Helix — Deterministic, auditable genome-editing simulation (CRISPR/Prime/PCR)

Helix is a deterministic, auditable genome editing simulator and reporting system for pre-clinical, in-silico CRISPR, Prime, and PCR workflows — a computational system of record for genome editing design decisions.

Helix does not claim biological truth. It guarantees computational reproducibility, explicit modeling boundaries, and verifiable decision artifacts (reports, manifests, schema-versioned evidence bundles).

Pre-clinical, in-silico simulation only. See docs/positioning.md.

Migration note (veri-helix → helix-governance)

Helix is now published on PyPI as helix-governance (Python module namespace and CLI entrypoints are unchanged).

python -m pip uninstall -y veri-helix
python -m pip install -U helix-governance

Choose your path

• Try Helix quickly → First Run or docs/getting-started.md
• Evaluate auditability/reproducibility → docs/audit_walkthrough.md and docs/scientific_contract_v1.md
• Run the Public Validation Pack v1 → docs/validation/README.md
• Verify release receipts (trust model + receipts) → docs/reference_validation_bundle.md
• Enterprise proof dossier (security, threat model, signing, receipts) → docs/enterprise_proof/index.md
• Teams v0 blueprint (artifact store + run registry + RBAC) → docs/teams_v0.md
• Use CRISPR/Prime decision modeling → docs/edit_dag_overview.md (limitations: docs/model_limitations/crispr_edit_dag_limitations.md)
• Integrate in CI/headless lanes → docs/cli_headless.md and docs/trust_kit.md
• Hack on internals → docs/contributing.md (tests: tools/test.sh / tools/test.ps1)

First Run

Install, run a deterministic demo, and open the exported report:

python -m venv .venv
source .venv/bin/activate
pip install "helix-governance"

helix demo run --demo-id crispr --outdir out/demo_crispr --zip
python -m http.server --directory out/demo_crispr/reports 8000

Prime demo:

helix demo run --demo-id prime --outdir out/demo_prime --zip

Governance licensing (principle: authority, not bits)

• Helix is free to install/run (simulate + explore).
• Decision-grade assertions and signed bundles require an offline license file.
• Verification is always free + offline: helix verify <bundle_dir_or_zip> validates signatures and lineage, and never reads your local license.

Dynamic CRISPR simulation (resource-aware)

Copy/paste quickstart (Python API):

from helix.crispr.dynamic import CrisprDynamicSimConfig, simulate_crispr_dynamic

# Key mental model: `delivery` shapes Cas(t) (availability over time), not a static cut probability.
# `population.seed` makes the stochastic simulation reproducible.
cfg = CrisprDynamicSimConfig.from_yaml("""
time: {dt_h: 0.25, t_end_h: 48.0}
population: {n_cells: 2000, seed: 1}
delivery: {mode: RNP, params: {C0: 1.0}}
cas_kinetics: {k_deg: 0.35, k_dil: 0.0}
engagement: {k_eff: 0.55}
grnas: [{id: g1, abundance: 1.0, load_efficiency: 1.0}, {id: g2, abundance: 1.0, load_efficiency: 1.0}]
targets: [{id: t1, grna_id: g1, chr: chr1, pos: 1000, accessibility: 1.0}, {id: t2, grna_id: g2, chr: chr1, pos: 2000, accessibility: 1.0}]
ploidy: {loci: [{locus_id: t1, copies: 2, allele_accessibility: [1.0, 0.5]}, {locus_id: t2, copies: 2, allele_accessibility: [1.0, 1.0]}]}
measurement: {amplicons: [{id: amp1, chr: chr1, start: 900, end: 1100, locus_id: t1}]}
""")
result = simulate_crispr_dynamic(cfg)

print("edited_fraction(t1) =", result.edited_fraction("t1"))
print("edited_fraction(t2) =", result.edited_fraction("t2"))
print("amp1 truth =", result.measurement.amplicons[0].truth_counts)
print("amp1 observed =", result.measurement.amplicons[0].observed_counts)

Want the GUI? pip install "helix-governance[studio]" then run helix-studio.

Who this is for

• Genome editing researchers who need reproducible CRISPR/Prime outcome enumeration and comparisons
• Auditors/reviewers who need deterministic replays and verifiable artifacts
• Contributors building policies, verifiers, and visualization/reporting pipelines

Docs

• Docs & Playground: https://omniscoder.github.io/Helix/
• Studio strategy: docs/helix_studio_strategy.md
• Snapshot spec v1: docs/snapshot_spec_v1.md
• Full manual / product cookbook (legacy README): docs/product_manual.md