Bioinformatics & multi-omics

01Overview and value chain

Markers: [EC: EHDS & GDPR (genomic data) | OECD: Genomics & bioinformatics | Regulator: FDA (USA), EMA (EU), NMPA (China)]

Bioinformatics and multi-omics turn biological samples into interpreted data: sequence a genome, profile single cells, map molecules in tissue, then resolve the result with computation. The throughput is staggering — Illumina’s NovaSeq X roadmap lifts maximum output from 25 to 35 billion reads, a 40% gain, and completes 14 billion reads in 20–22 hours, about 30% faster on whole-genome workflows. The frontier is no longer reading DNA but interpreting it across layers: single-cell and spatial transcriptomics, proteomics and metabolomics, fused by foundation models. Clinical multimodal platforms now reason over millions of records — Tempus AI’s Lens runs analyses against more than 8.5 million de-identified patient records — while Chinese instrument makers have closed the hardware gap, MGI Tech holding roughly 70% of China’s sequencer market.

Key directions of bioinformatics & multi-omics:

1. High-throughput sequencing and analysis (Sequencing & Analysis): short- and long-read platforms with integrated variant-calling pipelines like DRAGEN.
2. Single-cell omics (Single-Cell Omics): profiling expression one cell at a time to resolve heterogeneity invisible to bulk assays.
3. Spatial multi-omics (Spatial Omics): mapping transcripts and proteins in their tissue location with Xenium, Visium and Stereo-seq.
4. Biological AI and bioinformatics services (Biological AI): foundation models and CRO-scale analysis turning multimodal data into prioritized targets.

Sectoral value chain

[sample] ──> [library prep] ──> [sequencing] ──> [primary analysis]
                                  │
                          (reads + QC)
                                  │
                                  ▼
[interpreted report] <─── [multi-omics integration] <─────┘

Value chain levels

Cross-cutting technologies of the sector:

• Cloud bioinformatics pipelines (Cloud Pipelines): scalable DRAGEN-style analysis across cohorts.
• Foundation models for biology (Foundation Models): sequence and multimodal models for prediction.
• Adaptive sampling and basecalling (Adaptive Sampling): real-time target enrichment on long-read flow cells.

02US

The US leads on sequencing platforms, single-cell and spatial tools, and AI-driven clinical bioinformatics.

sequencing platforms, single-cell & spatial, clinical ai

• Illumina: the NovaSeq X fleet (890 active installs at end of FY2025) gains a 40% output uplift to 35 billion reads and a Q70 quality score, with DRAGEN pipelines expanded for multi-omics and oncology.
• 10x Genomics: Chromium single-cell and Xenium spatial transcriptomics, releasing breast-cancer reference datasets that align Xenium spatial data with scRNA-seq.
• Tempus AI: the Lens agentic AI platform runs analyses over more than 8.5 million de-identified patient records and is used by 19 of the top 20 biopharma companies.

03CN

China has closed the sequencer gap and built CRO-scale omics, increasingly localizing both hardware and analysis.

domestic sequencers, multi-omics CRO, spatial leadership

• MGI Tech (688114): sold more than 1,470 sequencers in 2025 (over 6,060 cumulative) for roughly 70% of China’s market, with multi-omics revenue up over 47% and spatial-omics revenue up over 161%; Q1 2026 revenue reached 585 million yuan, up 24.8%.
• BGI Genomics (300676): founded in 1999, it runs genome, transcriptome, epigenome and proteome platforms across a global network of subsidiaries.
• Novogene (688315): a sequencing and bioinformatics CRO serving over 7,300 customers across about 90 countries, with 547 registered software copyrights.

04EU

The EU pairs long-read and proteomics innovation with the strictest genomic-data governance.

long-read sequencing, high-plex proteomics, data governance

• Oxford Nanopore: PromethION long-read sequencing with an updated cDNA-PCR kit for isoform-resolved transcriptomics and barcode-aware adaptive sampling.
• Olink: the Explore 3072 proximity-extension assay measures over 1,000 proteins per run for high-plex plasma proteomics.
• EHDS and GDPR: the European Health Data Space and GDPR set the consent and secondary-use rules that frame cross-border genomic data sharing.

05Leading companies and research institutes

06Tech stack and innovations

The stack spans sequencing chemistry, single-cell and spatial capture, and AI interpretation.

1. High-throughput sequencing (NovaSeq & DNBSEQ):
   • Illumina’s NovaSeq X reaches 35 billion reads with a Q70 quality score.
   • MGI Tech’s DNBSEQ instruments hold roughly 70% of China’s market, with the E25 cleared by NMPA.
2. Single-cell and spatial omics (Chromium & Xenium):
   • 10x Genomics Chromium resolves expression cell by cell; Xenium maps transcripts in tissue.
   • MGI’s Stereo-seq and Olink’s high-plex proteomics extend the omics layers.
3. Biological AI and analysis (DRAGEN & Lens):
   • DRAGEN integrates SNV, indel, STR, SV and CNV calling in one framework.
   • Tempus AI’s Lens reasons over multimodal records with specialized AI agents.

07Value chains and production pipelines

Industrial pipeline of a multi-omics study (ISO 20387 biobanking)

┌───────────────────────────┐      ┌───────────────────────────┐
│ 1. Sample & extraction    │ ───> │ 2. Library prep           │
└───────────────────────────┘      └───────────────────────────┘
                                                 │
                                                 ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 4. Primary analysis       │ <─── │ 3. Sequencing             │
└───────────────────────────┘      └───────────────────────────┘
              │
              ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 5. Multi-omics integration│ ───> │ 6. Interpretation & report│
└───────────────────────────┘      └───────────────────────────┘

Stage 1: Sample & extraction

Tissue, cells or fluids are processed to extract nucleic acids or proteins under biobanking controls.

Stage 2: Library prep

Fragmentation, barcoding and adapter ligation build sequencing libraries or single-cell partitions.

Stage 3: Sequencing

Short-read, long-read or spatial platforms generate raw reads, with adaptive sampling enriching targets in real time.

Stage 4: Primary analysis

Base-calling, alignment and variant calling with DRAGEN-style pipelines turn reads into aligned BAM and VCF files.

Stage 5: Multi-omics integration

Genome, transcriptome, proteome and spatial layers are joined into one integrated matrix.

Stage 6: Interpretation & report

Annotation, foundation models and prioritization produce a ranked, auditable report and deposited data.