GRAPPA - Global compRehensive Atlas of Peptide and Protein Abundance

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The world-leading PRIDE database now contains >14,000 proteomics datasets, all of which contain raw mass spectrometry (MS) data, some contain standardised lists of protein identifications but currently none contain quantitative data expressed in a standard format. As such, there is vast untapped potential for quantitative data re-use, for the majority of research groups who do not have the capability to re-process data sets themselves.

In this project, we will develop robust open cloud-based data analysis pipelines that will be used to process 100s of publicly available datasets, using standardised data processing and normalisation protocols. All datasets will be made available within a new portal, PRIDE Quant to support computational users, and will be passed to the Expression Atlas database to provide a biologist-friendly view of the data. Data processing will largely focus on human samples for which the highest data volumes exist, including both "baseline" datasets e.g. to provide cell line or tissue/organ-level estimates of protein abundance, and "differential" expression datasets for various diseases including cancer, dementia, diabetes and major infectious diseases.

We will develop several exemplar applications of the data, including displays showing correlations between gene and protein expression for matched samples, generation of co-expression networks from proteomics data, and generating vast maps of peptide-level abundance to support new research in proteome bioinformatics.

Human proteomics data have considerable potential to support biomarker discovery efforts by pharmaceutical companies, or for example to test the distribution of particular proteins over various tissues or cell types, more broadly to support pharmaceutical industry development pipelines. Many pharmaceutical companies do not have in-house proteomics analysis capabilities, and will be able to mine any datasets they wish straightforwardly, without requiring local/specialist bioinformatics support.

Research councils and charities funding research will benefit through the potential for increased impact of the mass spectrometry (MS)-based proteomics projects they fund, thanks to the re-analysis of public proteomics datasets and the integration of quantitative proteomics data in Expression Atlas.

More broadly, as proteomics is a key technology in the Life Sciences, there is the potential for considerable indirect benefits across a wide range of areas in basic biology, biomedical and clinical science, as more value will be derived from datasets.

Life scientists worldwide will be able to benefit from the training activities planned (both face-to-face and via on-line resources).

Staff employed will benefit:

- Receiving further training in a key enabling technology for the BBSRC (proteomics) and exposure to a multi-disciplinary team, and to conferences, workshops and new national and international collaborations (for example through the Proteomics Standards Initiative).

- Acquiring skills needed to work with bioinformatics software in a cloud environment, something that is getting increasingly important with the growing size of datasets and the need of suitable IT infrastructure.