Bio Imaging Mass Cytometry
Imaging mass cytometry 与多重组织空间表型 skill。用于 IMC、MIBI、CODEX 或多重 IF 的通道 QC、热像素处理、细胞分割、marker 表型、邻域图、空间相互作用和 ROI 级报告。
Install
$ agentstack add skill-onescience-ai-oneskills-imaging-mass-cytometry ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Imaging Mass Cytometry 与空间表型
使用边界
用于多重组织成像中的细胞级表型和空间关系。若任务只是通用显微图像分割，读取 ../bioimage-segmentation/SKILL.md；若是 WSI tile 级病理分析，读取 ../digital-pathology-wsi/SKILL.md。
可复用资源
onescience-coder/assets/bio_cell_imaging_templates/imc_analysis_plan.yaml：ROI、marker panel、preprocessing、segmentation、phenotyping 和 spatial tests 模板。references/imc_spatial_analysis.md：IMC/MIBI 预处理、QC、分割、表型和空间统计方法。
推荐流程
- 明确图像来源：MCD/TIFF/OME-TIFF、ROI、像素大小、channel-marker 映射。
- 预处理：hot pixel、spillover/crosstalk 检查、background、normalization、tissue mask。
- 分割：nuclear/cytoplasm membrane marker、Cellpose/Mesmer/classical watershed，输出 cell mask。
- 表型：按 marker panel 聚类或规则赋型，记录 marker thresholds 和 cell type confidence。
- 空间分析：邻域图、cell-cell adjacency、Ripley/nearest neighbor、neighborhood enrichment、区域比较。
- 输出：cell table、mask、ROI QC、phenotype table、spatial interaction table 和可审阅图。
交接物
bio_task_family: cell-imaging-cytometry
cell_task: imaging-mass-cytometry
image_inputs:
marker_panel:
roi_metadata:
preprocessing:
segmentation:
phenotyping:
spatial_statistics:
expected_outputs:
execution_entry:禁止事项
- 不要在没有 cell mask QC 的情况下解释空间邻域。
- 不要把 marker spillover 或背景高通道当作真实表达。
- 不要忽略 ROI、batch、抗体 panel 版本对空间统计的影响。
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: onescience-ai
- Source: onescience-ai/OneSkills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.