| 1. |
- Bouyssié, David, et al.
(författare)
-
WOMBAT-P : Benchmarking Label-Free Proteomics Data Analysis Workflows
-
Ingår i: Journal of Proteome Research. - 1535-3893.
-
Tidskriftsartikel (refereegranskat)abstract
- The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.
|
|
| 2. |
- Mischak, Harald, et al.
(författare)
-
Comprehensive human urine standards for comparability and standardization in clinical proteome analysis
- 2010
-
Ingår i: Proteomics - Clinical Applications. - : Wiley. - 1862-8346 .- 1862-8354. ; 4:4, s. 464-478
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well-characterized "real life" sample that can be used as reference standard in urine clinical proteomics studies. Experimental design: We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE-MS, LC-MS, LC-MS/MS, 1-D gel analysis in combination with nano-LC MS/MS (using LTQ-FT ultra), and 2-DE-MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds. Results: The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in "inter-laboratory" and "inter-platform" data comparison is also demonstrated. Conclusions and clinical relevance: These well-characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.
|
|
| 3. |
- Vizcaíno, Juan Antonio, et al.
(författare)
-
A community proposal to integrate proteomics activities in ELIXIR
- 2017
-
Ingår i: F1000Research. - : F1000 Research Ltd. - 2046-1402. ; 6
-
Tidskriftsartikel (refereegranskat)abstract
- Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.
|
|
