Abstract
Mass spectrometry (MS) data is a key technology in modern metabolomics and proteomics experiments. Continuous improvements in MS instrumentation, larger experiments and new technological developments lead to ever growing data sizes and increased number of available variables making standard in-memory data handling and processing difficult. The Spectra Bioconductor package provides a modern infrastructure for MS data handling specifically designed to enable extension to additional data resources or alternative data representations. These can be realized by extending the virtual MsBackend class and its related methods. Implementations of such MsBackend classes can be tailored for specific needs, such as low memory footprint, fast processing, remote data access, or also support for specific additional data types or variables. Importantly, data processing of Spectra objects is independent of the backend in use due to a lazy evaluation mechanism that caches data manipulations internally. This workshop discusses different available data representations for MS data along with their properties, advantages and performances. In addition, Spectra's concept of lazy evaluation for data manipulations is presented, as well as a simple caching mechanism for data modifications. Finally, it explains how new MsBackend instances can be implemented and tested to ensure compliance.