Run single-cell RNA-seq (scRNA-seq) analysis end to end: Seurat pipelines for QC, clustering, UMAP, integration, and cell type annotation. Every single cell sequencing run is reproducible by default and shared with your whole team.
Single-cell RNA sequencing (scRNA-seq) measures gene expression in individual cells rather than bulk tissue, so you can identify cell types, states, and trajectories inside one sample. A standard single cell RNA-seq analysis runs cell calling, QC, normalization, dimensionality reduction, clustering, UMAP, and marker identification, usually followed by cell type annotation and integration across samples.
On Horizon, the whole scRNA-seq workflow lives in one shared workspace. Bench scientists run validated Seurat pipelines themselves; bioinformaticians see the same data and runs and can adjust parameters, swap references, or extend the analysis without re-uploading anything.
Every run captures its pipeline version, container, reference, and parameters, so the UMAP you publish today can be re-generated identically by a teammate two years from now. No more 'we lost the analysis when she left the lab.'
How Bridge Horizon runs it
Bring in Cell Ranger output, FASTQs from 10x, Parse, or other platforms, or import a public dataset directly.
Choose from validated Seurat workflows. Horizon runs them with the same guided interface regardless.
Configure cell calling, mitochondrial percentage cutoffs, and feature filters through a sample sheet. No hand-edited config files.
Run dimensionality reduction, clustering, and automated cell type annotation, or annotate manually after the run.
Combine samples into one integrated object. Each integration is its own tracked run with full parameter history.
Your bioinformatician and PI explore the same UMAPs and marker tables you do, with controlled access and full provenance.
Supported tools
Bridge Horizon integrates validated bioinformatics tools directly into the workspace. More are added based on what teams request.
Run validated Seurat (R) pipelines for QC, clustering, UMAP, integration, and marker identification through a guided point-and-click interface.
Python-based single-cell analysis workflows are on the roadmap. Contact us if your team needs Scanpy support.
Reproducible bioinformatics workflows
Reproducibility shouldn't depend on whoever ran the analysis still being on the team. Bridge Horizon captures everything that went into a result, the pipeline version, parameters, reference, container image, and inputs, so any teammate can re-run it identically months or years later.
Pipelines are pinned to a specific version on every run, so an old analysis doesn't silently change when the pipeline does.
Every parameter, input file, and reference is recorded automatically. No lab notebook entries to maintain by hand.
When a reviewer, client, or auditor asks how a figure was made, you can show them the full chain in one click.
FAQ
Request a demo to see your data, analyses, and results in one workspace.
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