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写作与投稿
FL
FlowIO
维护者 K-Dense Inc. · 最近更新 2026年4月1日
FlowIO是一个lightweight Python 库 ，用于 reading 、 writing Flow Cytometry Standard (FCS) files。 解析 FCS metadata，extract event data，、 create new FCS files ，支持 minimal dependencies。
原始来源
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/flowio
- 维护者
- K-Dense Inc.
- 许可
- BSD-3-Clause license
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- FlowIO是一个lightweight Python 库 ，用于 reading 、 writing Flow Cytometry Standard (FCS) files. Parse FCS metadata，extract event data，、 create new FCS files ，支持 minimal dependencies. 库 supports FCS versions 2.0，3.0，、 3.1，making it ideal ，用于 backend services，data pipelines，、 basic cytometry file operations。
- flow_data = FlowData('experiment.fcs')。
原始文档
SKILL.md 摘录
When to Use This Skill
This skill should be used when:
- FCS files requiring parsing or metadata extraction
- Flow cytometry data needing conversion to NumPy arrays
- Event data requiring export to FCS format
- Multi-dataset FCS files needing separation
- Channel information extraction (scatter, fluorescence, time)
- Cytometry file validation or inspection
- Pre-processing workflows before advanced analysis
Related Tools: For advanced flow cytometry analysis including compensation, gating, and FlowJo/GatingML support, recommend FlowKit library as a companion to FlowIO.
Basic File Reading
from flowio import FlowData
## Access basic information
print(f"FCS Version: {flow_data.version}")
print(f"Events: {flow_data.event_count}")
print(f"Channels: {flow_data.pnn_labels}")
适用场景
- FCS files requiring parsing 或 metadata extraction。
- Flow cytometry data needing conversion to NumPy arrays。
- Event data requiring export to FCS format。
- Multi-数据集 FCS files needing separation。
不适用场景
- Do not treat this catalog entry as substitute ，用于 full upstream workflow。
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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