Trans‐Proteomic Pipeline, a standardized data processing pipeline for large‐scale reproducible proteomics informatics
Open accessAbstract
Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans‐Proteomics Pipeline (TPP) is a robust open‐source standardized data processing pipeline for large‐scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features.
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The HPP routinely applies high-stringency protein inference analytics generated through the Trans-Proteomic Pipeline.
“The HPP routinely applies high-stringency protein inference analytics10, generated through the Trans-Proteomic Pipeline11.”
From A high-stringency blueprint of the human proteome (2020) · cites this paper as [11]
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Cites
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855 · see citing works
UniProt: the Universal Protein knowledgebase
Apweiler, R. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh131 · Cited by 7,535 · see citing works
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574 · see citing works
Keller, A., Nesvizhskii, A., Kolker, E., & Aebersold, R. (2002) · Analytical Chemistry · doi:10.1021/ac025747h · Cited by 4,970 · see citing works
A statistical model for identifying proteins by tandem mass spectrometry.
Nesvizhskii, A., Keller, A., Kolker, E., & Aebersold, R. (2003) · Analytical Chemistry · doi:10.1021/ac0341261 · Cited by 4,902 · see citing works
Skyline: an open source document editor for creating and analyzing targeted proteomics experiments
MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., & MacCoss, M. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq054 · Cited by 4,697 · see citing works
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683 · see citing works
A cross-platform toolkit for mass spectrometry and proteomics
Chambers, M., MacLean, B., Burke, R., Amodei, D., Ruderman, D., Neumann, S., Gatto, L., Fischer, B., Pratt, B. S., Egertson, J. D., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2377 · Cited by 4,042 · see citing works
Self-citationGillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877 · see citing works
ProteomeXchange provides globally coordinated proteomics data submission and dissemination
Vizcaíno, J. A., Deutsch, E. W., Wang, R., Csordás, A., Reisinger, F., Ríos, D., Dianes, J. A., Sun, Z., Farrah, T., Bandeira, N., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2839 · Cited by 2,735 · see citing works
Self-citationTANDEM: matching proteins with tandem mass spectra
Craig, R., & Beavis, R. C. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth092 · Cited by 2,553 · see citing works
ProteoWizard: open source software for rapid proteomics tools development
Kessner, D., Chambers, M., Burke, R., Agus, D., & Mallick, P. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn323 · Cited by 2,024 · see citing works
Comet: An open‐source <scp>MS</scp> / <scp>MS</scp> sequence database search tool
Eng, J. K., Jahan, T. A., & Hoopmann, M. R. (2013) · PROTEOMICS · doi:10.1002/pmic.201200439 · Cited by 1,474 · see citing works
Proteogenomic characterization of human colon and rectal cancer
CPTAC, T. N., Zhang, B., Wang, J., Wang, X., Zhu, J., Liu, Q., Shi, Z., Chambers, M. C., Zimmerman, L. J., Shaddox, K. F., et al. (2014) · Nature · doi:10.1038/nature13438 · Cited by 1,462 · see citing works
mzML—a Community Standard for Mass Spectrometry Data
Martens, L., Chambers, M., Sturm, M., Kessner, D., Levander, F., Shofstahl, J., Tang, W. H., Römpp, A., Neumann, S., Pizarro, A., et al. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r110.000133 · Cited by 754 · see citing works
Self-citationA guided tour of the Trans‐Proteomic Pipeline
Deutsch, E. W., Mendoza, L., Shteynberg, D. D., Farrah, T., Lam, H., Tasman, N., Sun, Z., Nilsson, E. J., Pratt, B. S., Prazen, B. J., et al. (2010) · PROTEOMICS · doi:10.1002/pmic.200900375 · Cited by 746 · see citing works
Self-citationOpen Source System for Analyzing, Validating, and Storing Protein Identification Data
Craig, R., Cortens, J. P., & Beavis, R. C. (2004) · Journal of Proteome Research · doi:10.1021/pr049882h · Cited by 696 · see citing works
A uniform proteomics MS/MS analysis platform utilizing open XML file formats
Keller, A., Eng, J. K., Zhang, N., Li, X., & Aebersold, R. H. (2005) · Molecular Systems Biology · doi:10.1038/msb4100024 · Cited by 692 · see citing works
Wolstencroft, K., Haines, R., Fellows, D. K., Williams, A. R., Withers, D., Owen, S., Soiland‐Reyes, S., Dunlop, I., Nenadić, A., Fisher, P., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt328 · Cited by 671 · see citing works
Shteynberg, D. D., Deutsch, E. W., Lam, H., Eng, J. K., Sun, Z., Tasman, N., Mendoza, L., Moritz, R. L., Aebersold, R. H., & Nesvizhskii, A. I. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.007690 · Cited by 548 · see citing works
Self-citationPeptideAtlas: a resource for target selection for emerging targeted proteomics workflows
Deutsch, E. W., Lam, H., & Aebersold, R. H. (2008) · EMBO Reports · doi:10.1038/embor.2008.56 · Cited by 541 · see citing works
Self-citationNesvizhskii, A. I. (2010) · Journal of Proteomics · doi:10.1016/j.jprot.2010.08.009 · Cited by 535 · see citing works
mProphet: automated data processing and statistical validation for large-scale SRM experiments
Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Brusniak, M.-Y., Hengartner, M. O., & Aebersold, R. (2011) · Nature Methods · doi:10.1038/nmeth.1584 · Cited by 532 · see citing works
Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., King, N., Stein, S. E., & Aebersold, R. (2007) · PROTEOMICS · doi:10.1002/pmic.200600625 · Cited by 517 · see citing works
Self-citationA perspective on the use of iTRAQTM reagent technology for protein complex and profiling studies
Zieske, L. R. (2006) · Journal of Experimental Botany · doi:10.1093/jxb/erj168 · Cited by 468 · see citing works
A High-Confidence Human Plasma Proteome Reference Set with Estimated Concentrations in PeptideAtlas
Farrah, T., Deutsch, E. W., Omenn, G. S., Campbell, D. S., Sun, Z., Bletz, J., Mallick, P., Katz, J. E., Malmström, J. A., Ossola, R., et al. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m110.006353 · Cited by 446 · see citing works
Self-citationLi, X., Zhang, H., Ranish, J. A., & Aebersold, R. H. (2003) · Analytical Chemistry · doi:10.1021/ac034633i · Cited by 342 · see citing works
Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900317-mcp200 · Cited by 312 · see citing works
Ellis, M. J., Gillette, M. A., Carr, S. A., Paulovich, A. G., Smith, R. D., Rodland, K., Townsend, R. R., Kinsinger, C. R., Mesri, M., Rodriguez, H., et al. (2013) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0219 · Cited by 311 · see citing works
TOPP—the OpenMS proteomics pipeline
Kohlbacher, O., Reinert, K., Gröpl, C., Lange, E., Pfeifer, N., Schulz-Trieglaff, O. B., & Sturm, M. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btl299 · Cited by 281 · see citing works
Building consensus spectral libraries for peptide identification in proteomics
Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., Stein, S. E., & Aebersold, R. H. (2008) · Nature Methods · doi:10.1038/nmeth.1254 · Cited by 265 · see citing works
Self-citationRauch, A., Bellew, M., Eng, J. K., et al. (2005) · Journal of Proteome Research · doi:10.1021/pr0503533 · Cited by 215 · see citing works
MacLean, B., Eng, J. K., Beavis, R. C., & McIntosh, M. W. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl379 · Cited by 210 · see citing works
The mzIdentML Data Standard for Mass Spectrometry-Based Proteomics Results
Jones, A. R., Eisenacher, M., Mayer, G., Kohlbacher, O., Siepen, J. A., Hubbard, S. J., Selley, J. N., Searle, B. C., Shofstahl, J. H., Seymour, S. L., et al. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.014381 · Cited by 200 · see citing works
Self-citationA Blood-Based Proteomic Classifier for the Molecular Characterization of Pulmonary Nodules
Li, X., Hayward, C., Fong, P.-Y., Dominguez, M., Hunsucker, S. W., Lee, L. W., McLean, M. A., Law, S. M., Butler, H., Schirm, M., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3007013 · Cited by 192 · see citing works
A Face in the Crowd: Recognizing Peptides Through Database Search
Eng, J. K., Searle, B. C., Clauser, K. R., & Tabb, D. L. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r111.009522 · Cited by 187 · see citing works
Griss, J., Jones, A. R., Sachsenberg, T. T., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o113.036681 · Cited by 154 · see citing works
Data analysis and bioinformatics tools for tandem mass spectrometry in proteomics
Deutsch, E. W., Lam, H., & Aebersold, R. H. (2008) · Physiological Genomics · doi:10.1152/physiolgenomics.00298.2007 · Cited by 154 · see citing works
Self-citationThe State of the Human Proteome in 2012 as Viewed through PeptideAtlas
Farrah, T., Deutsch, E. W., Hoopmann, M. R., Hallows, J. L., Sun, Z., Huang, C., & Moritz, R. L. (2012) · Journal of Proteome Research · doi:10.1021/pr301012j · Cited by 120 · see citing works
Self-citationPedrioli, P. G. A., Raught, B., Zhang, X. D., Rogers, R. S., Aitchison, J. D., Matunis, M. J., & Aebersold, R. H. (2006) · Nature Methods · doi:10.1038/nmeth891 · Cited by 120 · see citing works
File Formats Commonly Used in Mass Spectrometry Proteomics
Deutsch, E. W. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r112.019695 · Cited by 102 · see citing works
Self-citationShotgun‐proteomics‐based clinical testing for diagnosis and classification of amyloidosis
Theis, J. D., Dasari, S., Vrana, J. A., Kurtin, P. J., & Doǧan, A. (2013) · Journal of Mass Spectrometry · doi:10.1002/jms.3264 · Cited by 84 · see citing works
The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics
Walzer, M., Qi, D., Mayer, G., et al. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o113.028506 · Cited by 75 · see citing works
The Effect of Using an Inappropriate Protein Database for Proteomic Data Analysis
Knudsen, G. M., & Chalkley, R. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020873 · Cited by 61 · see citing works
PRIDE Cluster: building a consensus of proteomics data
Griss, J., Foster, J. M., Hermjakob, H., & Vizcaíno, J. A. (2013) · Nature Methods · doi:10.1038/nmeth.2343 · Cited by 57 · see citing works
Deutsch, E. W., Albar, J. P., Binz, P., Eisenacher, M., Jones, A. R., Mayer, G., Omenn, G. S., Orchard, S. E., Vizcaíno, J. A., & Hermjakob, H. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv001 · Cited by 56 · see citing works
Self-citationBoja, E. S., Fehniger, T. E., Baker, M. S., Marko‐Varga, G., & Rodriguez, H. (2014) · Journal of Proteome Research · doi:10.1021/pr500753r · Cited by 54 · see citing works
SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology
Marzolf, B., Deutsch, E. W., Moss, P., et al. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-286 · Cited by 53 · see citing works
Self-citationCloud CPFP: A Shotgun Proteomics Data Analysis Pipeline Using Cloud and High Performance Computing
Trudgian, D. C., & Mirzaei, H. (2012) · Journal of Proteome Research · doi:10.1021/pr300694b · Cited by 51 · see citing works
YPED: A Web-Accessible Database System for Protein Expression Analysis
Shifman, M. A., Li, Y., Colangelo, C. M., Stone, K. L., WU, T. L., Cheung, K., Miller, P. L., & Williams, K. R. (2007) · Journal of Proteome Research · doi:10.1021/pr070325f · Cited by 37 · see citing works
Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline
Slagel, J., Mendoza, L., Shteynberg, D. D., Deutsch, E. W., & Moritz, R. L. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.043380 · Cited by 22 · see citing works
Self-citationRegulatory Considerations for Clinical Mass Spectrometry: Multiple Reaction Monitoring
Boja, E. S., & Rodriguez, H. (2011) · Clinics in Laboratory Medicine · doi:10.1016/j.cll.2011.07.001 · Cited by 4 · see citing works
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- Authors
- Deutsch, E. W., Mendoza, L., Shteynberg, D., Slagel, J., Sun, Z., & Moritz, R. L.
- Affiliations
- Institute for Systems Biology (US)
- Corresponding author
- Deutsch, Eric W.
- Venue
- PROTEOMICS – Clinical Applications
- Publisher
- Wiley
- Published
- 2015-04-02
- Volume
- 9
- Issue
- 7-8
- Pages
- 745-754
- ISSN
- 1862-8346 (ISSN-L)
- 1862-8354
- PMC
- PMC4506239
- OpenAlex
- W2091377998
- Cited by
- 342
- References
- 53
- Citations by year
- 2026: 4 · 2025: 14 · 2024: 22 · 2023: 35 · 2022: 49 · 2021: 49 · 2020: 39 · 2019: 29 · 2018: 37 · 2017: 19 · 2016: 24 · 2015: 20
- FWCI
- 3.18
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- PROTEOMICS - CLINICAL APPLICATIONS (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health from the NHGRI (RC2 HG005805)
- NIGMS (R01 GM087221 and 2P50 GM076547)
- National Institute of Biomedical Imaging and Bioengineering (U54EB020406)
- National Science Foundation MRI (0923536)
- ProteomeXchange” (260558)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- open source software, proteomics workflow, data visualization, cloud computing
- MeSH terms
- Humans, Software, Statistics as Topic, Reproducibility of Results, Computational Biology, Proteome, Proteomics
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