Quality control of samples Downstream analysis of RNASeq and Microarray Illumina platforms involving: Exploratory / Unsupervised analysis to identify the main driver of expression Applying appropriate normalization techniques and testing for differential transcript expression between different conditions to identify gene signatures Statistical analysis involving Longitudinal analysis (Anova, linear models / Generalized linear models) Regression analysis to study the association of gene expression with clinical outcomes such as CD4 counts, viral loads, HIV latent reservoir, viral reactivation measures, antibody responses, ICS data, luminex data and other flow data Pathway analysis by assessing the enrichment in priori known genesets (IPA / MSigDB) Network inference on the enriched genes / pathways Network inference of gene co-expression Analysis help will be provided by using R-Bioconductor and linux shell scripting