Data & ReproProteomics & MetabolomicsFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction

spatial-proteomics

Maintainer FreedomIntelligence · Last updated April 1, 2026

spatial-proteomics.

OpenClawNanoClawAnalysisReproductionspatial-proteomicsopenclaw medical skillsadditional scientific toolsspatial

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/spatial-proteomics

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

adata = ad.read_h5ad('spatial_proteomics.h5ad').
sm.pp.combat(adata, batch_key='fov').

Source Doc

Excerpt From SKILL.md

Data Loading

import scimap as sm
import anndata as ad

## Manual gating approach

phenotype_markers = {
    'T_cell': ['CD3', 'CD45'],
    'B_cell': ['CD20', 'CD45'],
    'Macrophage': ['CD68', 'CD163'],
    'Tumor': ['panCK', 'Ki67']
}

sm.tl.phenotype_cells(adata, phenotype=phenotype_markers,
                      gate=0.5, label='phenotype')

## Clustering-based phenotyping

sm.tl.cluster(adata, method='leiden', resolution=1.0)

Use cases

Use spatial-proteomics in research workflows aligned with this subject area.
Follow the upstream documentation for the full working procedure.

Not for

Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

spatial-transcriptomics/spatial-neighbors - Spatial graph construction
spatial-transcriptomics/spatial-domains - Domain identification
imaging-mass-cytometry/phenotyping - IMC-specific analysis

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