem mass spectrometry; CSV, comma-separated value; MGF, mascot generic format; IPSA, interactive peptide spectral annotator; PSM, peptide spectral match; m/z, mass to charge ratio; ETD, electron transfer dissociation; EThcD, electron transfer and higher-energy collision dissociation; ETciD, electron transfer and collision-induced dissociation; AI-ETD, activated ion electron transfer dissociation; AI-NETD, activated ion negative electron transfer dissociation; UVPD, ultraviolet photodissociation; SVG, scalable vector graphic; ACN, acetonitrile; TFA, trifluoroacetic acid; PPM, parts per million; PTM, post-translational modification; FDR, false discovery rate; JSON, JavaScript Object Notation.
      is the centerpiece of modern proteome analysis. Advances in instrument design and acquisition software have enabled collection of well over 100,000 MS/MS scans in less than an hour of analysis (
      • Hebert A.S.
      • Richards A.L.
      • Bailey D.J.
      • Ulbrich A.
      • Coughlin E.E.
      • Westphall M.S.
      • Coon J.J.
      The One Hour Yeast Proteome.
      ,
      • Richards A.L.
      • Hebert A.S.
      • Ulbrich A.
      • Bailey D.J.
      • Coughlin E.E.
      • Westphall M.S.
      • Coon J.J.
      One-hour proteome analysis in yeast.
      ,
      • Senko M.W.
      • Remes P.M.
      • Canterbury J.D.
      • Mathur R.
      • Song Q.
      • Eliuk S.M.
      • Mullen C.
      • Earley L.
      • Hardman M.
      • Blethrow J.D.
      • Bui H.
      • Specht A.
      • Lange O.
      • Denisov E.
      • Makarov A.
      • Horning S.
      • Zabrouskov V.
      Novel parallelized quadrupole/linear ion trap/orbitrap tribrid mass spectrometer improving proteome coverage and peptide identification rates.
      ,
      • Richards A.L.
      • Merrill A.E.
      • Coon J.J.
      Proteome sequencing goes deep.
      ,
      • Hebert A.S.
      • Thöing C.
      • Riley N.M.
      • Kwiecien N.W.
      • Shiskova E.
      • Huguet R.
      • Cardasis H.L.
      • Kuehn A.
      • Eliuk S.
      • Zabrouskov V.
      • Westphall M.S.
      • McAlister G.C.
      • Coon J.J.
      Improved precursor characterization for data-dependent mass spectrometry.
      ,
      • Scheltema R.A.
      • Hauschild J.-P.
      • Lange O.
      • Hornburg D.
      • Denisov E.
      • Damoc E.
      • Kuehn A.
      • Makarov A.
      • Mann M.
      The Q exactive HF, a benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field orbitrap analyzer.
      ,
      • Kelstrup C.D.
      • Bekker-Jensen D.B.
      • Arrey T.N.
      • Hogrebe A.
      • Harder A.
      • Olsen J.V.
      Performance evaluation of the Q exactive HF-X for shotgun proteomics.
      ,
      • Bekker-Jensen D.B.
      • Kelstrup C.D.
      • Batth T.S.
      • Larsen S.C.
      • Haldrup C.
      • Bramsen J.B.
      • Sørensen K.D.
      • Høyer S.
      • Ørntoft T.F.
      • Andersen C.L.
      • Nielsen M.L.
      • Olsen J.V.
      An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.
      ,
      • Shishkova E.
      • Hebert A.S.
      • Coon J.J.
      Now, more than ever, proteomics needs better chromatography.
      ). Researchers have developed a wide variety of search algorithms and related computational tools to rapidly translate this large volume of experimental data to peptide spectral matches (PSMs), where peptide sequences are assigned to spectra to identify the proteins present in a sample (
      • Eng J.K.
      • Mccormack A.L.
      • Yates J.R.
      An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.
      ,
      • Cox J.
      • Mann M.
      MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.
      ,
      • Perkins D.N.
      • Pappin D.J. C.C.
      • Creasy D.M.
      • Cottrell J.S.
      Probability-based protein identification by searching sequence databases using mass spectrometry data.
      ,
      • Taylor J.A.
      • Johnson R.S.
      Sequence database searches via de Novo peptide sequencing by tandem mass spectrometry.
      ,
      • Ma B.
      • Zhang K.
      • Hendrie C.
      • Liang C.
      • Li M.
      • Doherty-Kirby A.
      • Lajoie G.
      PEAKS: Powerful software for peptide de novo sequencing by tandem mass spectrometry.
      ,
      • Chi H.
      • Sun R.X.
      • Yang B.
      • Song C.Q.
      • Wang L.H.
      • Liu C.
      • Fu Y.
      • Yuan Z.F.
      • Wang H.P.
      • He S.M.
      • Dong M.Q.
      PNovo: De novo peptide sequencing and identification using HCD spectra.
      ,
      • Sinitcyn P.
      • Daniel Rudolph J.
      • Cox J.
      • Rudolph J.D.
      • Cox J.
      Computational methods for understanding mass spectrometry–based shotgun proteomics data.
      ). An important component to this process is matching expected product ions to those observed in the experimental spectra. Annotation of spectra in this sense usually involves labeling observed m/z features with matched fragment ion designations (e.g. a/x-, b/y-, or c/z-type product ions) derived from the reported peptide sequence. Expert manual annotation is a valuable but greatly time-consuming process—unfeasible for the large volume of spectra generated in modern proteomic experiments.
      Proteomic field guidelines have increasingly emphasized the importance of providing access to annotated MS/MS spectra for publication, which allows others to inspect reported PSMs and validate their assignment to a given sequence (
      • Bradshaw R.A.
      • Burlingame A.L.
      • Carr S.
      • Aebersold R.
      Reporting protein identification data: the next generation of guidelines.
      ,
      • Jones A.R.
      • Eisenacher M.
      • Mayer G.
      • Kohlbacher O.
      • Siepen J.
      • Hubbard S.J.
      • Selley J.N.
      • Searle B.C.
      • Shofstahl J.
      • Seymour S.L.
      • Julian R.
      • Binz P.-A.
      • Deutsch E.W.
      • Hermjakob H.
      • Reisinger F.
      • Griss J.
      • Vizcaíno J.A.
      • Chambers M.
      • Pizarro A.
      • Creasy D.
      The mzIdentML data standard for mass spectrometry-based proteomics results.
      ,
      • Seymour S.L.
      • Farrah T.
      • Binz P.A.
      • Chalkley R.J.
      • Cottrell J.S.
      • Searle B.C.
      • Tabb D.L.
      • Vizcaíno J.A.
      • Prieto G.
      • Uszkoreit J.
      • Eisenacher M.
      • Martínez-Bartolomé S.
      • Ghali F.
      • Jones A.R.
      A standardized framing for reporting protein identifications in mzIdentML 1.2.
      ,
      • Burlingame A.
      • Carr S.A.
      • Bradshaw R.A.
      • Chalkley R.J.
      On credibility, clarity, and compliance.
      ). Many software tools have been created to aid researchers annotating individual PSMs contained in bulk datasets. Most such tools are downloadable and often integrated directly into data-analysis suites, although a handful have been developed as web browser-based platforms (
      • Baker P.R.
      • Chalkley R.J.
      MS-viewer: a web-based spectral viewer for proteomics results.
      ,
      • Strohalm M.
      • Hassman M.
      • Košata B.
      • Kodíček M.
      mMass data miner: An open source alternative for mass spectrometric data analysis.
      ,
      • Colinge J.
      • Masselot A.
      • Carbonell P.
      • Appel R.D.
      InSilicoSpectro: An open-source proteomics library.
      ). Lorikeet (https://uwpr.github.io/Lorikeet/) is a well-established web-based spectral annotator which has been integrated into several online mass spectrometry resources to visualize routine shotgun and cross-linked proteomics data (
      • Sharma V.
      • Eng J.K.
      • Maccoss M.J.
      • Riffle M.
      A mass spectrometry proteomics data management platform.
      ,
      • Riffle M.
      • Jaschob D.
      • Zelter A.
      • Davis T.N.
      ProXL (Protein Cross-Linking Database): A platform for analysis, visualization, and sharing of protein cross-linking mass spectrometry data.
      ,
      • Perez-Riverol Y.
      • Alpi E.
      • Wang R.
      • Hermjakob H.
      • Vizcaíno J.A.
      Making proteomics data accessible and reusable: Current state of proteomics databases and repositories.
      ,
      • Riffle M.
      • Merrihew G.E.
      • Jaschob D.
      • Sharma V.
      • Davis T.N.
      • Noble W.S.
      • MacCoss M.J.
      Visualization and dissemination of multidimensional proteomics data comparing protein abundance during Caenorhabditis elegans development.
      ). However, Lorikeet does not render generated annotated spectra in scalable vector graphics (SVG) format, limiting the flexibility of exported visualizations with regards to figure creation.
      Although powerful for the platforms for which they were designed, many of these tools are inseparable from their respective analytical pipelines; data visualization in MaxQuant is only available following processing with the integrated Andromeda search engine, for example. Their purview is therefore limited, and facile spectral annotation is restricted to only those search algorithms packaged in a pipeline with a developed annotator. This restriction poses a problem for numerous applications, especially for alternative peptide fragmentation methods such as ultraviolet photodissociation (UVPD), collisionally supplemented electron-transfer dissociation (EThcD), or activated-ion electron-transfer dissociation (AI-ETD) (
      • Ly T.
      • Julian R.R.
      Ultraviolet photodissociation: developments towards applications for mass-spectrometry-based proteomics.
      ,
      • Yu Q.
      • Wang B.
      • Chen Z.
      • Urabe G.
      • Glover M.S.
      • Shi X.
      • Guo L.W.
      • Kent K.C.
      • Li L.
      Electron-transfer/higher-energy collision dissociation (EThcD)-enabled intact glycopeptide/glycoproteome characterization.
      ,
      • Ledvina A.R.
      • Beauchene N.A.
      • McAlister G.C.
      • Syka J.E.P.
      • Schwartz J.C.
      • Griep-Raming J.
      • Westphall M.S.
      • Coon J.J.
      Activated-ion electron transfer dissociation improves the ability of electron transfer dissociation to identify peptides in a complex mixture.
      ). Often these methods can be integrated into established analytical pipelines adopted by the field over the course of several years. But flexible annotation tools are largely unavailable in the beginning stages of method development—arguably when they are needed most. For example, Lorikeet bundles annotation calculations directly with its spectrum viewer. This requires in-depth knowledge of Lorikeet's architecture to add functionality for new technologies. However, separating the annotation process from the spectrum renderer is amenable toward a more stable platform for spectral annotation as the components can be maintained and implemented independently.
      Here we present the Interactive Peptide Spectra Annotator (IPSA) to provide a standalone web platform for annotation and interpretation of peptide tandem mass spectra independent of instrumental platform, identification pipeline, and peptide fragmentation technique. IPSA provides flexibility to annotate spectra containing any of the six common peptide fragment ion types. Importantly, it can export annotated data in a tabular format, which enables the rapid culmination of fragment ion statistics for individual or multiple peptide tandem mass spectra, a useful tool in a wide range of proteomic experiments. We have also built in compatibility with spectra collected in the negative mode, providing a much-needed resource for the continued development of negative-mode proteomic approaches. Further, IPSA offers a platform for the generation and exportation of figure-ready annotated spectra in an editable format. In all, IPSA expands spectral annotation capabilities to all types of shotgun proteomic data regardless of how data was collected or processed.

      DISCUSSION

      Modern MS-based proteomics techniques are widely used to identify and characterize tens of thousands of peptides and proteins originating from a variety of biological samples. The annotation of the tandem mass spectra used to identify these species is an arduous task requiring extensive expertise. Our web-based and open-source peptide spectral annotator, IPSA, provides a resource for generating and investigating annotated spectra for peptide identifications to a wide research community. IPSA can generate customizable annotated peptide spectra using a clean and intuitive user interface, allowing researchers to export customizable, publication-ready annotated spectra as vector graphics to aid in figure creation. It can process MS/MS spectra from both anionic and cationic precursors, and it has built-in support to annotate fragment ions generated from a diverse assortment of dissociative techniques. Additionally, IPSA can extract fragment ion statistics from any number of peptide spectra and return results in a tabular format, giving researchers a deeper and more comprehensive view of their peptide analyses.
      We chose to develop IPSA as an online platform to reach a wide audience of proteomics researchers: those with an Internet connection on a computer with a web browser. Web-based software also allowed us to use the flexibility of the well-established JavaScript visualization library D3.js while avoiding software compatibility issues and version control. Through IPSA, we aim to increase the approachability of spectral annotation to proteomics novices and experts alike.
      The IPSA source code is freely available for inspection and download at https://github.com/coongroup/IPSA alongside additional guides regarding software usage. We recommend using an updated web browser to access IPSA at http://interactivepeptidespectralannotator.com as outdated browsers may not provide support for critical functions. IPSA can be easily installed on a private desktop or server using a prebuilt Docker image and instructions at https://hub.docker.com/r/dbrademan/ipsa, or IPSA's project files can be manually configured to operate on private web servers with full functionality. Additionally, the JavaScript file used to render the interactive visualization, IPSA.js, is configured to be used as an AngularJS directive. This directive can be attached to custom annotation scripts in many website environments, allowing the use of our software beyond that of the platform we described here.

      DATA AVAILABILITY

      Raw spectral data, peptide identifications, and protein databases have been deposited to the ProteomeXchange Consortium via the PRIDE (
      • Vizcaíno J.A.
      • Csordas A.
      • del-Toro N.
      • Dianes J.A.
      • Griss J.
      • Lavidas I.
      • Mayer G.
      • Perez-Riverol Y.
      • Reisinger F.
      • Ternent T.
      • Xu Q.-W.
      • Wang R.
      • Hermjakob H.
      2016 update of the PRIDE database and its related tools.
      ) partner repository with the dataset identifier PXD011695.

      Acknowledgments

      We thank Kevin Schauer for providing feedback during IPSA's design.

      REFERENCES

        • Hebert A.S.
        • Richards A.L.
        • Bailey D.J.
        • Ulbrich A.
        • Coughlin E.E.
        • Westphall M.S.
        • Coon J.J.
        The One Hour Yeast Proteome.
        Mol. Cell Proteomics. 2014; 13: 339-347
        • Richards A.L.
        • Hebert A.S.
        • Ulbrich A.
        • Bailey D.J.
        • Coughlin E.E.
        • Westphall M.S.
        • Coon J.J.
        One-hour proteome analysis in yeast.
        Nat. Protoc. 2015; 10: 701-714
        • Senko M.W.
        • Remes P.M.
        • Canterbury J.D.
        • Mathur R.
        • Song Q.
        • Eliuk S.M.
        • Mullen C.
        • Earley L.
        • Hardman M.
        • Blethrow J.D.
        • Bui H.
        • Specht A.
        • Lange O.
        • Denisov E.
        • Makarov A.
        • Horning S.
        • Zabrouskov V.
        Novel parallelized quadrupole/linear ion trap/orbitrap tribrid mass spectrometer improving proteome coverage and peptide identification rates.
        Anal. Chem. 2013; 85: 11710-11714
        • Richards A.L.
        • Merrill A.E.
        • Coon J.J.
        Proteome sequencing goes deep.
        Curr. Opin. Chem. Biol. 2015; 24: 11-17
        • Hebert A.S.
        • Thöing C.
        • Riley N.M.
        • Kwiecien N.W.
        • Shiskova E.
        • Huguet R.
        • Cardasis H.L.
        • Kuehn A.
        • Eliuk S.
        • Zabrouskov V.
        • Westphall M.S.
        • McAlister G.C.
        • Coon J.J.
        Improved precursor characterization for data-dependent mass spectrometry.
        Anal. Chem. 2018; 90: 2333-2340
        • Scheltema R.A.
        • Hauschild J.-P.
        • Lange O.
        • Hornburg D.
        • Denisov E.
        • Damoc E.
        • Kuehn A.
        • Makarov A.
        • Mann M.
        The Q exactive HF, a benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field orbitrap analyzer.
        Mol. Cell Proteomics. 2014; 13: 3698-3708
        • Kelstrup C.D.
        • Bekker-Jensen D.B.
        • Arrey T.N.
        • Hogrebe A.
        • Harder A.
        • Olsen J.V.
        Performance evaluation of the Q exactive HF-X for shotgun proteomics.
        J. Proteome Res. 2018; 17: 727-738
        • Bekker-Jensen D.B.
        • Kelstrup C.D.
        • Batth T.S.
        • Larsen S.C.
        • Haldrup C.
        • Bramsen J.B.
        • Sørensen K.D.
        • Høyer S.
        • Ørntoft T.F.
        • Andersen C.L.
        • Nielsen M.L.
        • Olsen J.V.
        An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.
        Cell Syst. 2017; 4: 587-599.e4
        • Shishkova E.
        • Hebert A.S.
        • Coon J.J.
        Now, more than ever, proteomics needs better chromatography.
        Cell Syst. 2016; 3: 321-324
        • Eng J.K.
        • Mccormack A.L.
        • Yates J.R.
        An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.
        Am. Soc. Mass Spectrom. 1994; 5: 976-989
        • Cox J.
        • Mann M.
        MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.
        Nat. Biotechnol. 2008; 26: 1367-1372
        • Perkins D.N.
        • Pappin D.J. C.C.
        • Creasy D.M.
        • Cottrell J.S.
        Probability-based protein identification by searching sequence databases using mass spectrometry data.
        Electrophoresis. 1999; 20: 3551-3567
        • Taylor J.A.
        • Johnson R.S.
        Sequence database searches via de Novo peptide sequencing by tandem mass spectrometry.
        Rapid Commun. Mass Spectrom. 1997; 11: 1067-1075
        • Ma B.
        • Zhang K.
        • Hendrie C.
        • Liang C.
        • Li M.
        • Doherty-Kirby A.
        • Lajoie G.
        PEAKS: Powerful software for peptide de novo sequencing by tandem mass spectrometry.
        Rapid Commun. Mass Spectrom. 2003; 17: 2337-2342
        • Chi H.
        • Sun R.X.
        • Yang B.
        • Song C.Q.
        • Wang L.H.
        • Liu C.
        • Fu Y.
        • Yuan Z.F.
        • Wang H.P.
        • He S.M.
        • Dong M.Q.
        PNovo: De novo peptide sequencing and identification using HCD spectra.
        J. Proteome Res. 2010; 9: 2713-2724
        • Sinitcyn P.
        • Daniel Rudolph J.
        • Cox J.
        • Rudolph J.D.
        • Cox J.
        Computational methods for understanding mass spectrometry–based shotgun proteomics data.
        Annu. Rev. Biomed. Data Sci. 2018; 1 (annurev-biodatasci-080917-013516)
        • Bradshaw R.A.
        • Burlingame A.L.
        • Carr S.
        • Aebersold R.
        Reporting protein identification data: the next generation of guidelines.
        Mol. Cell Proteomics. 2006; 5: 787-788
        • Jones A.R.
        • Eisenacher M.
        • Mayer G.
        • Kohlbacher O.
        • Siepen J.
        • Hubbard S.J.
        • Selley J.N.
        • Searle B.C.
        • Shofstahl J.
        • Seymour S.L.
        • Julian R.
        • Binz P.-A.
        • Deutsch E.W.
        • Hermjakob H.
        • Reisinger F.
        • Griss J.
        • Vizcaíno J.A.
        • Chambers M.
        • Pizarro A.
        • Creasy D.
        The mzIdentML data standard for mass spectrometry-based proteomics results.
        Mol. Cell Proteomics. 2012; 11 (M111.014381)
        • Seymour S.L.
        • Farrah T.
        • Binz P.A.
        • Chalkley R.J.
        • Cottrell J.S.
        • Searle B.C.
        • Tabb D.L.
        • Vizcaíno J.A.
        • Prieto G.
        • Uszkoreit J.
        • Eisenacher M.
        • Martínez-Bartolomé S.
        • Ghali F.
        • Jones A.R.
        A standardized framing for reporting protein identifications in mzIdentML 1.2.
        Proteomics. 2014; 14: 2389-2399
        • Burlingame A.
        • Carr S.A.
        • Bradshaw R.A.
        • Chalkley R.J.
        On credibility, clarity, and compliance.
        Mol. Cell Proteomics. 2015; 14: 1731-1733
        • Baker P.R.
        • Chalkley R.J.
        MS-viewer: a web-based spectral viewer for proteomics results.
        Mol. Cell Proteomics. 2014; 13: 1392-1396
        • Strohalm M.
        • Hassman M.
        • Košata B.
        • Kodíček M.
        mMass data miner: An open source alternative for mass spectrometric data analysis.
        Rapid Commun. Mass Spectrom. 2008; 22: 905-908
        • Colinge J.
        • Masselot A.
        • Carbonell P.
        • Appel R.D.
        InSilicoSpectro: An open-source proteomics library.
        J. Proteome Res. 2006; 5: 619-624
        • Sharma V.
        • Eng J.K.
        • Maccoss M.J.
        • Riffle M.
        A mass spectrometry proteomics data management platform.
        Mol. Cell Proteomics. 2012; 11: 824-831
        • Riffle M.
        • Jaschob D.
        • Zelter A.
        • Davis T.N.
        ProXL (Protein Cross-Linking Database): A platform for analysis, visualization, and sharing of protein cross-linking mass spectrometry data.
        J. Proteome Res. 2016; 15: 2863-2870
        • Perez-Riverol Y.
        • Alpi E.
        • Wang R.
        • Hermjakob H.
        • Vizcaíno J.A.
        Making proteomics data accessible and reusable: Current state of proteomics databases and repositories.
        Proteomics. 2015; 15: 930-950
        • Riffle M.
        • Merrihew G.E.
        • Jaschob D.
        • Sharma V.
        • Davis T.N.
        • Noble W.S.
        • MacCoss M.J.
        Visualization and dissemination of multidimensional proteomics data comparing protein abundance during Caenorhabditis elegans development.
        J. Am. Soc. Mass Spectrom. 2015; 26: 1827-1836
        • Ly T.
        • Julian R.R.
        Ultraviolet photodissociation: developments towards applications for mass-spectrometry-based proteomics.
        Angew. Chemie - Int. Ed. 2009; 48: 7130-7137
        • Yu Q.
        • Wang B.
        • Chen Z.
        • Urabe G.
        • Glover M.S.
        • Shi X.
        • Guo L.W.
        • Kent K.C.
        • Li L.
        Electron-transfer/higher-energy collision dissociation (EThcD)-enabled intact glycopeptide/glycoproteome characterization.
        J. Am. Soc. Mass Spectrom. 2017; 28: 1751-1764
        • Ledvina A.R.
        • Beauchene N.A.
        • McAlister G.C.
        • Syka J.E.P.
        • Schwartz J.C.
        • Griep-Raming J.
        • Westphall M.S.
        • Coon J.J.
        Activated-ion electron transfer dissociation improves the ability of electron transfer dissociation to identify peptides in a complex mixture.
        Anal. Chem. 2010; 82: 10068-10074
        • Bostock M.
        • Ogievetsky V.
        • Heer J.
        D3 data-driven documents.
        IEEE Trans. Vis. Comput. Graph. 2011; 17: 2301-2309
        • Geer L.Y.
        • Markey S.P.
        • Kowalak J.A.
        • Wagner L.
        • Xu M.
        • Maynard D.M.
        • Yang X.
        • Shi W.
        • Bryant S.H.
        Open mass spectrometry search algorithm.
        J. Proteome Res. 2004; 3: 958-964
        • Wenger C.D.
        • Phanstiel D.H.
        • Lee M.V.
        • Bailey D.J.
        • Coon J.J.
        COMPASS: A suite of pre- and post-search proteomics software tools for OMSSA.
        Proteomics. 2011; 11: 1064-1074
        • Riley N.M.
        • Westphall M.S.
        • Hebert A.S.
        • Coon J.J.
        Implementation of activated ion electron transfer dissociation on a quadrupole-orbitrap-linear ion trap hybrid mass spectrometer.
        Anal. Chem. 2017; 89: 6358-6366
        • Riley N.M.
        • Rush M.J.P.
        • Rose C.M.
        • Richards A.L.
        • Kwiecien N.W.
        • Bailey D.J.
        • Hebert A.S.
        • Westphall M.S.
        • Coon J.J.
        The negative mode proteome with activated ion negative electron transfer dissociation (AI-NETD).
        Mol. Cell Proteomics. 2015; 14: 2644-2660
        • Roepstorff P.
        • Fohlman J.
        Letter to the editors.
        Biol. Mass Spectrom. 1984; 11: 601
        • Johnson R.S.
        • Martin S.A.
        • Biemann K.
        • Stults J.T.
        • Watson J.T.
        Novel fragmentation process of peptides by collision-induced decomposition in a tandem mass spectrometer: differentiation of leucine and isoleucine.
        Anal. Chem. 1987; 59: 2621-2625
        • Griss J.
        • Jones A.R.
        • Sachsenberg T.
        • Walzer M.
        • Gatto L.
        • Hartler J.
        • Thallinger G.G.
        • Salek R.M.
        • Steinbeck C.
        • Neuhauser N.
        • Cox J.
        • Neumann S.
        • Fan J.
        • Reisinger F.
        • Xu Q.-W.
        • Del Toro N.
        • Pérez-Riverol Y.
        • Ghali F.
        • Bandeira N.
        • Xenarios I.
        • Kohlbacher O.
        • Vizcaíno J.A.
        • Hermjakob H.
        The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.
        Mol. Cell Proteomics. 2014; 13: 2765-2775
        • Martens L.
        • Chambers M.
        • Sturm M.
        • Kessner D.
        • Levander F.
        • Shofstahl J.
        • Tang W.H.
        • Römpp A.
        • Neumann S.
        • Pizarro A.D.
        • Montecchi-Palazzi L.
        • Tasman N.
        • Coleman M.
        • Reisinger F.
        • Souda P.
        • Hermjakob H.
        • Binz P.-A.
        • Deutsch E.W.
        mzML—a community standard for mass spectrometry data.
        Mol. Cell Proteomics. 2011; 10 (R110.000133)
        • Chambers M.C.
        • Maclean B.
        • Burke R.
        • Amode D.
        • Ruderman D.L.
        • Neumann S.
        • Gatto L.
        • Fischer B.
        • Pratt B.
        • Egertson J.
        • Hoff K.
        • Kessner D.
        • Tasman N.
        • Shulman N.
        • Frewen B.
        • Baker T.A.
        • Brusniak M.-Y.
        • Paulse C.
        • Creasy D.
        • Flashner L.
        • Kani K.
        • Moulding C.
        • Seymour S.L.
        • Nuwaysir L.M.
        • Lefebvre B.
        • Kuhlmann F.
        • Roark J.
        • Rainer P.
        • Detlev S.
        • Hemenway T.
        • Huhmer A.
        • Langridge J.
        • Connolly B.
        • Chadick T.
        • Holly K.
        • Eckels J.
        • Deutsch E.W.
        • Moritz R.L.
        • Katz J.E.
        • Agus D.B.
        • MacCoss M.
        • Tabb D.L.
        • Mallick P.
        A cross-platform toolkit for mass spectrometry and proteomics.
        Nat. Biotechnol. 2012; 30
        • McAlister G.C.
        • Russell J.D.
        • Rumachik N.G.
        • Hebert A.S.
        • Syka J.E.P.
        • Geer L.Y.
        • Westphall M.S.
        • Pagliarini D.J.
        • Coon J.J.
        Analysis of the acidic proteome with negative electron-transfer dissociation mass spectrometry.
        Anal. Chem. 2012; 84: 2875-2882
        • Rumachik N.G.
        • McAlister G.C.
        • Russell J.D.
        • Bailey D.J.
        • Wenger C.D.
        • Coon J.J.
        Characterizing peptide neutral losses induced by negative electron-transfer dissociation (NETD).
        J. Am. Soc. Mass Spectrom. 2012; 23: 718-727
        • Madsen J.A.
        • Xu H.
        • Robinson M.R.
        • Horton A.P.
        • Shaw J.B.
        • Giles D.K.
        • Kaoud T.S.
        • Dalby K.N.
        • Trent M.S.
        • Brodbelt J.S.
        High-throughput database search and large-scale negative polarity liquid chromatography–tandem mass spectrometry with ultraviolet photodissociation for complex proteomic samples.
        Mol. Cell Proteomics. 2013; 12: 2604-2614
        • Ewing N.P.
        • Cassady C.J.
        Dissociation of multiply charged negative ions for hirudin (54–65), fibrinopeptide B, and insulin A (oxidized).
        J. Am. Soc. Mass Spectrom. 2001; 12: 105-116
        • Vizcaíno J.A.
        • Csordas A.
        • del-Toro N.
        • Dianes J.A.
        • Griss J.
        • Lavidas I.
        • Mayer G.
        • Perez-Riverol Y.
        • Reisinger F.
        • Ternent T.
        • Xu Q.-W.
        • Wang R.
        • Hermjakob H.
        2016 update of the PRIDE database and its related tools.
        Nucleic Acids Res. 2016; 44: D447-D456