bio-imaging-mass-cytometry-phenotyping

lilinji/GeneTind-Life-Skills

SkillLoads cleanly

Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir),…

Scores
out of 100 · grade B+

2026-08-22

Works

40% of the score

100/100

Loads cleanly: valid frontmatter, required fields present, no dangling references.

Maintained

25% of the score

94/100

no commits in the last 12 weeks
no license file

Adopted

20% of the score

13/100

8 stars on the source repo.

Documented

15% of the score

91/100

1,886 words with worked examples.
Ships 2 bundled files.

Loads cleanly. Every structural check Claude Code needs to register this passed. Last commit today.

Install

npx skills add lilinji/GeneTind-Life-Skills/bio-imaging-mass-cytometry-phenotyping

What the check found

Every finding on this listing, and what each one means for whether it loads.
Finding	What it means
No license	The repository ships no license file, so the reuse terms are unclear.

What it says it does

Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.

Every number above came out of reading the file and its repository. Nothing is a judgement call, nothing is a model’s opinion, and nothing can be paid for. The full method is published. Source last committed 2026-08-21.

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