Tools

Software we build and ship.

Open-source scientific software from our lab, built to be used, audited, and extended by other researchers.

Open Source
Python package · scRNA-seq

msep

Multi-scale entropy profiling for single-cell transcriptomics.

Multi-Scale Entropy Profiling integrates per-cell Shannon entropy with across-cells coefficient of variation (CV), decomposed by biological pathway, to characterise population-level transcriptomic coordination in single-cell RNA-seq data. The framework reveals states invisible to single-scale analyses — such as populations that are individually diverse (high per-cell entropy) yet collectively disciplined (low across-cells CV) — and is applicable to any cancer type or cellular system.

  • Pathway-decomposed entropy, not a single global score
  • 33,000+ curated gene sets via MSigDB out of the box
  • Bootstrap confidence intervals reported for every estimate
  • Built for standard scRNA-seq workflows
pip install msep
Open Source
Clinical decision support

VUS Lens

Ancestry-aware variant interpretation, built to expose the gaps.

VUS Lens is a deterministic ACMG classification engine that does something most variant interpretation tools do not: it audits whether the evidence behind a call is actually strong enough for the patient's ancestry, rather than assuming Western-centric reference databases generalize across populations. Its reasoning layer is built with Claude.

  • Deterministic ACMG rule engine — same input, same output, every time
  • Ancestry-confidence auditing surfaces where reference data falls short
  • Validated against 1,277 known-pathogenic variants with zero false-benign calls
  • Reasoning layer built with Claude
Clinical decision support

VUS Pipeline

Transparent, ACMG-compliant variant classification for the clinic.

VUS Pipeline is a production-grade clinical decision-support system that applies the ACMG/AMP 2015 + ClinGen SVI + Tavtigian point framework deterministically, gathers evidence in parallel from authoritative sources, and layers advisory mechanistic interpretation on top — every step traceable and source-cited. The class is set by rules, never by an LLM.

  • Deterministic ACMG / SVI decision engine (Tavtigian points)
  • 8-layer parallel evidence collection (gnomAD v4, ClinVar, SpliceAI, ClinGen, CIViC)
  • Advisory mechanistic interpretation layer — never changes the class
  • Source-cited reports (HTML / PDF / DOCX) with a citation-verified assistant