Co-registration and analysis of multiple imaging mass spectrometry datasets targeting different analytes

MALDI imaging mass spectrometry (IMS) has been successfully used to image a variety of biomolecules. Imaging of the many classes of biomolecules is often achieved through several incompatible sample preparations. Thus, multiple datasets must be acquired from multiple tissue sections to obtain a total molecular overview of a single sample. Addressing the need for single datasets from multiple IMS analyses, we developed the R package RegCombIMS as an extension of R package Cardinal to co-register, combine and create single IMS datasets acquired from serial sections of tissue.

Dataset recombination and analysis is achieved by registration of the IMS datasets to a single coordinate space. The workflow allows for correlation of ions from IMS acquisitions that require incompatible sample preparations as well as multivariate analysis to mine the combined dataset for rapid and more thorough molecular query.

The source code and example data are freely available at https://github.com/NHPatterson/RegCombIMS. All code was implemented in R.

Supplementary data are available at Bioinformatics online.