Abstract

The Trans-Proteomic Pipeline (TPP) is a complete, free, and widely-adopted suite of tools for the analysis of tandem mass spectrometry (MS/MS) proteomics data (""""""""shotgun proteomics""""""""). The TPP is used for analyzing raw MS/MS data to identify and quantify proteins and their abundance levels in cells and tissues, allowing investigation of research questions surrounding the identification of causes of disease, the production of diagnostic techniques, and the development of treatments. The TPP is already in use by a community of hundreds of researchers, and is of fundamental importance to many ongoing research projects. This grant will allow us to continue to maintain current functionality, support the community, and adapt to changing proteomics technology and techniques.

Public Health Relevance

Mass spectrometry based proteomics has become key to the study of many aspects of human health, it allows for the study of disease pathology, the identification of diagnostic markers and the development of treatments. The Trans Proteomics Pipeline software suite has become the cornerstone for numerous research groups who undertake mass spectrometry based experiments. This grant will enable the maintenance and evolution of this invaluable software, and enable its continued usage and expansion of its relevance throughout research institutions, hospitals, university departments and commercial organizations.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM087221-01A2
Application #
7929427
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Lyster, Peter
Project Start
2010-09-01
Project End
2013-08-31
Budget Start
2010-09-01
Budget End
2011-08-31
Support Year
1
Fiscal Year
2010
Total Cost
$589,424
Indirect Cost

  Institution

Name
Institute for Systems Biology
Department
Type
DUNS #
135646524
City
Seattle
State
WA
Country
United States
Zip Code
98109

  Publications

Shao, Wenguang; Pedrioli, Patrick G A; Wolski, Witold et al. (2018) The SysteMHC Atlas project. Nucleic Acids Res 46:D1237-D1247
Menschaert, Gerben; Wang, Xiaojing; Jones, Andrew R et al. (2018) The proBAM and proBed standard formats: enabling a seamless integration of genomics and proteomics data. Genome Biol 19:12
Zhang, Chengxin; Wei, Xiaoqiong; Omenn, Gilbert S et al. (2018) Structure and Protein Interaction-based Gene Ontology Annotations Reveal Likely Functions of Uncharacterized Proteins on Human Chromosome 17. J Proteome Res :
Lee, Joon-Yong; Choi, Hyungwon; Colangelo, Christopher M et al. (2018) ABRF Proteome Informatics Research Group (iPRG) 2016 Study: Inferring Proteoforms from Bottom-up Proteomics Data. J Biomol Tech 29:39-45
Maixner, Frank; Turaev, Dmitrij; Cazenave-Gassiot, Amaury et al. (2018) The Iceman's Last Meal Consisted of Fat, Wild Meat, and Cereals. Curr Biol 28:2348-2355.e9
Hoopmann, Michael R; Winget, Jason M; Mendoza, Luis et al. (2018) StPeter: Seamless Label-Free Quantification with the Trans-Proteomic Pipeline. J Proteome Res 17:1314-1320
Slama, Patrick; Hoopmann, Michael R; Moritz, Robert L et al. (2018) Robust determination of differential abundance in shotgun proteomics using nonparametric statistics. Mol Omics 14:424-436
Choi, Meena; Eren-Dogu, Zeynep F; Colangelo, Christopher et al. (2017) ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC-MS/MS Experiments. J Proteome Res 16:945-957
Deutsch, Eric W; Csordas, Attila; Sun, Zhi et al. (2017) The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition. Nucleic Acids Res 45:D1100-D1106
McCord, James; Sun, Zhi; Deutsch, Eric W et al. (2017) The PeptideAtlas of the Domestic Laying Hen. J Proteome Res 16:1352-1363

Showing the most recent 10 out of 80 publications