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

20th Argentinean Bioengineering Society Congress

物理学;生物科学

Pagnuco, Inti A.^1,2,3 ; Pastore, Juan I.^1,2,3 ; Abras, Guillermo^1 ; Brun, Marcel^1,2 ; Ballarin, Virginia L.^1

Digital Image Processing Group, School of Engineering, UNMdP, Argentina^1

Department of Mathematics, School of Engineering, UNMdP, Argentina^2

CONICET, Argentina^3

关键词: Bioinformatics tools;    Cluster qualities;    Data examples;    Expressed genes;    Hier-archical clustering;    Network information;    Regulatory network;    Silhouette indices;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012002/pdf
DOI  :  10.1088/1742-6596/705/1/012002

学科分类：生物科学（综合）

来源: IOP

【 摘 要 】

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 significative groups of genes are defined based on some criteria. This task is usually performed 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 experiment. 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 find all possible subsets, we compared its results against a full search, to determine the amount of good co-regulated sets not detected.