Study on Analysis of Gene Expression Dataset and Identification of Differentially Expressed Genes

The analysis on the dataset of complex genetic diseases such as cancer, cardiovascular, respiratory diseases, AIDS in Homo sapiens at early stage of diagnosis is important. It is a challenging task in today’s biomedical and other research area domains. In this paper, the analysis of gene expression dataset is discussed. The gene expression datasets are high-dimensional datasets and give more scope for us to analyze the diseases due to change in gene expression levels in the cell of human body. In this paper, gene expression datasets E-GEOD-6575 and of tumor are analyzed using heat map and classification technique. The gene expression dataset of RNA-seq tumor of 801 samples based on classification is discussed. Each sample of tumor dataset is associated with set of gene expression values. The gene expression values in the dataset of 801 patients are distributed among the five different types of classes of tumors. The main objective of this paper is to understand the significance of change in gene expression values in the dataset that are the cause of diseases. The analysis will be helpful in prognosis of diseases and will help the physicians for prediction and deriving conclusions. The analysis is also helpful to identify the existence of differentially expressed genes.