Mean intensity aggregation

mean-intensity-aggregation

Summary

Compute mean intensity values across all pixels in a mass spectrometry imaging (MSI) dataset by aggregating intensity arrays at each unique m/z value. This workflow step produces a representative mean spectrum and optionally exports it for downstream ROI analysis and metabolite annotation.

When to use

Apply this skill after importing imzML or vendor-specific MSI data into napari and visualizing the raw spectral dataset. Use it when you need a global intensity profile across the entire MSI experiment to identify dominant m/z peaks, normalize intensity ranges, or generate a reference spectrum for region-of-interest (ROI) comparisons.

When NOT to use

• Input MSI data has not been imported and loaded into the napari environment—perform data import first.
• You require intensity values for a single pixel or localized region only—use ROI selection instead.
• The dataset is already pre-aggregated into a mean spectrum; recalculating would be redundant.

Inputs

• Imported MSI spectral dataset in imzML or vendor-specific format
• m/z values and intensity arrays from all pixels/samples
• Optional pre-processing parameters (noise reduction %, normalization method, hotspot removal quantile)

Outputs

• Mean spectrum: m/z vs. mean intensity table
• CSV or HDF5 export file of aggregated mean intensities
• Mean spectrum visualization plot (optional)
• Image view of mean intensity distribution (optional)

How to apply

Load the imported MSI spectral data (imzML or converted centroid format) into the MSI-Explorer napari plugin environment. Extract m/z values and their corresponding intensity arrays for all spectra in the dataset. For each unique m/z value across all pixels/samples, calculate the arithmetic mean of intensities at that m/z. Optionally apply pre-processing steps (noise reduction as a percentage threshold, normalization methods such as TIC, RMS, or reference peak, and hotspot removal at a quantile threshold like 99.9%) before mean calculation. Aggregate results into a structured m/z vs. mean intensity table and export as CSV or HDF5 for compatibility with downstream ROI analysis and annotation workflows.

Related tools

• napari (Plugin framework environment for loading, visualizing, and processing MSI spectral data) — https://github.com/napari/napari
• MSI-Explorer (napari plugin that implements mean intensity calculation as a workflow step following data import and visualization) — https://github.com/MMV-Lab/MSI-Explorer
• Python (Programming language for arithmetic aggregation and export of mean intensity arrays)

Evaluation signals

• Output table contains all unique m/z values present in the original dataset with no missing entries
• Each mean intensity value is the arithmetic average of intensities at that m/z across all pixels; spot-check by manual calculation on a subset
• Output file is valid CSV or HDF5 and is compatible with downstream ROI analysis and annotation tools
• Mean spectrum plot shows expected dominant peaks and relative intensity relationships consistent with the raw data distribution
• When pre-processing is applied, mean intensities reflect the specified noise reduction percentage, normalization method, and hotspot removal threshold

Limitations

• Profile mode MSI data must be converted to centroid mode before processing; the plugin prompts for this conversion but cannot be circumvented
• Mean intensity calculation assumes all pixels have comparable sampling; highly uneven sampling or missing pixels may skew the aggregate
• Pre-processing steps (noise reduction, normalization, hotspot removal) are applied before aggregation; the order and parameters chosen will significantly affect the final mean spectrum
• Export format (CSV vs. HDF5) must be chosen appropriately for downstream tools; some tools may require specific formats

Evidence

• [other] MSI-Explorer implements mean intensity calculation as a workflow step that processes imported MSI data following data import and visualization stages, operating within the napari plugin framework.: "MSI-Explorer implements mean intensity calculation as a workflow step that processes imported MSI data following data import and visualization stages, operating within the napari plugin framework."
• [other] For each unique m/z value across all spectra, calculate the arithmetic mean of intensities at that m/z across all pixels/samples.: "For each unique m/z value across all spectra, calculate the arithmetic mean of intensities at that m/z across all pixels/samples."
• [other] Aggregate results into a structured table (m/z vs. mean intensity) and save as a CSV or HDF5 file compatible with downstream ROI analysis and annotation workflows.: "Aggregate results into a structured table (m/z vs. mean intensity) and save as a CSV or HDF5 file compatible with downstream ROI analysis and annotation workflows."
• [readme] 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 calculate the mean spectrum, click on Show true mean spectrum. Clicking Show image will create an image view"
• [readme] After pre-processing steps are chosen, click Execute and Show true mean spectrum to calculate the mean intensity.: "After pre-processing steps are chosen, click Execute and Show true mean spectrum to calculate the mean intensity."