Parse FCS 2.0 to 3.1 files to extract event data and metadata.
npx skills add https://github.com/rubensliv/k-dense-ai --skill flowio-rubensliv
Please help me install this Agent Skill. Skill: flowio Source: https://github.com/rubensliv/k-dense-ai/tree/main/scientific-skills/flowio Command: npx skills add https://github.com/rubensliv/k-dense-ai --skill flowio-rubensliv
FlowIO solves the challenge of reading Flow Cytometry Standard (FCS) files, extracting event data as numerical arrays, and retrieving channel metadata for downstream analysis and data pipelines.
Process a sample.fcs file to extract event data and channel metadata and export to CSV.
High-intent search queries and answers about installing and using this skill.
FCS files are parsed by reading Flow Cytometry Standard v2.0 to v3.1 data to extract event arrays and TEXT metadata. This handles single- and multi-dataset files with robust error-handling mechanisms for downstream analysis.
Extracted flow cytometry events can be converted to NumPy arrays or exported to CSV and DataFrame formats. This enables seamless analytics and visualization within data pipelines.
Multi-dataset FCS files are supported with automatic channel typing and preprocessing options. The parser implements robust error handling across FCS versions 2.0, 3.0, and 3.1.
Extracting channel metadata is done using a parser that retrieves TEXT metadata and event data simultaneously. This allows direct integration into preprocessing steps for data pipelines.
No external dependencies are required to parse FCS v3.1 files. The parser operates independently to extract event data and metadata without additional libraries.
FCS file parsing may fail without proper error-handling mechanisms for multi-dataset configurations. Using a parser with robust preprocessing options ensures events are extracted correctly across versions.
Estrella-231Parse FCS 2.0–3.1 files to extract event data and metadata.
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