Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format
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Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format Stefania Alexandra Iakab1,2†, Lluc Sementé1†, María García‑Altares1,2* , Xavier Correig1,2,3 and Pere Ràfols1 *Correspondence: maria.garcia‑[email protected] † Stefania Alexandra Iakab and Lluc Sementé have contributed equally to this work. 1 Department of Electronic Engineering, Rovira i Virgili University, 43007 Tarragona, Spain Full list of author information is available at the end of the article
Abstract Background: Multimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand. Results: Raman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications. Conclusion: Raman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis. Keywords: Converter, Raman imaging, imzML, R, Mass spectrometry imaging
Background In recent years, mass spectrometry imaging (MSI) has become an important analytical technique because of its capacity to spatially localize a wide range of biomolecules from plant, animal and human tissues [1]. The main advantage of MSI is its high specificity, which makes it possible to identify endogenous and exogenous compounds such as metabolites, lipids, peptides and proteins. Consequently, a considerable number of advanced data analysis tools have emerged as proprietary or open source software, with a tendency towards data format standardization [2]. However, the most common MSI instruments and sample preparation protocols have difficulty in acquiring high spatial resolution images. The spatial resolution of current acquisitions is limited to a few micrometres, which prevents the detailed molecular characterization at the micron scale so necessary for the study of microorganisms and cells [3]. Thus, it was suggested that the molecular images produced by MSI could be combined with images obtained by other high spatial resolution techniques. Several studies
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