Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

By Eric W. Deutsch, Luis Mendoza, David D. Shteynberg, J. Slagel, Zhi Sun, Rob Moritz. PROTEOMICS - Clinical Applications, 2015

308 citations recorded by the source corpus.

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.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2b2eaf0a473ebaf5e4250abb7efb34d4b2265dc6

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Citations in the corpus

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma (2019, methodology): “In the case of the phosphopeptide-enriched dataset, PeptideProphet files were additionally processed using PTMProphet (Deutsch et al., 2015) to localize the phosphorylation sites.”
2016 update of the PRIDE database and its related tools (2015, methodology): “PeptideAtlas is a secondary resource, focused on the reanalysis of tandem MS data sets using their inhouse Trans Proteomic Pipeline (9).”
The Perseus computational platform for comprehensive analysis of (prote)omics data (2016, unknown): “Protein HCT116 5/4 (10) m R N A H C T 11 6 5/ 4 (1 0 – 1 )”