Can I convert FCS files to CSV using this skill?

Yes, the skill provides clear workflows to extract event data as NumPy arrays, which can then be easily converted to Pandas DataFrames and exported to CSV format.

Can I create new FCS files from scratch?

Absolutely. You can use the create_fcs function to generate valid FCS 3.1 files from NumPy arrays and define your own custom metadata and channel labels.

Which FCS versions does FlowIO support?

FlowIO supports FCS versions 2.0, 3.0, and 3.1, making it compatible with most modern and legacy cytometry instruments.

Does it handle files with multiple datasets?

Yes, FlowIO includes specific functionality to detect and read multi-dataset FCS files using the read_multiple_data_sets() utility.

Does FlowIO apply data preprocessing automatically?

By default, FlowIO applies standard gain scaling and logarithmic transformations (PnE) to the data, though users can access raw data by setting preprocess=False.

FlowIO (Flow Cytometry Data Handler)

Name: FlowIO (Flow Cytometry Data Handler)
Author: Sologa

bySologa

0•

Data Science & ML

Parses and generates Flow Cytometry Standard (FCS) files to facilitate cytometry data preprocessing and scientific analysis.

FlowIO is a specialized skill designed for handling Flow Cytometry Standard (FCS) files across versions 2.0, 3.0, and 3.1. It enables developers and researchers to seamlessly extract metadata, convert event data into NumPy arrays or DataFrames, and generate new FCS files from scratch. This skill is particularly valuable for bioinformatics pipelines, laboratory data processing, and preparing cytometry datasets for advanced machine learning or statistical analysis without the overhead of heavy dependencies.

Key Features

01Comprehensive metadata and channel information parsing

02Ability to create and export new FCS files with custom metadata

03Extraction of event data as NumPy arrays for scientific computing

04Support for FCS versions 2.0, 3.0, and 3.1

050 GitHub stars

06Advanced handling of multi-dataset files and offset discrepancies

Use Cases

01Automated validation and metadata inspection of large laboratory datasets

02Converting FCS files to CSV or Pandas DataFrames for batch analysis

03Preprocessing raw cytometry data for machine learning models

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sologa/codex-pipeline flowio

For use in Claude.ai and ChatGPT

Download Skill