a napari plug-in for biochemical annotation of mass spectrometry imaging data

License BSD-3 PyPI Python Version tests codecov napari hub

The MSI-Explorer napari plugin is a powerful tool designed for targeted biochemical annotations in MSI data. This user manual provides a comprehensive guide on how to install, use, and explore the functionalities of the plugin within the napari platform. It covers data import, visualization, mean intensity calculation, region of interest (ROI) analysis, annotation with selected databases and pre-processing such as noise reduction and normalization.



Install napari by using this command.

 pip install "napari[all]"

You can install MSI-Explorer via pip:

 pip install MSI-Explorer


Start napari from the console with:


Navigate to Plugins -> MSI-Explorer (MSI-Explorer) Plugin

1. Uploading and visualization of mass spectrometry imaging data

  • Select imzml file using Load imzML.
  • Metadata can be checked by View Metadata. Uploading MSI data_v1

Visualization of MSI data_v1

Upon uploading profile mode data, a pop-up appears prompting you to convert it to centroid mode. Selecting Yes converts the data, while No keeps it in its original profile format.


2. Calculating mean (average) intensity

  • To calculate the mean spectrum, click on Show true mean spectrum.
  • Clicking Show image will create an image view of the currently plotted data
  • To export the plotted data as .csv file, click Export spectrum data.
  • To save the spectrum plot as image, click Export spectrum plot.

Calculating mean spectrum

Calculating mean spectrum_v1

2.1. Calculating mean (average) intensity of selected m/z value

To focus on a specific m/z value, zoom in on the spectrum plot. The figure will be as shown as below. Calculating mean spectrum specific mz_v1

It is recommended to use Multi panel view. The image can be displayed by Show image and the data can be exported as .csv file by using Export spectrum data.

3. Pre-processing

The pre-processing capabilities of MSI-Explorer enhance data quality and prepare MSI data for downstream analysis. Pre-processing steps involve:

(a) Noise reduction

Users can choose their desired level of noise reduction (shown as a percentage) for their experiment.

Noise reduction_v1

(b) Normalization

The normalization methods that the user can apply are

  • Total ion current (TIC)
  • Root mean square (RMS)
  • Medium
  • Reference peak (or internal standard)


(c) Hotspot removal

Hotspot removal can also be applied using a default threshold of 99.99%. hotspot removal_v1

After pre-processing steps are chosen, click Execute and Show true mean spectrum to calculate the mean intensity.

The figure shows the spectrum and image of the TIC normalization with 3% noise reduction and hotspot removal for the 99.9% quantile. pre-processed_v1

4. Database

To use the database search, click on Select and a pop-up window will appear. There, select Metabolite_database_ver2, which is a built-in database, and click Confirm.


The features of the database function are

  1. Charge (neutral, positive or negative)
  2. Adduct (based on the charge chosen)
  3. Range of the m/z value for the image display
  4. custom search with molecule name or m/z value


Users can customize the database with exact mass, molecule name, or molecular formula. The format should be as shown in the table and the headers are not needed in the database.

Exact massMolecule nameMolecula formula

5. Region of interest (ROI) selection

  • To select the ROI, click on Select ROI for mean spectrum. Adjust the brush size and label color. You can fill the area by using paint icon.
  • Then click on the Calculate ROI mean spectrum.
  • You can export as .csv file by using Export spectrum data.
  • If one m/z is needed, just zoom-in the spectrum plot window and export.
  • Before selecting the second ROI, remove the first selected area by using eraser or label 0.

ROI selection_v1


Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.


Distributed under the terms of the BSD-3 license, "MSI-Explorer" is free and open source software


If you encounter any problems, please file an issue along with a detailed description.


  • 1.0.1

Last updated:

  • 13 March 2024

First released:

  • 20 July 2023


Supported data:

  • Information not submitted

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GitHub activity:

  • Stars: 2
  • Forks: 2
  • Issues + PRs: 12

Python versions supported:

Operating system:


  • numpy
  • qtpy
  • pyimzml
  • matplotlib
  • vaex
  • opencv-python