LFQProfiler and RNPxl: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer
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- 作者：Johannes Veit ; Timo Sachsenberg ; Aleksandar Chernev ; Fabian Aicheler ; Henning Urlaub ; Oliver Kohlbacher
- 刊名：Journal of Proteome Research
- 出版年：2016
- 出版时间：September 2, 2016
- 年：2016
- 卷：15
- 期：9
- 页码：3441-3448
- 全文大小：436K
- 年卷期：0
- ISSN：1535-3907
文摘
Modern mass spectrometry setups used in today’s proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNPxl for UV-induced peptide–RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark (Ramus, C.; J. Proteomics 2016, 132, 51– 62). The second workflow, RNPxl, represents the first software solution to date for identification of peptide–RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.