Cardinal is an R package that implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
NEWS
- July, 2024 — A recording of our Cardinal tutorial session from 2024’s May Institute short course series is now available on YouTube: https://www.youtube.com/watch?v=e6zZI2MsdA8.
- May, 2024 — Cardinal 3.6 is released! This is a major update with breaking changes (which we believe are very much worth it). New features include:
- Redesigned data structures
- Updated MSImagingExperiment class for MS imaging data with shared m/z values
- New MSImagingArrays class for MS imaging data with different m/z values
- All statistical methods (including PCA, PLS, spatial k-means, and spatial shrunken centroids) have been updated for improved speed and simpler storage of results
- New pre-processing workflow with better support for high-resolution experiments
- New support for multiple-instance learning
- New plotting engine
- Redesigned data structures
- May, 2024 — We are teaching a Cardinal session at our May Institute Short Course on Computation and Statistics for Mass Spectrometry and Proteomics on May 6, 2024.
- July, 2023 — We are teaching a Cardinal workshop at the Mass Spectrometry Imaging Short Course and Workshop at the University of Texas at Austin on August 1-4, 2023.
- February, 2023 — A preprint of our forthcoming article on “Cardinal v3 – a versatile open source software for mass spectrometry imaging analysis” is now online! We will update the Cardinal citation below when the final article is published.
- November, 2022 — Cardinal 3.0 is released! This is a major update with that will set the framework for many upcoming improvements over the next versions. While there are no big user-visible changes in 3.0, there have been significant improvements on the backend that will affect Cardinal’s support for high-resolution datasets. We will be continuing to build on these improvements over the next several versions, with a focus on easier data import/export and better pre-processing capabilities.
- October, 2019 — We are teaching Cardinal Workshops at the following mass spectrometry imaging conferences:
- October 11, 2019 – Asilomar Conference, hosted by ASMS and IMSS
- October 28, 2019 – OurCon VII, hosted by MSIS
- May 3, 2019 — Cardinal 2.2 is officially live with Bioconductor 3.9! This is a major update with many changes. Cardinal 2.0 set the groundwork for a migration to the new MSImagingExperiment class, and Cardinal 2.2 fulfills that promise with many new updates, changes, and new features:
- Defaults for data import have changed:
- Datasets are imported as MSImagingExperiment objects
- Spectra from imported datasets are not loaded into memory; they are loaded on-access
- All statistical methods (including PCA, PLS, spatial k-means, and spatial shrunken centroids) are now fully supported for MSImagingExperiment
- New statistical methods including spatial-DGMM and hypothesis testing via means-summarized linear models and segmentation-based linear models
- Pervasive support for parallel computation via BiocParallel
- New vignettes documenting both basic use and statistical methods for MSImagingExperiment
- Visualization enhancements:
- Colorkeys for images are now plotted on the side
- Default colorscale for images is now “viridis”
- “Dark mode”
- Improved simulation of spectra and imaging experiments
- Out-of-memory enhancements in matter backend
- Exhaustive list of changes documented here on Bioconductor NEWS
- Defaults for data import have changed:
- May 1-3, 2019 — We will teach a Cardinal workshop as part of the May Institute short course series in computation and statistics for proteomics
- See the May Institute course website for more details
- Workshop will include an introductory lecture to basic Cardinal concepts, followed by a hands-on tutorial of common statistical analyses
- October 30, 2018 — Cardinal 2.0 is available on Bioconductor 3.8! This is a major update with many new features including:
- New MS imaging data classes with improved support for working with large experiments
- Rewritten visualization methods with support for non-gridded pixel coordinates and new color schemes
- Full read/write support for both imzML ‘continuous’ and ‘processed’ formats
- New preprocessing workflows with support for queueing of delayed processing steps and out-of-memory parallel execution
- May 4, 2016 — Cardinal 1.4 is available on Bioconductor 3.3
- December 16, 2015 — Cardinal 1.3 is available on Github with *experimental* support for:
- Working with larger-than-memory datasets on disk
- 3D imaging datasets
- imzML ‘processed’ format
- June 10, 2015 — Cardinal wins the John M. Chambers Statistical Software Award 2015 presented by the American Statistical Association
DATA FORMATS
- Analyze 7.5 (ABSciex and others)
- imzML (converters available at http://www.imzml.org)
FEATURES
- Visualization of mass spectra and molecular ion images
- Pre-processing including normalization, baseline correction, peak-picking and alignment
- Principal components analysis (PCA)
- Partial least squares discriminant analysis (PLS-DA)
- Classification based on regularized nearest shrunken centroids
- Spatial segmentation via regularized nearest shrunken centroid clustering
CITING CARDINAL
CITING SPATIAL SHRUNKEN CENTROIDS
- Bemis, K. D., Harry, A., Eberlin, L. S., Ferreira, C. R., van de Ven, S. M., Mallick, P., et al. (2016). Probabilistic Segmentation of Mass Spectrometry (MS) Images Helps Select Important Ions and Characterize Confidence in the Resulting Segments. Molecular & Cellular Proteomics, 15(5), 1761–1772. http://doi.org/10.1074/mcp.O115.053918