Abstract

Continued progress toward systematic generation of large-scale and comprehensive proteomics data in the context of biomedical research will create project-level data sets of unprecedented size and ultimately overwhelm current practices for results validation that are based on distribution of native or surrogate mass spectrometry files. Moreover, the majority of proteomics studies leverage discovery-mode MS/MS analyses, rendering associated data-reduction efforts incomplete at best, and essentially ensuring future demand for re-analysis of data as new biological and technical information become available. Based on these observations, we propose to move beyond the sharing of interpreted spectra, or even the distribution of data at the individual file or project level, to a system much like that used in high-energy physics and astronomy, whereby raw data are made programmatically accessible at the site of acquisition. Toward this end we have developed a web-based server (mzServer), which exposes our common API (mzAPI) through very intuitive (RESTful) uniform resource locators (URL) and provides remote data access and analysis capabilities to the research community. Our prototype mzServer provides a model for lab-based and community-wide data access and analysis.

Highlights

  • The effective communication of mass-spectrometry based analyses performed in support of biomedical research remains a significant challenge

  • The scenario described above is feasible in principle, we believe that in practice the paradigm of communitywide distribution of primary mass spectrometry data is poorly matched with the current trajectory of biomedical research

  • One viable alternative would be to provide web-based, programmatic access to primary mass spectrometry data at the site of acquisition or a third party data-server. This strategy is the standard in the field of astronomy, exemplified by the Virtual Astronomical Observatory

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Summary

Introduction

The effective communication of mass-spectrometry based analyses performed in support of biomedical research remains a significant challenge. A substantial portion of mzResults’ functionality goes beyond compliance with data reporting requirements, and enables user-driven interrogation of the underlying native mass spectrometry data files through our recently described common application programming interface (API)1 (mzAPI) [1].

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