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flowio

Parse FCS files and extract event data as NumPy arrays or CSV.

4|1|Updated Jun 18, 2025
Search Tags:#metadata#csv#numpy#data-extraction#flowio#fcs#flow-cytometry
One-click install
npx skills add https://github.com/HolobiomicsLab/Toolomics --skill flowio-holobiomicslab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: flowio
Source: https://github.com/HolobiomicsLab/Toolomics/tree/main/mcp_host/skills/scientific-skills/scientific-skills/flowio
Command: npx skills add https://github.com/HolobiomicsLab/Toolomics --skill flowio-holobiomicslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

FlowIO standardizes access to Flow Cytometry Standard (FCS) files, enabling researchers and developers to parse metadata, extract event data as NumPy arrays, and convert or export results for downstream analysis.

Core Features & Use Cases

  • Read and parse FCS metadata and event data from FCS files
  • Extract event data as NumPy arrays and export to CSV or DataFrame
  • Create new FCS files with minimal dependencies and customizable TEXT metadata
  • Support for FCS versions 2.0, 3.0, and 3.1 for broad compatibility
  • Suitable for backend services, data pipelines, and lightweight cytometry workflows

Quick Start

Run FlowIO to read an FCS file and export its events as a NumPy array.

Frequently Asked Questions about flowio

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I parse FCS flow cytometry files and export event data to NumPy arrays?▼

This Skill parses FCS files and extracts event data and metadata, outputting the events as NumPy arrays or CSV for downstream analysis. It supports FCS versions 2.0, 3.0, and 3.1.

What is the best way to extract metadata from flow cytometry standard files for data pipelines?▼

The best way to extract metadata from flow cytometry standard files is using a parser that reads the FCS TEXT segments and channel information without requiring heavy external dependencies for pipeline integration.

Does this FCS parser support older flow cytometry file versions like 2.0?▼

This FCS parser supports flow cytometry file versions 2.0, 3.0, and 3.1 for broad compatibility. It reads both metadata and event data from legacy and modern FCS datasets.

Can I create new FCS files with custom metadata for cytometry workflows?▼

Yes, you can create new FCS files with customizable TEXT metadata and minimal dependencies. This supports lightweight cytometry workflows and backend data generation tasks.

How do I convert FCS datasets to CSV for analysis?▼

To convert FCS datasets to CSV, parse the flow cytometry file to extract event data as a NumPy array or DataFrame, then export the structured data directly to CSV format.

Do I need external libraries to read flow cytometry data in backend services?▼

No, you do not need heavy external libraries to read flow cytometry data. This parser operates with minimal dependencies, making it ideal for backend services and data pipelines.

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