RomicsProcessor use case 2: Histology guided MALDI-MSI

This dataset and accompanying code correspond to Use Case 2 from the manuscript "Reproducible-by-design: RomicsProcessor, a FAIR ecosystem for multi-omics and spatial-omics analysis". Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) data and co-registered histology dataset of kidney biopsies from quality control (QC) and acute kidney injury (AKI) tissues. All biopsy data is combined into a single SCiLS datafile (.slx and .sdb). The primary goal of this data is to provide an example workflow for mass spectrometry imaging data. This use case moves the data from Bruker's SCiLS data format to a Romics_object format for streamlined data processing within an open source R-enviroment. Experimental Context: This dataset consists of MALDI-MSI lipidomics of three batches of kidney biopsies and control tissues ran on a Bruker SolariX 12 Tesla FTICR instrument at a 25 µm step size. Dataset Contents and Structure: .slx and .sdb files: are SCiLS files that can be opened in Bruker SCiLS or using the SCiLS API *.Rmd file: Contains the R script used to perform the entire data processing and statistical analysis workflow described in the manuscript. This script demonstrates how to create the romics_object and apply filtering, normalization, and statistical functions. *.Rda: Contains the final, processed data object generated by the code. This single file encapsulates the original data, all processing steps, parameters, software dependencies, and final statistical results, serving as a complete and verifiable digital record of the analysis.