With the large variety of Proteomics workflows, as well as the large variety of instruments and data-analysis software available, researchers today face major challenges validating and comparing their Proteomics data. It is the expectation that Human Proteome Organisation (HUPO) related standardization initiatives with its standardized data formats but also with its efforts in standardized processing and validation will lead to field-generated data of greater accuracy, reproducibility and comparability.

Here we present a new generation of the ProteinScapeTM bioinformatics platform, now enabling researchers to manage Proteomics data from the generation and data warehousing to a central data repository with a strong focus on the improved accuracy, reproducibility and comparability demanded by many researchers in the field. It addresses scientists‘ current needs in proteomics identification, quantification, validation and biomarker discovery. Offering comprehensive solutions for qualitative and quantitative LC-MS/MS and gel-based protein analysis, this proteomics data warehousing and project management software supports various discovery workflows through a flexible analyte hierarchy, a combination of different database search engines, scoring algorithms and quantification methods. It streamlines the discovery process through Decoy validation and the ProteinExtractor™ algorithm that produces non redundant protein result lists across entire Proteomics projects. The implemented processing pipeline for protein identification adopts the human brain proteome project (HUPO BPP) processing guidelines (forum.hbpp.org) and facilitates the direct submission process of Proteomics project data adhering to HUPO/PSI publishing guidelines.

As a specific example of the HUPO based data processing strategy, the analysis of a large proteomics data set is described, including the automatic search over four search engines to generate peptide results, the use of Decoy databases to measure the false positive rate (FPR), the combination of peptide results by the ProteinExtractor algorithm to non-redundant protein lists with known FPR, the automatic evaluation and cutoff of protein lists to defined FPR and merging protein lists of four search engines to one list (ProteinExtractor) with automatic result validation based on the defined FPR threshold value.