NetworkAnalyst is designed to support integrative analysis of gene expression data through statistical, visual and network-based approaches:

Data inputs: one or more gene/protein lists with optional fold changes; one or more gene expression tables from microarray or RNAseq experiments. Network currently supports 13 species (eight model organisms & five common species).

Expression analysis & meta-analysis: support limma, edgeR and DESeq2. The interface allows paired comparisons, time series, common reference, as well as two-factor nested comparisons; for meta-analysis - p values, fold changes, effect sizes, vote counts, and direct merge.

Network creation & customization: support protein-protein interactions, TF-gene interactions, miRNA-gene interactions, protein-drug interactions and protein-chemical interactions; multiple functions for network refinement;

Network visual analytics: interactive visual exploration - zooming, searching, highlighting, point-and-click, drag-and-drop; network customization - six layout algorithms, background color, edge size/shape, node size/color/visibility; in situ functional enrichment analysis (GO, pathways, etc.); network editing - node deletion, module extraction, and image exporting; topology analysis - hubs, shortest paths analysis, as well as three module detection algorithms.

Other visual analytics: interactive heatmaps, clustering (PCA & t-SNE), Venn diagram and chord diagrams for pattern discovery & complex comparisons.