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Prioritization of m/z‑Values in Mass Spectrometry Imaging Profiles Obtained Using Uniform Manifold Approximation and Projection for Dimensionality Reduction
journal contribution
posted on 2020-03-20, 19:39 authored by Tina Smets, Etienne Waelkens, Bart De MoorMass
spectrometry imaging (MSI) is a promising technique to assess
the spatial distribution of molecules in a tissue sample. Nonlinear
dimensionality reduction methods such as Uniform Manifold Approximation
and Projection (UMAP) can be very valuable for the visualization of
the massive data sets produced by MSI. These visualizations can offer
us good initial insights regarding the heterogeneity and variety of
molecular patterns present in the data, but they do not discern which
molecules might be driving these observations. To prioritize the m/z-values associated with these biochemical
profiles, we apply a bidirectional dimensionality reduction approach
taking into account both the spectral and spatial information. The
results show that both sources of information are instrumental to
get a more comprehensive view on the relevant m/z-values and can support the reliability of the results
obtained using UMAP. We illustrate our approach on heterogeneous pancreas
tissues obtained from healthy mice.
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Mass Spectrometry Imaging Profiles ObtainedprofileinsightMSIresults showDimensionality Reduction Mass spectrometry imagingvisualizationvarietypatterntechniquesourceUniform Manifold Approximationtissue sampleheterogeneityinformationmoleculeUMAPbidirectional dimensionality reduction approachProjectionprioritizedata setsPrioritizationNonlinear dimensionality reduction methodspancreas tissuesreliability
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