Parse FCS 2.0, 3.0, and 3.1 files into NumPy arrays and metadata.
npx skills add https://github.com/ovachiever/droid-tings --skill flowio-ovachiever
Please help me install this Agent Skill. Skill: flowio Source: https://github.com/ovachiever/droid-tings/tree/main/skills/flowio Command: npx skills add https://github.com/ovachiever/droid-tings --skill flowio-ovachiever
FlowIO provides a lightweight interface to read Flow Cytometry Standard (FCS) files, extract events, metadata, and convert data into usable NumPy arrays for downstream analyses.
Use cases include flow cytometry data preprocessing, batch analysis, and integration with downstream ML pipelines.
Load an FCS file, extract events as a NumPy array, and export basic metadata to JSON.
High-intent search queries and answers about installing and using this skill.
Parse FCS files using FlowIO to extract event data as NumPy arrays. FlowIO reads FCS 2.0, 3.0, and 3.1 formats, accesses channel metadata (scatter, fluorescence, time), and supports compressed and multi-dataset files for downstream preprocessing and analysis.
Yes. FlowIO extracts events from FCS files and converts them to NumPy arrays, which you can then export to CSV or DataFrame formats for integration with data analysis pipelines and statistical tools.
FlowIO extracts TEXT and ANALYSIS metadata sections, channel information (names and ranges), and event counts from FCS files. Access metadata dictionaries and channel details to validate data quality and configure downstream analyses.
Yes. FlowIO reads multi-dataset FCS files and separates datasets during parsing, enabling batch analysis of multiple flow cytometry experiments in a single file without manual dataset extraction.
FlowIO is designed for batch analysis of FCS files with tools for data validation, anonymization, and conversion to NumPy arrays. Parse multiple datasets and export metadata to automate preprocessing in ML pipelines and analytical workflows.
FlowIO supports compressed FCS files as part of its standard parsing workflow. Ensure your environment has the required dependencies (numpy, pillow) installed; compression support depends on the FCS file's encoding specification.
Yezez9Parse FCS files into NumPy arrays and metadata.
K-Dense-AIParse FCS files and extract event data as NumPy arrays.
SciMate-AIParse FCS files and convert event data to NumPy arrays or CSV.
Zeyuyang-0420Parses FCS files to extract metadata and event data for analysis.
