bioanchor 0.1.0

Permanent archiving of Bayesian/MCMC analysis artifacts on Arweave

BioAnchor 🔬⛓️

Permanent, verifiable archiving of Bayesian/MCMC analysis artifacts on Arweave.

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The Problem

Bayesian and MCMC analyses in computational biology are nearly impossible to reproduce:

• Raw MCMC chains are large and rarely shared
• Zenodo, GitHub, and NCBI can delete or restrict data
• There is no standard for what constitutes a "reproducible" Bayesian analysis artifact
• Drug discovery and genomics data have provenance and audit requirements that no current tool addresses

The Solution

BioAnchor defines a minimal, standardised manifest of everything needed to verify and re-run a Bayesian analysis, then uploads it to Arweave — a decentralised storage network where data is permanent and immutable.

You do not upload raw data (privacy + cost). You upload:

• SHA-256 hash of input data (proof of what was used)
• MCMC configuration: sampler, chains, draws, seed, priors
• Posterior summary statistics (mean, SD, R̂, ESS)
• Software environment fingerprint

This is typically < 5 KB — negligible cost on Arweave.

The Arweave TX ID goes into your paper alongside the DOI. Anyone can verify the analysis, check convergence, and reproduce results with the same seed.

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Quick Start

pip install bioanchor[all]

With PyMC

import pymc as pm
from bioanchor import BioAnchor

with pm.Model() as model:
    alpha = pm.Normal("alpha", 0, 1)
    beta  = pm.HalfNormal("beta", 1)
    # ... your model ...
    idata = pm.sample(2000, random_seed=42)

ba = BioAnchor(wallet_path="wallet.json")

tx_id = ba.archive_pymc(
    idata=idata,
    model=model,
    seed=42,
    data=X,                                        # numpy array, hashed not uploaded
    data_description="TCGA-BRCA expression matrix (n=500, p=200)",
    data_source="TCGA",
    title="Sparse Bayesian regression for drug target identification",
    authors=["Your Name <[e-mail]>"],
    domain="drug_discovery",
    tags=["sparse-regression", "drug-target", "tcga"],
)

print(f"https://arweave.net/{tx_id}")
# → Add this URL to your Methods section

CLI

# Generate a manifest template
bioanchor init --output my_analysis.json

# Upload to Arweave (edit the template first)
bioanchor upload --manifest my_analysis.json --wallet wallet.json

# Verify an uploaded manifest
bioanchor verify xK9mP2abc...

# Check wallet balance
bioanchor balance --wallet wallet.json

Development / Testing (no wallet needed)

ba = BioAnchor(mock=True)   # uses MockUploader, prints fake TX ID
tx_id = ba.archive_pymc(idata, seed=42, data=X, title="Test")

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Manifest Format

The manifest is a small JSON file (~2–5 KB). This is the core scientific contribution of BioAnchor.

{
  "schema_version": "1.0",
  "bioanchor_version": "0.1.0",
  "created_at": "2026-04-16T09:00:00+00:00",
  "title": "Bayesian dose-response IC50 estimation",
  "authors": ["Author Name"],
  "analysis_type": "MCMC",
  "domain": "drug_discovery",
  "tags": ["dose-response", "ic50", "hill-equation"],
  "software": {
    "language": "Python 3.11.0",
    "packages": { "pymc": "5.9.0", "arviz": "0.18.0", "numpy": "1.26.0" }
  },
  "data": {
    "sha256": "de2fb170...",
    "description": "12-point IC50 curve (log10 μM, % activity)",
    "n_samples": 12,
    "n_features": 2,
    "source": "synthetic"
  },
  "mcmc": {
    "sampler": "NUTS",
    "n_chains": 4,
    "n_draws": 2000,
    "n_warmup": 1000,
    "seed": 42,
    "prior_spec": {
      "log_ic50": "Normal(mu=-0.3, sigma=1.0)",
      "hill_n":   "HalfNormal(sigma=2.0)"
    },
    "posterior_mean": { "log_ic50": -0.31, "ic50": 0.49, "hill_n": 1.79 },
    "posterior_std":  { "log_ic50": 0.09,  "ic50": 0.10, "hill_n": 0.21 },
    "r_hat":          { "log_ic50": 1.001, "ic50": 1.001, "hill_n": 1.003 },
    "ess_bulk":       { "log_ic50": 892.0, "ic50": 887.0, "hill_n": 755.0 },
    "divergences": 0,
    "acceptance_rate": 0.93
  }
}

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Why Arweave?

Storage	Permanent?	Immutable?	Decentralised?
GitHub	✗ (account deletion)	✗	✗
Zenodo	✗ (operator control)	✗	✗
IPFS	✗ (requires pinning)	✓	✓
Arweave	✓ (mathematical guarantee)	✓	✓

Arweave's endowment model guarantees storage for a minimum of 200 years. A 5 KB manifest costs ~$0.0001 USD to archive permanently.

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Arweave Wallet Setup

1. Go to arweave.app and generate a wallet
2. Download the JWK JSON file (wallet.json)
3. Fund with a small amount of AR (~0.01 AR is enough for thousands of uploads)
4. Use bioanchor balance --wallet wallet.json to check

For testnet experimentation, use Irys devnet.

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Supported Integrations

Framework	Status
PyMC 5.x	✅ Full integration
ArviZ	✅ (via PyMC)
Stan/CmdStanPy	🔜 Planned
NumPyro	🔜 Planned
R (rstan)	🔜 Planned

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Citing This Tool

If you use BioAnchor in your research, please cite:

[Paper citation — in preparation]

And add to your Methods section:

"MCMC analysis artifacts (manifest, posterior summary, and software environment) were permanently archived on the Arweave network using BioAnchor v0.1.0 (TX ID: https://arweave.net/YOUR_TX_ID)."

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License

MIT License. See LICENSE.