How does FlowIO handle data preprocessing?

By default, FlowIO automatically applies gain scaling and logarithmic transformations (PnE) to raw data during the parsing process, though these can be disabled if raw event values are required.

Is FlowIO suitable for large-scale data pipelines?

Absolutely. Its lightweight design, minimal dependencies, and native NumPy integration make it ideal for high-throughput bioinformatics pipelines and backend data services.

What FCS versions does FlowIO support?

FlowIO supports FCS versions 2.0, 3.0, and 3.1, covering the vast majority of modern and legacy flow cytometry data formats used in clinical and research settings.

Can I use FlowIO to create new FCS files from scratch?

Yes, FlowIO includes a create_fcs utility that allows you to generate valid FCS 3.1 files from NumPy arrays, custom channel names, and user-defined metadata.

Does it support files with multiple datasets?

Yes, the skill provides specific workflows for detecting and reading multiple datasets within a single FCS container using the dedicated read_multiple_data_sets function.

FlowIO FCS File Handler

Name: FlowIO FCS File Handler
Author: K-Dense-AI

byK-Dense-AI

•

3,718

•

数据科学与机器学习

Parses and manages Flow Cytometry Standard (FCS) files, enabling seamless conversion to NumPy arrays and metadata extraction for bioinformatics workflows.

FlowIO is a lightweight Python utility designed for the high-performance handling of Flow Cytometry Standard (FCS) files versions 2.0 through 3.1. It empowers researchers and data scientists to programmatically extract event data into NumPy arrays, manage complex metadata segments, and generate new FCS files from scratch. Ideal for building automated data pipelines or preprocessing cytometry data for machine learning models, FlowIO handles technical nuances like gain scaling, logarithmic transformations, and multi-dataset file structures with minimal dependencies.

主要功能

01High-speed conversion of event data to NumPy arrays for scientific analysis

02Full support for FCS versions 2.0, 3.0, and 3.1 file parsing and creation

03Integrated preprocessing for gain scaling and logarithmic transformations

04Advanced metadata extraction from TEXT and ANALYSIS file segments

05Robust support for multi-dataset FCS files and offset discrepancy correction

063,718 GitHub stars

使用场景

01Automating the preprocessing of large flow cytometry datasets for machine learning training

02Converting proprietary instrument data into CSV or DataFrames for custom visualization

03Validating and repairing corrupted FCS files with offset or header discrepancies

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add k-dense-ai/claude-scientific-skills flowio

For use in Claude.ai and ChatGPT

Download Skill