If you're working with flow cytometry data and need to parse FCS files without pulling in heavy analysis frameworks, this handles versions 2.0 through 3.1 cleanly. It reads metadata and event data into NumPy arrays, writes modified FCS files back out, and includes practical flags for dealing with broken offset headers that show up in real lab data. The library separates scatter, fluorescence, and time channels automatically, which saves you from parsing channel names yourself. It's deliberately lightweight, so if you need compensation matrices or gating logic, you'll want FlowKit alongside it. Good fit for ETL pipelines or preprocessing steps before handing data off to analysis tools.
- skills.sh installs
- 2K
- GitHub stars
- 56.6K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill flowio --agent claude-codeInstalls into .claude/skills of the current project.
Files
FlowIO
Purpose
Use FlowIO as a lightweight, low-level reader and writer for Flow Cytometry Standard files. Examples in this skill target FlowIO 1.4.0, the current stable release verified on 2026-09-30. Standalone FlowIO checks used Python 3.13, NumPy 2.5.3, and pandas 3.0.6.
FlowIO is appropriate for:
- Reading FCS 2.0, 3.0, and 3.1 files
- Inspecting HEADER, TEXT, ANALYSIS, and channel metadata
- Retrieving event data as a two-dimensional NumPy array
- Reading legacy files that contain multiple datasets
- Writing list-mode, single-precision FCS 3.1 files
- Preparing data for pandas, machine-learning, or downstream cytometry tools
FlowIO does not perform compensation, logicle/biexponential transforms, gating, clustering, or FlowJo workspace processing. Use FlowKit or another analysis package for those tasks.
Install
Create or activate a Python environment, then install the verified release:
uv pip install "flowio==1.4.0"
Confirm the runtime version:
uv run python -c "import flowio; print(flowio.__version__)"
FlowIO 1.4.0 supports Python 3.9 through 3.13 and depends on NumPy.
Operating Workflow
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- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- AI & Agent Building, Data Science & ML
- First seen
- Jun 3, 2026
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