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Unraveling Biology One Cell at a Time

Integrating transcriptomics, epigenomics, proteomics, and metabolomics at the single-cell level to decode complexity in health and disease.

📈 Why Single-Cell Multiomics Matters

Traditional "bulk" sequencing masks cellular heterogeneity by averaging signals across millions of cells. Single-cell multiomics enables researchers to:

  • Capture the true diversity of cell states
  • Discover rare cell populations (e.g., stem-like cancer cells)
  • Understand how genomic, transcriptomic, and epigenetic programs interact
  • Build cell atlases for organs and diseases

"Every cell tells a story. Multiomics lets us read every chapter."

📊 Key Modalities in Single-Cell Multiomics

 scRNA-seq: Single-Cell Transcriptomics

  • Measures gene expression in thousands to millions of individual cells.
  • Useful for identifying cell types, cell states, and developmental trajectories.

scATAC-seq: Chromatin Accessibility

  • Reveals which parts of the genome are open and active in each cell.
  • Helps in linking enhancers to target genes and understanding epigenetic regulation.

 CITE-seq: Protein + RNA Quantification

  • Uses oligo-tagged antibodies to quantify surface proteins and RNA in parallel.
  • Bridges the gap between transcriptome and proteome.

Multiome-seq / SNARE-seq

  • Captures both RNA and chromatin accessibility from the same cell.
  • Enables integrative models of gene regulation.

Spatial Transcriptomics (Optional Integration)

  • Localizes gene expression within tissue architecture.
  • Can be integrated with scRNA-seq for spatial context.

🌍 Applications Across the Biomedical Landscape

 Cancer Research

  • Identifying tumor subclones
  • Understanding therapy resistance
  • Mapping tumor-immune microenvironments

Developmental Biology

  • Tracing lineage trajectories
  • Mapping differentiation in embryos
  • Studying tissue morphogenesis

 Immunology

  • Profiling immune responses to infection or vaccination
  • Understanding autoimmune disease at the cellular level
  • Defining T-cell receptor and B-cell receptor diversity

Neuroscience

  • Deconstructing brain cell types and regional variation
  • Linking gene expression to function in health and disease
  • Studying neurodevelopmental and neurodegenerative disorders