Abstract
A frequent problem with scientific research software is the lack of support, maintenance, and continued enhancement. In particular, development lead by a single researcher can easily result in orphaned software packages, especially if combined with poor documentation or lack of adherence to open software development standards. The RforMassSpectrometry initiative aims to establish an efficient and stable infrastructure for mass spectrometry (MS) data analysis. To this end, a growing ecosystem of R software packages is being developed covering different aspects of metabolomics and proteomics data analysis. To avoid the aforementioned problems, community contributions are fostered, while open development, documentation and long-term support are emphasized. At the heart of the package ecosystem is the Spectra package which provides the core infrastructure to handle and analyze MS data. Its design allows easy expansion to support additional file or data formats including data representations with minimal memory footprint or remote data access. Through chunk-wise data processing and a lazy processing queue analysis of also very large data sets is supported. All packages are available through the Bioconductor project and enable the creation of customized, data set specific, and reproducible analysis workflows.