Parse and write FCS files into NumPy arrays or CSV.
npx skills add https://github.com/fuzzy-dynamics/strings --skill flowio-fuzzy-dynamics
Please help me install this Agent Skill. Skill: flowio Source: https://github.com/fuzzy-dynamics/strings/tree/main/packages/skills/flowio Command: npx skills add https://github.com/fuzzy-dynamics/strings --skill flowio-fuzzy-dynamics
Flow cytometry data often comes in FCS files requiring reliable parsing and conversion to analysis-ready formats such as NumPy arrays or CSV. This skill provides robust tools to read, interpret, and write FCS data across versions 2.0, 3.0, and 3.1, enabling smooth integration into data pipelines.
Load an FCS file with FlowIO and retrieve a 2-D array of events along with channel names for downstream analysis.
High-intent search queries and answers about installing and using this skill.
You can parse FCS flow cytometry files to NumPy arrays or CSV by loading the file with FlowData, which extracts event data and channel labels for downstream analysis. The API supports FCS versions 2.0, 3.0, and 3.1.
Yes, you can write new Flow Cytometry Standard files from arrays using the create_fcs utility. It preserves or extends metadata to ensure reproducible analyses and exports within your data pipelines.
The best way to handle multi-dataset FCS files is using the read_multiple_data_sets utility. It processes complex workflows by extracting metadata and event data across multiple datasets within a single FCS file.
Yes, this FCS parser supports flow cytometry file versions 2.0, 3.0, and 3.1. It reliably reads TEXT metadata, extracts channel information, and handles event data across all these versions.
You extract metadata and channel labels from an FCS file by loading it with the FlowData API. This provides direct access to TEXT metadata, channel information, and event data for robust data extraction.
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