Co-localization features for classification of tumors using mass spectrometry imaging

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Title: Co-localization features for classification of tumors using mass spectrometry imaging
Authors: Inglese, P
Dos Santos Correia, G
Pruski, P
Glen, R
Takats, Z
Item Type: Working Paper
Abstract: Statistical modeling of mass spectrometry imaging (MSI) data is a crucial component for the understanding of the molecular characteristics of cancerous tissues. Quantification of the abundances of metabolites or batch effect between multiple spectral acquisitions represents only a few of the challenges associated with this type of data analysis. Here we introduce a method based on ion co-localization features that allows the classification of whole tissue specimens using MSI data, which overcomes the possible batch effect issues and generates data-driven hypotheses on the underlying mechanisms associated with the different classes of analyzed samples.
Issue Date: 11-Oct-2018
URI: http://hdl.handle.net/10044/1/65504
DOI: htts://dx.doi.org/10.1101/440057
Copyright Statement: © 2018 The Author(s)
Appears in Collections:Division of Surgery
Faculty of Medicine



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