title: Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.
abstract: Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single-labeling cDNA microarrays with 11500 original clones. Afterwards, supervised and unsupervised methodologies were applied to obtain the classification model: the former was based on linear discriminant analysis, the later on clustering using the SMCE embedding data. The results obtained using both approaches showed that all (100%) the samples could be correctly classified and the results of all repetitions but one formed a compatible cluster of predictive labels. Finally, the embedding dimensionality of the dataset extracted by SMCE revealed large discrimination margins between both classes.
authors.affiliation: Biomedical Informatics Group (IBIME-ITACA), Universitat Politècnica de València. Camí de Vera s/n, Building 8G, 1st Floor. 46022, València, Spain; GIBI230(Grupo de Investigación Biomédica en Imagen), Instituto de Investigación Sanitaria (IIS) hospital la Fe, Spain.. Electronic address: juanmig@ibime.upv.es.
authors.forename: Juan M
authors.initials: JM
authors.lastname: García-Gómez
authors.forename: Juan
authors.initials: J
authors.lastname: Gómez-Sanchis
authors.forename: Pablo
authors.initials: P
authors.lastname: Escandell-Montero
authors.forename: Elies
authors.initials: E
authors.lastname: Fuster-Garcia
authors.forename: Emilio
authors.initials: E
authors.lastname: Soria-Olivas
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D016002:Discriminant Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D005909:Glioblastoma / Q000235:genetics* / Q000378:metabolism; D006801:Humans; D008579:Meningioma / Q000235:genetics* / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis; D059467:Transcriptome / Q000235:genetics*
keywords: Automatic classification; Bioinformatics; Manifolds; Medical applications; Microarray data analysis