期刊
JOURNAL OF PROTEOME RESEARCH
卷 17, 期 3, 页码 1314-1320出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.7b00786
关键词
label-free quantification; open-source software; quantitative proteomics; data analysis pipeline; automation; trans-proteomic pipeline
资金
- National Institutes of Health from the National Institute of General Medical Sciences [2P50 GM076547/Center for Systems Biology, R01 GM087221]
- National Heart, Lung and Blood Institute [R01 HL133135]
- Procter Gamble, Inc.
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.
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