GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

Abstract

Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.

Figure 1.

Schema describing data processing and data display for the GEPIA visualization tool.

Figure 2.

Examples of GEPIA outputs. (A) Users can check gene expression by body map in the ‘General’ tab. (B) The differential genes provided by GEPIA can be plotted as chromosomal distribution in the ‘Differential Genes’ tab. (C) GEPIA provides box plots, violin plots based on pathological stages, dot plots and matrix plots in the ‘Expression DIY’ tab. (D) The overall survival and disease-free survival analysis of gene of interest can be presented in the ‘Survival’ tab. Meanwhile, genes with the most significant association with patient survival can be identified. (E) GEPIA provides pairwise gene correlation analysis for given sets of TCGA and/or GTEx expression data in the ‘Correlation’ tab. Genes of interest can be normalized by other gene. (F) Principal component analysis results based on a set of input genes can be presented in the ‘PCA’ tab.