Artículo
Analysis of genetic association using hierarchical clustering and cluster validation indices
Pagnuco, Inti Anabela
; Pastore, Juan Ignacio
; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia Laura
Fecha de publicación:
10/2017
Editorial:
Academic Press Inc Elsevier Science
Revista:
Genomics
ISSN:
0888-7543
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes.
Palabras clave:
Association
,
Clustering
,
Genomics
,
Validation Indices
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Articulos(ICYTE)
Articulos de INSTITUTO DE INVESTIGACIONES CIENTIFICAS Y TECNOLOGICAS EN ELECTRONICA
Articulos de INSTITUTO DE INVESTIGACIONES CIENTIFICAS Y TECNOLOGICAS EN ELECTRONICA
Citación
Pagnuco, Inti Anabela; Pastore, Juan Ignacio; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia Laura; Analysis of genetic association using hierarchical clustering and cluster validation indices; Academic Press Inc Elsevier Science; Genomics; 109; 5-6; 10-2017; 438-445
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