Identifying critical genes in esophageal squamous cell carcinoma using an ensemble approach

Abstract

Abstract Esophageal Squamous Cell Carcinoma (ESCC) is considered as a deadly disease especially in the North-East, India. A series of differentially expressed genes (DEGs) are suspected to be involved in the progression of ESCC. To search the DEGs a good number of tools are available. To remove the biasness of resulting DEGs given by all such tools, a consensus function is necessary on which user can rely on the output generated by differential expression analysis methods applied on multiple sources of data. In this study, we have considered two microarrays (of 34 and 106 samples, respectively) and one RNA-seq data (of 29 samples) to conduct an unbiased integrative analysis towards the identification of critical genes for ESCC. Initially, independent downstream analysis on each type of data using six differentially expressed gene identification tools followed by an integrative analysis supported by an effective consensus function is conducted to identify an unbiased set of differently expressed genes. The identified gene set includes common genes obtained (for P-value cut-off