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flowio

Parse FCS files and extract events and metadata as NumPy arrays.

Updated Dec 17, 2025
Search Tags:#data analysis#file processing#flow cytometry#flowio#python library
One-click install
npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill flowio-robotlearning123
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: flowio
Source: https://github.com/robotlearning123/claude-scientific-skills/tree/main/scientific-skills/flowio
Command: npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill flowio-robotlearning123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires flowio, and includes scripts (resource) and references (resource) components.

What problem does it solve?

FlowIO skill unit addresses the complexities of working with Flow Cytometry Standard (FCS) files, streamlining the data processing for researchers and scientists.

Core Features & Use Cases

  • FCS File Parsing: Reads FCS files of versions 2.0, 3.0, and 3.1.
  • Data Extraction: Extracts events and metadata as NumPy arrays.
  • File Conversion: Converts FCS files to CSV/DataFrame format.
  • Use Case: This skill is perfect for preprocessing flow cytometry data in research environments, enabling quick access to raw data for analysis and visualization.

Quick Start

Use the flowio skill to read and process the FCS file 'flowcytometry_data.fcs'.

Frequently Asked Questions about flowio

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

FAQPage Schema
How do I parse FCS files from flow cytometry for data analysis?▼

To parse FCS files from flow cytometry, use the FlowIO Python library to read versions 2.0, 3.0, and 3.1, extracting events and metadata into NumPy arrays. This enables quick access to raw data for analysis.

Can I convert flow cytometry FCS files to a CSV or DataFrame format?▼

Yes, you can convert flow cytometry FCS files to CSV or DataFrame format. The process extracts events and metadata as NumPy arrays, enabling researchers to preprocess and manipulate raw data efficiently for visualization.

What is the best way to extract events and metadata from flow cytometry data?▼

The best way to extract events and metadata from flow cytometry data is using a dedicated Python library that parses FCS files and outputs NumPy arrays. This approach streamlines data extraction for biological and medical research workflows.

Does FlowIO support FCS file version 3.1 for biological research workflows?▼

Yes, FlowIO supports parsing FCS file versions 2.0, 3.0, and 3.1 for biological research workflows. It efficiently reads flow cytometry data and extracts the necessary events and metadata for analysis.

How do I preprocess raw flow cytometry data in Python for visualization?▼

To preprocess raw flow cytometry data in Python for visualization, parse FCS files to extract events and metadata into NumPy arrays or DataFrames. This prepares the raw data for immediate analysis and visualization tasks.

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