| Literature DB >> 29400476 |
Michael R Hoopmann1, Jason M Winget1, Luis Mendoza1, Robert L Moritz1.
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.Entities:
Keywords: automation; data analysis pipeline; label-free quantification; open-source software; quantitative proteomics; trans-proteomic pipeline
Mesh:
Year: 2018 PMID: 29400476 PMCID: PMC5891225 DOI: 10.1021/acs.jproteome.7b00786
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466