Data Visualizations

Transform complex biological data into clear, interactive visualizations. Our tools help researchers explore genomic data, identify patterns, and communicate findings effectively.

Genomic Browser

Navigate through genomes with our interactive browser. View genes, regulatory elements, variants, and custom annotation tracks in a unified interface. Zoom from chromosome level down to individual nucleotides, overlay multiple data types, and export publication-ready figures.

  • • Support for human, mouse, and custom reference genomes
  • • Load VCF, BED, GFF, and BigWig files
  • • Integrated variant annotation from ClinVar and gnomAD

Expression Heatmaps

Visualize gene expression patterns across samples with clustered heatmaps. Identify co-expressed gene modules, compare conditions, and discover biomarkers. Our heatmaps support hierarchical clustering, k-means, and custom groupings with multiple color scales.

  • • Automatic normalization and scaling options
  • • Interactive zoom and gene selection
  • • Export to SVG, PNG, or raw data matrices

Variant Explorer

Analyze and visualize genetic variants from VCF files. Filter by impact, frequency, and clinical significance. View variants in genomic context, explore population frequencies, and assess pathogenicity predictions from multiple algorithms.

  • • Lollipop plots for protein-coding variants
  • • Allele frequency comparisons across populations
  • • Integration with ACMG classification guidelines

Pathway & Network Analysis

Map your data onto biological pathways and interaction networks. Identify enriched pathways, visualize protein-protein interactions, and discover functional modules. Overlay expression data, mutations, or custom scores onto KEGG, Reactome, and WikiPathways diagrams.

  • • Gene set enrichment analysis visualization
  • • Interactive network graphs with clustering
  • • Custom pathway creation and annotation

Dimensionality Reduction

Explore high-dimensional data with PCA, t-SNE, and UMAP visualizations. Perfect for single-cell RNA-seq, bulk expression studies, and multi-omics integration. Identify clusters, outliers, and batch effects with interactive 2D and 3D scatter plots.

  • • Color by metadata, expression, or cluster assignment
  • • Adjustable algorithm parameters in real-time
  • • Trajectory inference for developmental studies

Visualization tools are currently in development. Subscribe to get notified when they launch.