SLICE-MSI: A machine learning interface for system suitability testing of mass spectrometry imaging platforms

The field of mass spectrometry imaging is currently devoid of standardized protocols or commercially available products designed for system suitability testing of MSI platforms. Machine learning is an approach that can quickly and effectively identify complex patterns in data and use them to make informed classifications, but there is a technical barrier to implementing these algorithms. Here we package the machine learning algorithms into a user-friendly interface to make community-wide implementation of this protocol possible. The software package is built entirely in the Python language using the PySimpleGUI library for the construction of the interface, Pandas and Numpy libraries for data formatting and manipulation, and the Scikit-Learn library for the implementation of machine learning algorithms. Training data is collected on a clean and compromised instrument that can then be used to evaluate model performance and to train models prior to interrogating unknown samples before, du..., , , # SLICE-MSI Executable and Example Data

[https://doi.org/10.5061/dryad.msbcc2g7c](https://doi.org/10.5061/dryad.msbcc2g7c)

## Description of the data and file structure

The collected data comes from a novel QC mix detected on a clean and compromised IR-MALDESI-MSI platform. The corresponding software package is a graphical user interface that incorporates machine learning algorithms for efficient and effective classification of instrument condition. This work was completed to fill a current void in the MSI community and provide an easy-to-use and easily implementable quality control and system suitability testing protocol for MSI.

### Files and variables

#### File: QC\_Testing.csv

**Description:** CSV containing one replicate from the complete dataset to act as a testing set to be used alongside the user manual. Any missing values present are due to the lack of detection of the analyte in that scan. For example, if the analyte is not detected in the ROI the abundance cell will be ...