数据与复现生物信息与基因组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现

bio-imaging-mass-cytometry-data-preprocessing

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Load and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD files or preparing images for segmentation.

OpenClawNanoClaw分析处理复现实验bio-imaging-mass-cytometry-data-preprocessing🧬 bioinformatics (gptomics bio-* suite)bioinformatics — immunoinformatics & flow cytometryload

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-imaging-mass-cytometry-data-preprocessing

维护者: FreedomIntelligence
许可: MIT
最近更新: 2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

CLI：steinbock preprocess ，用于 automated IMC preprocessing pipeline。
Preprocess my imaging mass cytometry data" → Load MCD files，apply hot pixel removal，channel cropping，、 signal normalization to prepare multiplexed images ，用于分割、 analysis. CLI：steinbock preprocess ，用于 automated IMC preprocessing pipeline。
steinbock preprocess imc \ --mcd raw/*.mcd \ --panel panel.csv \ -o img。

原始文档

SKILL.md 摘录

panel.csv

channel,name,keep,ilastik 1,DNA1,1,1 2,CD45,1,1 3,CD3,1,0 4,CD8,1,0 5,CD4,1,0


## Python-Based Loading

```python
import readimc
import numpy as np
from pathlib import Path

## Read MCD file

mcd_file = Path('acquisition.mcd')
with readimc.MCDFile(mcd_file) as mcd:
    # List acquisitions
    for acquisition in mcd.acquisitions:
        print(f'Acquisition: {acquisition.id}')
        print(f'  Channels: {len(acquisition.channel_metals)}')
        print(f'  Size: {acquisition.width} x {acquisition.height}')

    # Load specific acquisition
    acq = mcd.acquisitions[0]
    img = mcd.read_acquisition(acq)  # Returns (C, H, W) array

    # Channel names
    channel_names = acq.channel_names