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flowio

Parse FCS files into NumPy arrays and metadata.

Updated Mar 10, 2026
Search Tags:#data extraction#bioinformatics#data parsing#numpy#flow cytometry#fcs files
One-click install
npx skills add https://github.com/Yezez9/Research-Agent --skill flowio-yezez9
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: flowio
Source: https://github.com/Yezez9/Research-Agent/tree/main/scientific-skills/flowio
Command: npx skills add https://github.com/Yezez9/Research-Agent --skill flowio-yezez9

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the process of reading, parsing, and extracting data from Flow Cytometry Standard (FCS) files, a common format in biological research.

Core Features & Use Cases

  • FCS File Parsing: Read metadata, channel information, and event data from FCS files (versions 2.0-3.1).
  • Data Extraction: Extract event data as NumPy arrays or convert to Pandas DataFrames.
  • File Creation: Generate new FCS files from processed data.
  • Use Case: You have a directory of FCS files from a recent experiment. Use this Skill to extract the event data for specific channels from each file and compile them into a single CSV for downstream analysis.

Quick Start

Use the flowio skill to read the file 'experiment.fcs' and print the number of events and channel names.

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 and extract flow cytometry event data as NumPy arrays?▼

You can parse Flow Cytometry Standard (FCS) files by reading metadata, channel information, and event data directly as NumPy arrays, supporting FCS versions 2.0 through 3.1 for flow cytometry data preprocessing and analysis.

Can I convert flow cytometry data from FCS files to a Pandas DataFrame or CSV?▼

Yes, flow cytometry data extracted from FCS files can be converted into Pandas DataFrames or compiled into a single CSV file to facilitate downstream analysis and data sharing.

What is the best way to read metadata and channel information from FCS files across different versions?▼

Reading FCS files across versions 2.0 to 3.1 allows you to extract both metadata and channel information, ensuring compatibility with flow cytometry data generated by various instrument software versions.

Does this FCS parsing approach work for creating new flow cytometry files from processed data?▼

Yes, beyond parsing existing data, this functionality supports generating new FCS files from processed event data, enabling you to save modified or filtered flow cytometry datasets.

Why do I need to extract event data from multiple FCS files for flow cytometry analysis?▼

Extracting event data from multiple FCS files is necessary to compile specific channel data from various experimental runs into a unified dataset, simplifying downstream bioinformatics analysis.

What are the limitations when parsing FCS files for flow cytometry data preprocessing?▼

Parsing is limited to Flow Cytometry Standard (FCS) file versions 2.0 through 3.1, meaning older or non-standard proprietary flow cytometry formats may not be supported for data extraction.

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