Analysis of genetic association in Listeria and Diabetes using Hierarchical Clustering and Silhouette Index

INTI PAGNUCO; JUAN IGNACIO PASTORE; GUILLERMO ABRAS; MARCEL BRUN; VIRGINIA BALLARIN

San Nicolás

Congreso; XX CONGRESO ARGENTINO DE BIOINGENIERÍA IX JORNADAS DE INGENIERÍA CLÍNICA; 2015

Sociedad Argentina de Bioingeniería y el Grupo de Análisis, Desarrollos e Investigaciones Biomédicas (GADIB) de la Facultad Regional San Nicolás

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, where signicative groups of genes are dened based on some criteria. This task is usually erformed by clustering algorithms, where the whole family of genes, or a subset of them, are clustered into meaningful groups based on their expression values in a set of xperiment.In this work we used a methodology based on the Silhouette index as a measure of cluster quality for individual gene groups, and a combination of several variants of hierarchical clustering to generate the candidate groups, to obtain sets of co-expressed genes for two real data examples.We analyzed the quality of the best ranked groups, obtained by the algorithm, using an online bioinformatics tool that provides network information for the selected genes.Moreover, to verify the performance of the algorithm, considering the fact that it doesn´t nd all possible subsets, we compared its results against a full search, to determine the amount of good co-regulated sets not detected.