Lineage Tracing (bioSkills)

A Claude Code skill that builds clonal phylogenies from single-cell lineage recorders — CRISPR/Cas9 scars, static expressed barcodes, or somatic mitochondrial mutations — and joins them to transcriptomic state.


Type	Claude Skill
Supplier	GPTomics bioSkills (community OSS, MIT)
Availability	GA — part of the bioSkills collection
Pricing	Free / OSS (MIT) — Cassiopeia, CoSpar, Startle and scanpy are separately installed OSS
Capabilities	Read/Write — Claude runs the skill’s workflow locally (Python), not as an MCP tool
Verified	works · 2026-08-03
Security	cleared · 2026-08-03 — GPTomics/bioSkills MIT confirmed, provenance matches, no advisories

How to install

bioSkills is not an npm package — skills are plain markdown/code read directly by the agent. Clone the repo, then either run the installer for the whole category or copy the single skill directory.

Claude Code — clone and install via the bundled script:
```
git clone https://github.com/GPTomics/bioSkills
cd bioSkills
./install-claude.sh --categories "single-cell"
```
The installer copies matching skills into ~/.claude/skills/ (default target). Use ./install-claude.sh --list to preview the skills first.
Claude Code / other agents — copy just this one skill:
```
cp -r bioSkills/single-cell/lineage-tracing ~/.claude/skills/
```
(run from inside your clone — the previous step left you in bioSkills/; otherwise replace bioSkills/ with the absolute path of your clone). Install the Python stack on first use:
```
pip install "cospar>=0.3" "scanpy>=1.10" "numpy>=1.26"
pip install git+https://github.com/YosefLab/Cassiopeia@master
```
Cassiopeia must come from GitHub, not PyPI: the skill targets Cassiopeia 2.0+, but the PyPI distribution cassiopeia-lineage is still at 1.0.4 (checked 2026-08-01), so pip install cassiopeia-lineage gets you the older API.

What it does

Five stages from recorder reads to a fate-annotated tree:

Assay selection — CRISPR/Cas9 scars, static expressed barcodes (LARRY, CellTag), combinatorial tags, or somatic mtDNA mutations, each with different resolution and dropout behaviour.
Character matrix construction — resolve UMIs, align reads, call alleles, and convert to phylogenetic characters.
Solver selection and tree reconstruction — Cassiopeia 2.0+ parsimony and distance solvers (VanillaGreedy, ILP, Hybrid, NeighborJoining) plus Startle for scar data with homoplasy.
Robustness assessment — compare topologies across solvers with Robinson–Foulds distance and triplets-correct scores, rather than trusting a single reconstruction.
Clone–state integration — CoSpar 0.3+ to map fate bias from paired clonal and transcriptomic data.

Quality thresholds the skill applies — drop cells below ~10 UMIs per cell (noise dominates allele calls); drop cells missing more than ~50% of characters (insufficient phylogenetic signal); count a character as informative only if its states appear in more than one cell; and require barcode library complexity far exceeding the founder population so collisions do not fabricate clones.

Primary use cases: developmental and tumor-progression phylogenies, clonal fate-bias analysis, mtDNA-based clone grouping in human samples.

Notes

Distributed as a SKILL.md (plus reference material) in the bioSkills collection — Claude executes the workflow locally rather than as an MCP server. The upstream skill front-matter name is bio-single-cell-lineage-tracing (tool_type: python, primary_tool: Cassiopeia); if invoked as a namespaced plugin command it resolves under the bioSkills plugin, not as a bare /lineage-tracing. Homoplasy — the same scar arising independently in unrelated cells — and allele dropout are the two failure modes the skill spends most of its guidance on, since both produce confidently wrong topologies. Distinct from expression-based pseudotime: scVelo and CellRank infer trajectories from RNA dynamics, whereas this skill uses a physical heritable recorder, and it treats a state-based fate call as something to be validated against clonal evidence rather than assumed. Upstream directory: single-cell/lineage-tracing.

Sources

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