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The rawrr R Package: Direct Access to Orbitrap Data and Beyond

Tobias Kockmann, Christian Panse

2021Journal of Proteome Research36 citationsDOIOpen Access PDF

Abstract

The Bioconductor project (Nat. Methods 2015, 12 (2), 115–121) has shown that the R statistical environment is a highly valuable tool for genomics data analysis, but with respect to proteomics, we are still missing low-level infrastructure to enable performant and robust analysis workflows in R. Fundamentally important are libraries that provide raw data access. Our R package rawDiag (J. Proteome Res. 2018, 17 (8), 2908–2914) has provided the proof-of-principle how access to mass spectrometry raw files can be realized by wrapping a vendor-provided advanced programming interface (API) for the purpose of metadata analysis and visualization. Our novel package rawrr now provides complete, OS-independent access to all spectral data logged in Thermo Fisher Scientific raw files. In this technical note, we present implementation details and describe the main functionalities provided by the rawrr package. In addition, we report two use cases inspired by real-world research tasks that demonstrate the application of the package. The raw data used for demonstration purposes was deposited as MassIVE data set MSV000086542. Availability: https://github.com/fgcz/rawrr.

Topics & Concepts

BioconductorComputer scienceWorkflowMetadataRaw dataApplication programming interfaceDatabaseFile formatR packageJSONInterface (matter)Data accessData miningInformation retrievalWorld Wide WebOperating systemProgramming languageMaximum bubble pressure methodBubbleChemistryGeneBiochemistryAdvanced Proteomics Techniques and ApplicationsGene expression and cancer classificationMetabolomics and Mass Spectrometry Studies
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