Multi-Slide Alignment

When working with MSI datasets from multiple slides (e.g., different patients or tissue sections), each slide typically contains a unique m/z list. This prevents direct comparison or merging of datasets. The Multi-Slide Alignment tab in MassVision provides tools to unify m/z features across slides before exporting a merged dataset for downstream analysis.

Import datasets

  • Import as many CSV files as desired by clicking Select under “Import CSV datasets” section. A dialog box will appear allowing you to browse your local storage and select files.

  • After adding all data, you see the names and locations in list. You can add more files by clicking the Select button again, or delete existing files by clicking on Delete in front of each item.

  • After satisfied with the list, click on Load files to load the data.

Important

Differentiation between slides/patients is based on the names of the individual CSV datasets. Therefore, each dataset name must be unique to ensure error-free slide tracking.

Alignment Parameters

KDE bandwidth for ion clustering

Controls the standard deviation of the Gaussian kernel used in Kernel Density Estimation (KDE). This parameter defines the radius (in Da) for grouping neighboring m/z values into clusters.

  • Smaller values → narrow clustering, preserving fine details but requiring higher mass accuracy.

  • Larger values → broader clustering, merging nearby peaks more aggressively.

Feature sparsity

Specifies the criterion for retaining clusters (features) after alignment. For example, a sparsity value of 0.7 means that a feature will be discarded if it appears in 30% or fewer spectra or slides, depending on the selected Sparsity level.

  • Higher sparsity values → keep only features shared broadly across the dataset, reducing the number of total features.

  • Lower sparsity values → retain more features, including those that may be rare or slide-specific.

Sparsity level

Defines whether sparsity is calculated based on Slides or Spectra.

  • Spectra: the threshold is applied across individual spectra within slides.

  • Slides: the threshold is applied across entire slides, retaining only features consistently present between slides.

Alignment Preview

visualization range (m/z)

Enter an m/z window to inspect alignment quality in a specific region.

Visualize

Generates the interactive KDE density preview, helping confirm that peaks from different slides are correctly grouped. The preview shows:

  • The original m/z values,

  • KDE-derived density peaks (clusters), and

  • The final selected feature list after applying sparsity.

Peak Matching

Method

Select how intensities are assigned to the unified feature list:

  • Cluster: assigns each peak to the nearest KDE-derived cluster.

  • Tolerance mode: assigns peaks within a user-defined m/z window around each feature.

In this mode, multiple matches can be aggregated using statistics such as mean, sum, or maximum.

Align and Save

Performs alignment using the selected parameters and saves the merged dataset in CSV format in the user defined location. The aligned spectra from all slides are mapped to a single unified m/z reference list. The metadata about the aligned dataset detailing the number of slides, classes, and spectra per classes will be displayed after alignment.