Microarray Gene Expression Statistical Data Analysis of Three Different Clinical Forms of Human Tuberculosis Stimulated Samples in the Bioconductor R Package

Abstract

The overall aim of this research identified and explores the usage of microarray gene expression statistical tools available in Bioconductor R package for image visualization, data quality control, background correction, summarization, normalization and identification of highly differential gene expression from microarray gene expression data of human tuberculosis infections. The stimulated samples with phosphate buffered saline (PBS) of human tuberculosis microarray gene expression data such include pulmonary TB infection (PTB), meningeal TB infection (TBM) and latent TB infection (LTB) image data were collected from GEO-NCBI (Gene Expression Omnibus-National Centre for Biotechnical information’s) database in a form of CEL file format with Accession number: GSE11199 and all the analyses were performed in the R packages. These analyses identified and explore the use of AffyQCReport tool, affycoretools, PCA, MAS 5.0 and GCRMA for microarray gene expression data pre-processing and for the identification of highly significantly expressed genes, LIMMA was used and explore as a statistical tool for such analysis. The statistical analysis from LIMMA indicates that there was a significant difference between the three different forms of human tuberculosis. Therefore, most of the genes significantly expressed in both groups were genes responsible for cellular immune response. The results of three different comparison groups generated from the LIMMA analysis were further analysed using correlation coefficient=1, when p-value<=0.05 and generated Venn diagram, the results from venn diagram shows that majority of the genes were up-regulated indicating less decrease in the rate of gene expression but increase among the regulated genes of stimulated tuberculosis and more genes were observed with higher expression than those with less expression during the three group’s comparison. It suggested recommendation that the results obtained from this study can be utilize in further analysis for detection and control of human tuberculosis infections.