Abstract
Label-free quantification has grown in popularity as a means of obtaining relative abundance measures for proteomics experiments. However, easily accessible and integrated tools to perform label-free quantification have been lacking. We describe StPeter, an implementation of Normalized Spectral Index quantification for wide availability through integration into the widely used Trans-Proteomic Pipeline. This implementation has been specifically designed for reproducibility and ease of use. We demonstrate that StPeter outperforms other state-of-the art packages using a recently reported benchmark data set over the range of false discovery rates relevant to shotgun proteomics results. We also demonstrate that the software is computationally efficient and supports data from a variety of instrument platforms and experimental designs. Results can be viewed within the Trans-Proteomic Pipeline graphical user interfaces and exported in standard formats for downstream statistical analysis. By integrating StPeter into the freely available Trans-Proteomic Pipeline, users can now obtain high-quality label-free quantification of any data set in seconds by adding a single command to the workflow.
| Original language | English |
|---|---|
| Pages (from-to) | 1314-1320 |
| Number of pages | 7 |
| Journal | Journal of Proteome Research |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2 2018 |
Keywords
- automation
- data analysis pipeline
- label-free quantification
- open-source software
- quantitative proteomics
- trans-proteomic pipeline
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