Ask biological questions
Explore your data with project-aware AI assistance and structured scientific guidance.
scRNA-agent / Researcher-directed discovery
From single-cell data to biological insight.
scRNA-agent is an AI-guided scientific analysis application that helps researchers process, annotate, visualize and explore single-cell RNA-seq data using established bioinformatics tools.
Free 7-day research beta after email verification. No credit card needed. Windows download pending final acceptance.
A CLOSER LOOK. A CLEARER QUESTION.
◉ Local scientific computation◇ Your data, under your control↗ Guided by science. Directed by you.
01 / Meet the first agent
From Lab Agent Works · Research betaSingle-cell RNA-seq
scRNA-agent
Single-cell RNA-seq
analysis for biologists.
AutoRun is a starting point. Your next question takes it further.
AutoRun generates an initial annotated dataset. Continue investigating biological questions interactively with Codex, revise previous analysis decisions and generate additional scientific results.
Prefer a step-by-step approach? Guided Run keeps you involved in analysis decisions. Scientific computation and project storage stay local.
Get to know scRNA-agentRun the analysis locally
Use local R and Python environments while raw scientific data stay on your computer.
Keep a traceable record
Review figures, reports, and analysis artifacts in a project you control.
02 / Local by design
Your data stay close. Your analysis moves forward.
Raw matrices stay on your computer, where R and Python run the analysis. The protected Core provides maintained workflows and scientific guidance without needing your raw dataset.
On your computerLOCAL WORKSPACE
01
Your scientific data
Raw matrices & processed inputs
02
scRNA-agent workspace
Your question, context & decisions
03
R / Python analysis
Local scientific computation
04
Project outputs
Figures, tables, reports & provenance
Raw matrices stay on your computer. Scientific computation runs locally.
YOUR MODEL ACCESS
Your own AI provider supports reasoning and execution. Prompts and shared project context may leave your computer and are subject to that provider’s policies.
03 / From question to insight
A framework for the way you explore.
Move through single-cell analysis with guidance at each stage, and room to revisit decisions as the biology becomes clearer.
Start with the data
- Data intake
- Quality control
- Filtering
Assess & prepare
- Doublet detection
- Ambient RNA handling
- Dimensionality reduction
Resolve the biology
- Batch / integration assessment
- Clustering
- Annotation
Explore & communicate
- Differential analysis
- Pathway analysis
- Figures and reports
An adaptable framework, not a fixed pipeline. The steps and methods depend on the dataset and biological question.
Scientific capabilities
A dataset is the beginning of the investigation.
From cell identity to biological comparisons, build a scientific record you can review and reuse.
Screenshot previews are being prepared. The spaces below are placeholders, not scientific results.
Verified example forthcoming
Annotated UMAP
Explore cell populations and review cell-type annotations.
Verified example forthcoming
Markers & heatmaps
Examine marker expression to support annotation decisions.
Verified example forthcoming
Differential expression
Compare groups and inspect volcano plots in the context of your study.
Verified example forthcoming
Pathway enrichment
Investigate gene sets with GSEA enrichment figures.
Verified example forthcoming
Interactive Workbench
Ask follow-up questions and revisit analysis choices with Codex.
Verified example forthcoming
Reusable scientific outputs
Keep figures, reports and annotated datasets with your project.
Scientific results require researcher review. Method selection and interpretation depend on the dataset and study design.
Coming later
Short guides, from setup to discovery.
Demonstration videos are planned. No videos are available yet.
Installation and initial setup
Video forthcoming
From scRNA-seq data to annotated cells
Video forthcoming
Asking new biological questions after AutoRun
Video forthcoming
DE, GSEA and scientific plotting
Video forthcoming
05 / Purpose-built assistance
Scientific tools. Thoughtfully connected.
AutoRun & Guided Run
Generate an initial annotated dataset automatically, or work through analysis with researcher oversight.
Local R / Python execution
Run scientific tools in local environments, close to your data.
Interactive exploration with Codex
Ask new biological questions, revise earlier decisions and continue analyzing your annotated dataset.
Differential expression & enrichment
Investigate biological comparisons with differential expression, pathway enrichment and GSEA.
Reproducible figures and reports
Keep generated figures and reports connected to the analysis that produced them.
Reusable annotated datasets
Keep annotated datasets, figures and reports available for further investigation.
Local-first data handling
Your scientific data stay on your computer.
Raw matrices stay local. Project files remain under your control. The protected Core provides guidance without needing your raw dataset.
Your next biological question
Closer to your data.
Further in your research.
Meet scRNA-agent, the first tool from Lab Agent Works.