Public Data Access

Public Bioinformatics Data Access

Build a reproducible acquisition plan before downloading. Treat GEO, SRA/ENA, GDC, GTEx, and DepMap as independent providers behind one provider-neutral workflow. Do not require a provider-specific toolkit or machine-specific checkout.

Workflow

1. Clarify the dataset contract. Identify the provider, accession/project, release, modality, smallest useful data product, filters, target directory, expected scale, and downstream analysis.
2. Inspect before transfer. Use available MCP/connectors or official metadata endpoints to list releases, files, samples, sizes, and checksums. Do not start a bulk transfer during discovery.
3. Write a provider-neutral plan. Run scripts/public_data_plan.py init. Store the plan next to the future dataset as download-plan.json.
4. Validate and review. Run validate, show the user the resolved provider, transport, filters, limits, output location, and known size. For a large, paid, authenticated, or overwrite-capable job, confirm that the user's authorization covers this concrete transfer; ask only when it does not.
5. Select the adapter at runtime. Prefer an already available Wisp MCP tool for metadata and small queries. Prefer official HTTPS/FTP or provider clients for bulk files. Use an external project only when it is installed and record its version in the plan/manifest.
6. Acquire safely. Reuse existing valid files, resume partial transfers when supported, keep raw files immutable, and never place credentials in the plan.
7. Verify and hand off. Check expected files, byte sizes, checksums when available, and sample/file counts. Generate manifest.json with the script.

Provider routing

Read references/provider-routing.md before implementing or changing a provider adapter. DepMap-specific flags or release semantics must stay inside the DepMap adapter; they must not shape the common plan schema.

For GEO SOFT/Series Matrix parsing, sample metadata preparation, or ExpressionSet acquisition in an R workflow, read references/geokit.md. geokit is optional; ordinary GEO discovery does not require R or package installation.

Create and validate a plan

Resolve scripts/public_data_plan.py against this skill's directory (the use_skill result lists its path), and invoke that resolved script with a Python 3.10+ interpreter. Keep the working directory at the project root so relative plan/output paths belong to the project. The examples below abbreviate the script path; quote the resolved path when it contains spaces. In an SSH/WSL context, stage the helper there or use an existing copy in that context; a desktop skill path is not automatically available remotely.

python scripts/public_data_plan.py init \
  --provider geo \
  --identifier GSE12345 \
  --data-type series-matrix \
  --output-dir data/public/geo/GSE12345 \
  --plan data/public/geo/GSE12345/download-plan.json

python scripts/public_data_plan.py validate \
  data/public/geo/GSE12345/download-plan.json

Filters are provider-specific but encoded uniformly as repeated key=value pairs:

python scripts/public_data_plan.py init \
  --provider gdc \
  --identifier TCGA-BRCA \
  --data-type expression \
  --filter workflow_type="STAR - Counts" \
  --filter sample_type="Primary Tumor" \
  --max-files 20 \
  --transport gdc-client \
  --plan data/public/gdc/TCGA-BRCA/download-plan.json

The planner does not download data. It produces a reviewable contract. See references/download-plan-schema.md for the complete schema. Validation checks the plan structure; it does not probe URLs, enforce transfer limits, verify installed packages, or approve a pending transfer. The selected adapter must honor the plan's limits and resume behavior.

Generate a manifest

After acquisition:

python scripts/public_data_plan.py manifest \
  data/public/geo/GSE12345/download-plan.json \
  --scan-dir data/public/geo/GSE12345 \
  --output data/public/geo/GSE12345/manifest.json

Use SHA-256 for modest datasets and provider checksums for large archives. For very large datasets, --checksum none is acceptable only when official checksums or immutable object identifiers are recorded elsewhere.

Safety and reproducibility rules

• Default to overwrite=false, resume=true, and the minimum useful subset.
• Never translate an exploratory request into “download everything.”
• Keep provider metadata, query/filter payloads, release/version, transport, tool version, URLs/object identifiers, and validation results.
• Separate immutable source files from normalized/derived outputs.
• Do not treat a successful HTTP response as a valid dataset; verify content.
• Do not embed API keys, cookies, signed URLs, SSH keys, or bearer tokens.
• Use structured runs or a remote execution context for long transfers rather than extending an interactive shell timeout.
• If an adapter or connector cannot perform the requested transfer, stop after producing the validated plan and report the missing capability explicitly.

Wisp Science integration

• Discover the live connector/tool catalog instead of assuming exact MCP tool names; installations can expose different provider adapters.
• Use connectors for discovery and bounded queries, then official transfer mechanisms for large files.
• Keep outputs under the active project, normally data/public/<provider>/....
• Invoke the planner as a standalone CLI; no Python REPL helper loading is required. R-based acquisition can use geokit independently of the planner.
• Treat this skill as an acquisition/orchestration layer. Downstream QC, statistics, annotation, and visualization belong to other skills.