title: Insights from the clustering of microarray data associated with the heart disease.
abstract: 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.
authors.affiliation: Department of Statistics, National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Indian Council of Medical Research, Chennai-31, India.
authors.forename: Venkatesan
authors.initials: V
authors.lastname: Perumal
authors.forename: Vasantha
authors.initials: V
authors.lastname: Mahalingam
keywords: Cluster analysis; Heart failure; Microarray data; Principal component analysis
references.citation: Nat Med. 2006 Jan;12(1):128-32
references.pmid: 16327803
references.citation: Hum Genet. 1991 Jun;87(2):189-92
references.pmid: 2066106
references.citation: Nat Rev Cardiol. 2011 Jan;8(1):30-41
references.pmid: 21060326
references.citation: Bioinformation. 2011 Apr 22;6(3):95-9
references.pmid: 21584183
references.citation: Physiol Genomics. 2002 Jul 12;10(1):31-44
references.pmid: 12118103
references.citation: Mol Cell Biol. 2005 Dec;25(24):10953-64
references.pmid: 16314518
references.citation: Schizophr Res. 2011 May;128(1-3):143-9
references.pmid: 21353765
references.citation: Comput Methods Biomech Biomed Engin. 2010 Aug;13(4):493-503
references.pmid: 20635265
references.citation: BMC Bioinformatics. 2012 Feb 03;13:24
references.pmid: 22305354
references.citation: Physiol Genomics. 2007 Mar 14;29(1):76-83
references.pmid: 17164392
references.citation: Bioinformatics. 2001 Sep;17(9):763-74
references.pmid: 11590094