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OmicsHQ year-end promotion
Explore OmicsHQ. Access the data you need.
Free OmicsHQ platform access through December 31, 2026.
Discover thousands of expertly curated, harmonized single-cell datasets through OmicsHQ. Explore the catalog, evaluate datasets, and identify the data your research needs. Purchase the datasets you need with credits, with no platform access fee through the end of the year.
Get more from your data investment with bonus credits on qualifying purchases.
Purchase data credits by December 31, 2026. Purchased credits are guaranteed for use through December 31, 2027.
The challenge
Bring fragmented omics data into your research
Public single-cell datasets are spread across repositories, inconsistently processed, and difficult to compare. Finding suitable studies is only the first step; your research also depends on consistent metadata and reproducible processing.
OmicsHQ brings curated single-cell datasets and harmonized metadata into one catalog so you can evaluate the data before purchasing.
The solution
Depth, quality, and structure
Explore 8,000+ curated studies and identify the single-cell data your research needs. OmicsHQ combines study records, harmonized metadata, and pre-processed datasets to support downstream bioinformatics and AI/ML workflows.
A unified catalog of analysis-ready omics datasets
Search across public sources in one place. Evaluate datasets using UMAP and PCA visualizations, then purchase the data you need using credits.
Dataset collections
Collections by therapeutic area
Explore dataset collections by therapeutic area.
| Therapeutic area / collection | Datasets | Total cells |
|---|---|---|
| Cancer and neoplasms | 289 | 29.1 million |
| Autoimmune and inflammatory diseases | 158 | 14.3 million |
| Neurological and psychiatric disorders | 123 | 16.2 million |
| Cardiovascular and blood disorders | 53 | 66.6 million |
| Full SDCS1 catalog | 1,029 | 99.7 million |
More data. More value.
Invest in data. Get more with OmicsHQ.
For a limited time, Rancho is making OmicsHQ platform access free through December 31, 2026. Put your budget toward the data you need, and get additional credits with qualifying purchases.
| Data credit purchase | Bonus credits |
|---|---|
| $10,000+ | 5% |
| $25,000+ | 10% |
| $50,000+ | 15% |
| $100,000+ | 20% |
Purchase credits by December 31, 2026. Purchased credits are guaranteed to remain available for use in OmicsHQ through December 31, 2027.
From fragmented data to analysis-ready datasets
| Working across repositories | Working with OmicsHQ |
|---|---|
| Multiple repositories | One unified catalog |
| Inconsistent raw data | Standardized, curated datasets |
| Manual filtering through papers | Structured search with harmonized metadata |
| Difficult cross-study comparison | Consistent metadata for comparison |
| Dataset evaluation after download | UMAP and PCA previews before purchase |
| Dataset-by-dataset preprocessing | Pre-processed data available for downstream analysis |
Expert curation
Curated, standardized, and validated datasets
Each dataset goes through a structured process before it is added to the catalog.
- Pre-screening: Datasets are evaluated for relevance and quality before inclusion.
- Standardize and harmonize: Metadata is aligned to consistent ontologies across study, donor, sample, and disease levels.
- Bioinformatics processing: Datasets are processed through a reproducible, validated pipeline.
- Independent quality review: Each dataset is checked for accuracy and consistency before publication to the catalog.
- Ready-to-use delivery: Data is structured for downstream analysis and AI workflows.
Your next dataset is waiting.
Explore 8,000+ curated studies and discover how OmicsHQ can support your research.
Get free platform access through December 31, 2026, and bonus data credits with qualifying purchases.
Purchase credits by December 31, 2026. Purchased credits are guaranteed for use through December 31, 2027.
Tell us about your research and data needs. Our team will help you identify the right datasets and credit package for your organization.