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Title: Aplicación y comparativa de cuatro modelos de clustering para datos GTEx
Author: López Sánchez, Victoria
Director: Ventura Royo, Carles  
Tutor: Fernández Martínez, Daniel
Keywords: ARN-seq
Issue Date: Jan-2019
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Presently TFM, it has been studied and evaluated four different clustering algorithms: coexp method (WGCNA + k-means), k-means conventional and two mixture models. First of all, it will implement all clustering models, search optimum clusters numbers statistical criteria-based as BIC, AIC and elbow method, at last, the final partitions generated by those methods are visualized are compared via external validation metrics (measures). Various clustering comparison measures have been used, counting-based measures as Adjusted Rand index (ARI) and information theoretic-based as Normalized Variation of Information (NVI) and Normalized Distance of Information (NID).
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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