ShinyMDE: Shiny tool for microarray meta-analysis for differentially expressed gene detection

Abstract

The advancement in high-throughput microarray experiments has paved a way for several transcriptomic studies across the globe by several researchers in the area of functional genomics, molecular genetics, gene discovery, differentially expressed gene detection, diagnosis and prognosis etc. As a result, the tremendous amount of data that has been produced and accumulated in various public repositories such as Gene Expression Omnibus (GEO) and ArrayExpress, have been frequently used by researchers to readdress various biological goals. Since an independent study often comes with less sample size and limited statistical power, researchers are now relying on a more powerful technique called meta-analysis, an integrated analysis of existing data from different related independent studies. Meta-analysis is an active area in biomedical research which plays a vital role in increasing the statistical power to detect differentially expressed genes and to understand molecular and cellular aspects in a broader way. However, little efforts have been put to design user friendly tool/software to carry out meta-analysis automatically. In this paper, we present ShinyMDE, a user friendly tool to integrate different gene expression data for differentially expressed gene detection in an easy and efficient way. The tool handles processed and raw data generated from most widely used data platforms such as Affymetrix and Illumina. In addition, the tool provides user with an option of choosing the method of their choice from the list for meta-analysis. The tool is very simple to use and is developed with the aim of having an automated meta-analysis of gene expression data facilitating screening and downloading the results.