Journal
NATURE METHODS
Volume 13, Issue 9, Pages 777-783Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.3954
Keywords
-
Categories
Funding
- SyBIT project of SystemsX.ch
- ETH Zurich [ETH-30 11-2]
- Swiss National Science Foundation (SNSF) [P2EZP3_162268, 31003A_166435]
- ERC [233226, 670821]
- PhosphonetX project of SystemsX.ch
- ERC DISEASEAVATARS [616441]
- Telethon Foundation [GGP14265]
- Regione Lombardia
- Fondazione Umberto Veronesi
- Swiss National Science Foundation (SNF) [P2EZP3_162268] Funding Source: Swiss National Science Foundation (SNF)
- European Research Council (ERC) [616441, 670821] Funding Source: European Research Council (ERC)
Ask authors/readers for more resources
Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available