The R/Bioconductor infrastructure for single-cell proteomics

The Bioconductor project has been developing and sharing open source software for precise and repeatable analysis of biological data for 25 years. The first packages dedicated to mass spectrometry date back to 2004-2005, with the first complete infrastructure for proteomics data being available since 2011. This infrastructure was revisited in 2019 with the explicit goal of handling of mass spectrometry-based single-cell proteomics (SCP). These efforts led to the QFeautres, scp and scpdata package trio that have been spearheading SCP data analysis and interpretation since 2021. The packages provide a robust, thoroughly documented, tested, interoperable and flexible infrastructure for quantitative data processing and visualisation, dedicated analysis methods for SCP data, and tens of readily available curated SCP datasets, among which many seminal datasets. Together, these packages offer an ideal platform that provide users with rigorous data analysis and interpretation capabilities, and developers with flexible development and benchmarking environment. In this contribution, I will provide an overview of the QFeautres, scp and scpdata capabilities for SCP, catering for both technical and non-technical audiences.