Illumina
Definition
Illumina is a leading biotechnology company and the dominant platform for next-generation sequencing (NGS), utilizing sequencing-by-synthesis (SBS) technology. The platform employs bridge amplification to create clonal clusters on flow cells, followed by reversible terminator chemistry to read DNA sequences base-by-base. Illumina systems range from benchtop instruments (MiniSeq, MiSeq) to high-throughput production-scale sequencers (NovaSeq, HiSeq), enabling applications including whole-genome sequencing, RNA-seq, ChIP-seq, and single-cell sequencing. The technology's high accuracy (>99.9% at Q30), scalability, and cost-effectiveness have made it the standard for genomics research, clinical diagnostics, and precision medicine. Illumina sequencing generates massive datasets requiring sophisticated bioinformatics pipelines for quality control, alignment, variant calling, and downstream analysis.
Visualize Illumina in Nodes Bio
Researchers can visualize Illumina-derived multi-omics data as integrated network graphs in Nodes Bio. RNA-seq results can be mapped onto gene regulatory networks, showing differentially expressed genes and their interactions. ChIP-seq and ATAC-seq data can reveal transcription factor binding networks. Single-cell sequencing data can be visualized as cell-type interaction networks or developmental trajectories, enabling systems-level interpretation of sequencing results.
Visualization Ideas:
- Multi-omics integration networks combining Illumina RNA-seq, ChIP-seq, and variant data
- Differential gene expression networks from Illumina transcriptomics experiments
- Single-cell trajectory networks showing cellular differentiation paths from Illumina scRNA-seq data
Example Use Case
A cancer genomics team uses Illumina NovaSeq to perform whole-exome sequencing on 200 tumor samples, identifying recurrent mutations in TP53, KRAS, and PIK3CA. They integrate this variant data with RNA-seq expression profiles from the same samples. Using network analysis, they discover that tumors with co-occurring KRAS and PIK3CA mutations show distinct pathway activation patterns in MAPK and PI3K-AKT signaling networks, suggesting combination therapy targets. The multi-omics integration reveals synthetic lethality relationships not apparent from single-data-type analysis.