TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.
| Type | Information |
|---|---|
| Nr | 57 (Research article) |
| Authors | Röst, Hannes; Liu, Yansheng; DAgostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi |
| Title | TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics. |
| Journal | Nat Methods (2016) 13(9) 777-83 |
| DOI | 10.1038/nmeth.3954 |
| Citations | 184 citations (journal impact: 25.06) |
| Abstract | 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-MSMS 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 httpproteomics.ethz.chtric 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. |