bio-workflows-imc-pipeline

What problem does it solve?

Imaging mass cytometry experiments generate large, complex pipelines that require coordinating preprocessing, segmentation, phenotyping, and spatial analysis. This Skill provides an end-to-end blueprint to streamline IMC workflows from raw data to spatial insights.

Core Features & Use Cases

• End-to-end IMC pipeline: Orchestrates preprocessing (spillover correction, hot pixel removal), segmentation (Cellpose/Mesmer), single-cell quantification, phenotyping, and spatial statistics.
• Reproducible workflows: Uses a Python-based toolchain (steinbock) and explicit dependencies to ensure reproducibility across samples.
• Use Case: Process a multi-sample IMC study to derive cell-type maps and spatial neighborhoods for tumor microenvironment analysis.

Quick Start

Run the IMC pipeline on your MCD files to produce segmented cells, annotated phenotypes, and spatial interaction results.