This project brings together proteomics experts and computational biologists together to learn to use the R for Proteomics package, developed in Cambridge, integrate it into analysis pipelines to serve the proteomics community in Norwich.
Proteomics is increasingly used in many research projects. While the throughput of mass spectrometers used in proteomics has increased in recent years, data processing work-flows are still a recognised bottleneck. Proteomics users struggle with large datasets. Slow algorithms and proprietary and free software often require manual intervention during data processing. That has a negative effect on reproducibility and throughput. Truly configurable tools to suit the changing requirements are rare.
Recently there has been a substantial development of R package 'R for Proteomics' (RfP) in Cambridge by L. Gatto et al. We believe that RfP is a powerful independent open source data pipeline that allows the development of customized work-flows. At the same time, it provides high quality visualization available in R, a facility mostly missing from other software packages. For this reason, it could complement our data processing and, if appropriate, become an alternative to our currently used software.
We would like to introduce the package, train ourselves and integrate it into our toolbox to serve the proteomics community in Norwich. The desired outcome should be increase in the reproducibility of data analyses and our ability to provide clearer results of protein identifications to the users in many projects we collaborate on.
We have an agreement with RfP developer to come on site and provide hands on training.
Mr Jan Sklenar,
Proteomics and Mass Spectrometry Support Specialist, The Sainsbury Laboratory, Norwich
Dr Laurent Gatto,
Senior Research Associate, Department of Biochemistry, University of Cambridge
Ms Marielle Vigouroux,
Bioinformatics Support Specialist, Department of Computational and Systems Biology, John Innes Centre, Norwich
Dr Govind Chandra,
Senior Scientist, Molecular Microbiology, John Innes Centre, Norwich
This project is due to report in 2018.