StPeter: Seamless Label-Free Quantification with the Trans-Proteomic Pipeline.
Document Type
Article
Publication Date
3-2-2018
Keywords
Animals; Benchmarking; Computer Graphics; Databases, Protein; Datasets as Topic; Escherichia coli; Humans; Internet; Mass Spectrometry; Proteomics; User-Computer Interface; automation; data analysis pipeline; label-free quantification; open-source software; quantitative proteomics; trans-proteomic pipeline
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.
Specialty/Research Institute
Institute for Systems Biology
