Parse FCS files into NumPy arrays, metadata, and channel information.
npx skills add https://github.com/robinbarvaag/poynt --skill flowio-robinbarvaag
Please help me install this Agent Skill. Skill: flowio Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/flowio Command: npx skills add https://github.com/robinbarvaag/poynt --skill flowio-robinbarvaag
This Skill simplifies the complex task of reading and processing Flow Cytometry Standard (FCS) files, enabling efficient data extraction and manipulation for biological research.
Use the flowio skill to read the file 'experiment.fcs' and print its event count.
High-intent search queries and answers about installing and using this skill.
Parsing FCS files extracts flow cytometry event data directly into NumPy arrays while reading metadata and channel information. It supports FCS versions 2.0 through 3.1 for data preprocessing.
Yes, flow cytometry data parsed from FCS files can be converted to CSV or Pandas DataFrames. Event data is first extracted as NumPy arrays and then transformed for further statistical analysis.
Yes, this FCS parsing approach supports older flow cytometry file versions ranging from 2.0 to 3.1. It successfully reads metadata, channel information, and event data across these versions.
The best way to create new FCS files is by generating them from processed NumPy array event data. This allows you to save filtered flow cytometry events back into the standard format.
Filter flow cytometry events by extracting specific channel data from the parsed NumPy arrays. You can apply criteria to the event data and export the filtered results for further statistical analysis.
galeepParse FCS files and preprocess event data with Python.
mkurmanParse FCS files to extract event data and metadata into NumPy arrays or DataFrames.
yf8578Parse and create FCS files, converting event data to NumPy arrays or Pandas DataFrames.
jackspaceParse FCS files to extract events as NumPy arrays and metadata.
