This package, part of the R for Mass Spectrometry initiative, provides a powerful and expandable infrastructure for handling and analysing chromatographic mass spectrometry (MS) data.
It will replace the legacy classes to handle chromatographic data in R provided by the MSnbase package.
This package is part of Bioconductor: https://bioconductor.org/packages/Chromatograms.
Philippine Louail, Laurent Gatto, Sebastian Gibb, Johannes Rainer; Chromatograms: A Modular Infrastructure for Scalable Chromatographic Data Handling in R. Anal. Chem. 29 September 2026; 98 (38):28337β28344. doi: 10.1021/acs.analchem.6c03926
A Chromatograms object is designed to contain multiple chromatographic data
(i.e. chromatogram entities). The data will be stored linearly, i.e. as a long
list of chromatograms. The Chromatograms object will be the main object for
the end user, providing functionality to access, filter or process
chromatographic data, with the actual chromatographic MS data being stored
within backend classes. Different implementations of backend classes can be
designed for high performance or low memory footprint.
The existing backend classes are:
ChromBackendMemory: a memory-based backend, storing the data in
memory. This is the default backend and is used for testing purposes.
The ChromBackendMzR inherits all slots and methods from the base
ChromBackendMemory backend, providing additional functionality for reading
chromatographic data from mzML files.
ChromBackendSpectra: The ChromBackendSpectra inherits all slots and
methods from the base ChromBackendMemory backend, providing additional
functionality for reading chromatographic data from Spectra objects.
These backend are then handled on a user level by the Chromatograms class,
which provides a unified interface to access and manipulate the chromatographic
data.
install.packages("BiocManager")
BiocManager::install("Chromatograms")
Please help us improving and completing the package! Any type of contribution welcome :open_hands: - including discussions, suggestions or actual code. Don't be afraid - we're friendly βΊοΈ! π get involved by opening an issue.
Please also check out the RforMassSpectrometry Contributions Guide.
We follow the RforMassSpectrometry Code of Conduct to maintain an inclusive and respectful community.
This package is licensed under the Artistic 2.0 license: π https://opensource.org/license/Artistic-2.0
Documentation (manuals, vignettes) is licensed under CC BY-NC-SA 4.0: π https://creativecommons.org/licenses/by-nc-sa/4.0/
Part of this work was funded by the European Union under the HORIZON-MSCA-2021 project 101073062: HUMAN β Harmonising and Unifying Blood Metabolic Analysis Networks.