Run bioinformatics analyses using Lobster AI - single-cell RNA-seq, bulk RNA-seq, literature mining, dataset discovery, quality control, and visualization. Use when analyzing genomics data, searching for papers/datasets, or working with H5AD, CSV, GEO/SRA accessions, or biological data. Requires lobster-ai package installed.
Lobster AI is a bioinformatics platform that combines specialized AI agents with open-source tools to analyze multi-omics data through natural language.
Use Lobster when the user asks to:
Lobster must be installed and configured:
# Check if Lobster is installed
which lobster
# If not installed:
uv pip install lobster-ai
lobster init --help #to see non-interactive
Lobster requires an LLM provider (Ollama, Anthropic, or AWS Bedrock).
Before running any analysis, always verify Lobster is ready:
lobster config-test --json
Returns structured JSON:
{
"valid": true,
"env_file": "/path/to/.env",
"checks": {
"llm_provider": {"status": "pass", "provider": "bedrock", "message": "Connected"},
"ncbi_api": {"status": "pass", "has_key": true, "message": "Connected"},
"workspace": {"status": "pass", "path": "/path/to/workspace", "message": "Writable"}
}
}
This command validates:
Expected output for a working setup:
✅ LLM Provider: bedrock (connected)
✅ NCBI API: Connected (with API key)
✅ Workspace: Writable
✅ Configuration Valid
If config-test fails:
| Error | Solution |
|---|---|
| No LLM provider configured | Run lobster init |
| Ollama server not accessible | Start Ollama: ollama serve |
| Ollama: No models installed | After asking user - Install a model: ollama pull gpt-oss:20b |
| Anthropic/Bedrock API error | Check API key validity in .env |
| NCBI API not configured | Add NCBI_API_KEY to .env (optional) |
| Workspace not writable | Check directory permissions |
Quick status checks:
# Show configuration values (masked)
lobster config-show
# Show subscription tier and available agents
lobster status
# Single query (non-interactive)
lobster query "<natural language request>"
# With custom workspace
lobster query --workspace /path/to/workspace "<request>"
# With reasoning mode (for complex tasks)
lobster query --reasoning "<request>"
Lobster supports conversation continuity via --session-id, enabling follow-up questions that reference previous context either by setting sessin-id to latest or a string of your choice:
# default session
lobster query "Search PubMed for CRISPR papers"
# Output: Session: session_20241208_150000 (use --session-id latest for follow-ups)
# then follow up with
lobster query --session-id latest "Download the first dataset from that search"
#or use custom session id
lobster query --session-id "crispr_search_1" "Search PubMed for CRISPR papers"
#follow up with
lobster query --session-id "crispr_search_1" "show me metadata from the first paper"
Best practices:
--session-id latest for follow-up queriessession_*.json--workspace for related queries to maintain contextWorkspace-based sessions:
# Project 1: Cancer research
lobster query --workspace ~/cancer-project "Search for breast cancer datasets"
lobster query --workspace ~/cancer-project --session-id latest "Download the best one"
# Project 2: Immunology (separate session)
lobster query --workspace ~/immuno-project "Search for T cell datasets"
lobster query --workspace ~/immuno-project --session-id latest "Analyze that"
Single-cell analysis:
lobster query "Download GSE109564 and perform quality control"
lobster query "Cluster the dataset and find marker genes"
lobster query "Create UMAP visualization colored by cell type"
Literature mining:
lobster query "Search PubMed for CRISPR screens in cancer"
lobster query "Find papers about CAR-T therapy and extract their GEO datasets"
lobster query "Get the full text and methods section for PMID:12345678"
Dataset discovery:
lobster query "Search GEO for single-cell pancreatic beta cell datasets"
lobster query "Validate GSE200997 metadata for required fields: cell_type, tissue"
lobster query "Download SRA dataset SRP123456"
Data analysis:
lobster query "Load counts.csv and run differential expression analysis"
lobster query "Perform batch correction on the loaded dataset"
lobster query "Generate volcano plot for DE results"
Quality control:
lobster query "Assess quality metrics for the loaded dataset"
lobster query "Filter cells with <200 genes or >8000 genes"
lobster query "Identify doublets using scrublet"
Lobster outputs are saved in the workspace directory (default: .lobster_workspace/):
Key files to check:
*.h5ad - Processed datasets (AnnData format)*.html - Interactive visualizations*.png - Static plots for publications*.csv - Exported data tables*.json - Metadata and provenanceTo read results:
# List workspace files
ls -lh .lobster_workspace/
# Read specific outputs
cat .lobster_workspace/analysis_summary.json
Example 1: Analyze dataset and extract results
# Step 1: Run analysis
lobster query --session-id "gse109564" "Download GSE109564, run QC, and cluster cells"
# Step 2: Check outputs
ls .lobster_workspace/*.h5ad
ls .lobster_workspace/*.html
# Step 3: Extract specific data
lobster query --session-id "gse109564" "Export cluster markers to CSV"
# Step 4: Use results in your code
# Results are now in .lobster_workspace/markers.csv
Example 2: Literature mining workflow
# Step 1: Find papers
lobster query "Search for papers about immune checkpoint inhibitors in melanoma"
# Step 2: Extract datasets
lobster query "Extract all GEO dataset IDs from the cached papers"
# Step 3: Validate datasets
lobster query "Check which datasets have cell_type and treatment metadata"
# Step 4: Download best match
lobster query "Download the dataset with most samples"
Export reproducible notebooks:
lobster query "Export the analysis pipeline as a Jupyter notebook"
# Creates a Papermill-compatible notebook in workspace
Workspace management:
# Use custom workspace per project
lobster query --workspace ./project1-data "Analyze counts.csv"
lobster query --workspace ./project2-data "Analyze other-counts.csv"
Provider switching (if multiple LLM providers configured):
# Use specific provider
lobster query --provider ollama "Run expensive analysis" # Free local
lobster query --provider anthropic "Quick task" # Fast cloud
Command not found:
which lobsteruv pip install lobster-ailobster initRate limit errors:
ollama pull llama3:8b-instruct && export LOBSTER_LLM_PROVIDER=ollamaAnalysis errors:
ls .lobster_workspace/cat ~/.lobster/.session.jsonlobster query --reasoning "<request>"No output files:
lobster query "show workspace info".lobster_workspace/--reasoning flagThis Skill is compatible with:
For issues or questions: https://github.com/the-omics-os/lobster-local/issues