Materia: Chemistry; Medicine, Health and Life Sciences
Derechos de acceso: info:eu-repo/semantics/openAccess
Identificador del investigador: 0000-0002-3479-3841; 0000-0002-1743-656X
Publicado por (editorial): Universitat Rovira i Virgili (URV)
Idioma: en
Publicaciones relacionadas: Publication is in preparation.
Resumen: Replication data for the publication: "rSIREM: an R package for MALDI spectral deconvolution" by Del Castillo Pérez et al. The deposited data are SALDI-MSI data of three consectutive thin tissue sections from mouse cerebellum measured at the different mass resolutions at the same instrument (MALDI-MSI: Spectroglyph Injector - Orbitrap Exploris). The paper describes a new R package (rSIREM) to computationally improve the mass resolution of an MSI post-measurement. The developed R package (https://github.com/EdelCastillo/rSirem ) applies a statistical treatment on the concentration of spatial images obtained by separately considering each of the m/z over all the pixels. A representative scalar is associated with each image, obtained by applying a new measure (SIREM) to it, derived from Shannon's entropy. The perturbations of this measure, when considering a sequence of consecutive images, reveal the existence of overlap, if it exists. This information serves as a seed to initialize the EM algorithm in the Gaussian Mixture Model context. The efficiency of the method has been verified using three independent procedures. (2024-09-16)
Tipos de datos: Experimental data; Measurement and test data
Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
DOI: 10.34810/data1744
Tipo de documento: info:eu-repo/semantics/other
Fecha alta repositorio: 2025-04-24
Autor: Bookmeyer, Christoph Hauke Manfred; Del Castillo Pérez, Esteban
Palabras clave: Mass Spectrometry; MALDI MS; Lipids; deconvolution; Nanostructured materials
Grupo de investigación: Metabolomics Interdisciplary Laboratory
Año de publicación de la dataset: 2024
Título del conjunto de datos: Replication data for "rSIREM: an R package for MALDI spectral deconvolution"