Insights from the clustering of microarray data associated with the heart disease |
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Authors: | Venkatesan Perumal Vasantha Mahalingam |
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Institution: | Department of Statistics, National Institute for Research in Tuberculosis (Formerly Tuberculosis Research Centre), Indian Council of Medical Research, Chennai-31, India |
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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. |
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Keywords: | Microarray data Cluster analysis Principal component analysis Heart failure |
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