Title

Authors

Affiliation

Department of Statistics, National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Indian Council of Medical Research, Chennai-31, India

Email

venkaticmr@gmail.com; *Corresponding author

Article Type

Hypothesis

Date

Received June 17, 2013; Revised August 08, 2013; Accepted August 09, 2013; Published August 28, 2013

Heart failure (HF) is the major of cause of mortality and morbidity in the developed world. Gene expression profiles of animal model of heart failure have been used in number of studies to understand human cardiac disease. In this study, statistical methods of analysing microarray data on cardiac tissues from dogs with pacing induced HF were used to identify differentially expressed genes between normal and two abnormal tissues. The unsupervised techniques principal component analysis (PCA) and cluster analysis were explored to distinguish between three different groups of 12 arrays and to separate the genes which are up regulated in different conditions among 23912 genes in heart failure canines’ microarray data. It was found that out of 23912 genes, 1802 genes were differentially expressed in the three groups at 5% level of significance and 496 genes were differentially expressed at 1% level of significance using one way analysis of variance (ANOVA). The genes clustered using PCA and clustering analysis were explored in the paper to understand HF and a small number of differentially expressed genes related to HF were identified. 

Keywords

Microarray data, Cluster analysis, Principal component analysis, Heart failure, R.

Citation

Perumal & Mahalingam,    Bioinformation 9(15): 759-765 (2013)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.