bio-workflows-imc-pipeline
End-to-end imaging mass cytometry workflow from raw acquisitions to spatial cell analysis. Orchestrates image preprocessing, segmentation, phenotyping, and spatial statistics. Use when analyzing imaging mass cytometry data end-to-end.
npx skills add BioTender-max/awesome-bio-agent-skills --skill imc-pipeline --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: Cellpose 3.0+, anndata 0.10+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, scvi-tools 1.1+, squidpy 1.3+, steinbock 0.16+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Imaging Mass Cytometry Pipeline **"Process my imaging mass cytometry data from images to spatial analysis"** → Orchestrate image preprocessing (steinbock), cell segmentation (Cellpose), phenotyping (FlowSOM/scanpy), spatial neighborhood analysis (squidpy), and tissue community detection. ## Pipeline Overview ``` Raw MCD/TIFF Files ──> Image Processing ──> Cell Masks │ ▼ ┌─────────────────────────────────────────────┐ │ imc-pipeline │ ├─────────────────────────────────────────────┤ │ 1. Data Preprocessing (spillover, hot px) │ │ 2. Cell Segment
- Version Compatibility
- Pipeline Overview
- Complete steinbock Workflow
- Step 1: Setup and Preprocessing
- Step 2: Cell Segmentation
- Step 3: Single-cell Quantification
- Complete Python Workflow
- R Alternative (imcRtools)
- QC Checkpoints
- Workflow Variants
- High-plex Panels (40+ markers)
- Tumor Microenvironment Analysis
- Related Skills
Initialize steinbock project steinbock preprocess imc \ Hot pixel filtering steinbock preprocess imc hotpixel \ Create nuclear and membrane channels steinbock preprocess mosaic \ Using Cellpose steinbock segment cellpose \ steinbock segment mesmer \ Extract intensities
What does the bio-workflows-imc-pipeline skill do?
End-to-end imaging mass cytometry workflow from raw acquisitions to spatial cell analysis. Orchestrates image preprocessing, segmentation, phenotyping, and spatial statistics. Use when analyzing imaging mass cytometry data end-to-end.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill imc-pipeline --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.