GEN is equipped with a series of online tools in aid of further downstream analysis of both bulk and single-cell RNA-seq data and visualizaion of scRNA-seq data analysis results. All the analysis results can be downloaded in CSV and/or Excel formats and visualized images can be exported to PNG or PDF.
For bulk RNA-seq data, GEN offers online services for differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis and gene regulatory network inference. To start ‘Bulk RNA-seq Data Analysis’, users should select bulk RNA-seq dataset of interest first.
For scRNA-seq data, users can perform multiple analyses including quality control, data normalization, scaling and regression, dimensional reduction, graph-based clustering, identification of marker genes for cell clusters, gene enrichment analysis for cell markers, cell trajectory inference, and cell type annotation. To start ‘Single-cell RNA-seq Data Analysis’, users should select single-cell RNA-seq dataset of interest first. network inference. To start ‘Bulk RNA-seq Data Analysis’, users should select bulk RNA-seq dataset of interest first.
Interactive investigation and inspection of single-cell transcriptomic profiles incorporated in GEN through visualization of single-cell RNA-seq data analysis results.