rMSIproc: an R package for mass spectrometry imaging data processing.

Area of Science:

• Biochemistry
• Computational Biology
• Data Science

Background:

• Mass spectrometry imaging (MSI) provides direct biochemical insights from tissue sections.
• Processing the large and complex spectral data from MSI remains a significant challenge.
• Extracting meaningful biochemical information from MSI data requires sophisticated analytical tools.

Purpose of the Study:

• To introduce rMSIproc, an open-source R package for comprehensive MSI data processing.
• To enable robust statistical analysis by facilitating the simultaneous processing of multiple MSI datasets.
• To enhance the utilization of modern computational resources for MSI data analysis.

Main Methods:

• Development of an open-source R package, rMSIproc.
• Implementation of a novel spectral alignment and recalibration strategy.
• Design for handling large datasets exceeding computer memory capacity using multi-threading.

Main Results:

• rMSIproc enables simultaneous processing and confident statistical analysis of multiple MSI datasets.
• The package efficiently handles large files and utilizes multi-threading for performance.
• It provides a complete data processing workflow for TOF or FT-based mass spectrometers.

Conclusions:

• rMSIproc is a powerful tool for unlocking the full potential of MSI data.
• The package facilitates advanced biochemical analysis and statistical interpretation of complex MSI experiments.
• Its open-source nature and efficient algorithms support broader scientific application.