In the field of quantitative proteomics, an extensive number of different methods have been developed including differential labelling, label-free and isotope covalent tags such as iTRAQ.
The challenge of developing software to cover the main quantitative methods, and support diverse instruments and search engines, involves significant effort. Lab scientists are presented with a bewildering array of different software packages, both open source and commercial, generally each supporting only one or two workflows.
Our consortium is aimed with a longer term vision of building maintainable software, based on the Human Proteome Standards Initiative (HUPO-PSI) standard data formats, containing cutting edge algorithms and an intuitive graphical user interface.
The aim of this project is to develop an open source framework for the analysis of quantitative proteomics data by providing a user-friendly application, using open community standards and facilitating the deposition of data into public repositories. The development of this software includes:
- Development and Integration of Quantitation Tools
- Support of HUPO Proteome Standards Initiative standards
- Statistical Analysis Toolkit
- Provision of high-quality identification data, through advanced statistical methods
- A variety of protein inference algorithms
- Comparative output from different algorithms
- Development of a Common Graphical Unit Interface
- Deposition of data into public repositories
- Reanalysis of deposited data
(For more details see our Development section)