Skills flowio
🔬

flowio

Safe ⚙️ External commands🌐 Network access⚡ Contains scripts

Read and write FCS flow cytometry files

Also available from: davila7

Flow cytometry data requires specialized file handling. FlowIO parses FCS files, extracts event data as NumPy arrays, and enables conversion to CSV formats for downstream analysis pipelines.

Supports: Claude Codex Code(CC)
📊 69 Adequate
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Test it

Using "flowio". Read my flow cytometry file and show the channel information

Expected outcome:

  • File: sample.fcs (245 KB)
  • FCS Version: 3.1
  • Events: 10,234
  • Channels: 8
  • Channel [0] FSC-A | Forward Scatter | scatter
  • Channel [1] SSC-A | Side Scatter | scatter
  • Channel [2] FL1-A | FITC | fluoro
  • Channel [3] FL2-A | PE | fluoro
  • Time channel: Index 7

Using "flowio". Convert this FCS file to CSV format

Expected outcome:

  • Loaded sample.fcs with 15,000 events and 12 channels
  • Converted event data to Pandas DataFrame
  • Exported to sample.csv (2.3 MB)
  • Columns: FSC-A, SSC-A, FL1-A, FL2-A, FL3-A, FL4-A, FL5-A, Time

Security Audit

Safe
v4 • 1/17/2026

All 177 static findings are false positives. The scanner misidentified markdown documentation artifacts and legitimate scientific terminology as security issues. Shell command patterns are installation instructions in code blocks. 'Weak cryptographic algorithm' detections refer to 'PnE' (Parameter n Exponential), a legitimate flow cytometry data format term for amplification exponents. No actual executable code or malicious patterns exist in this skill.

3
Files scanned
1,962
Lines analyzed
3
findings
4
Total audits

Risk Factors

⚙️ External commands (2)
references/api_reference.md:9-11 SKILL.md:31-33
🌐 Network access (1)
skill-report.json:6
⚡ Contains scripts (1)
SKILL.md:350-355
Audited by: claude View Audit History →

Quality Score

41
Architecture
100
Maintainability
87
Content
21
Community
100
Security
78
Spec Compliance

What You Can Build

Preprocess cytometry data

Extract events from FCS files and prepare data for analysis pipelines with compensation and gating tools.

Inspect experiment files

Quickly view channel counts, event counts, and metadata from flow cytometry experiments without specialized software.

Batch convert to CSV

Process directories of FCS files and export to CSV format for machine learning workflows.

Try These Prompts

Basic file reading 
Use FlowIO to read experiment.fcs and show the version, event count, and channel names.
Extract event data 
Load sample.fcs using FlowIO and extract the event data as a NumPy array with preprocessing applied.
Create FCS file 
Create a new FCS file named output.fcs from a NumPy array with 1000 events and 5 channels named FSC-A, SSC-A, FL1-A, FL2-A, Time.
Batch conversion 
Find all .fcs files in data/ directory, read each one, and export the event data to CSV files with the same basename.

Best Practices

  • Use only_text=True parameter when only metadata is needed to save memory
  • Wrap file operations in try-except blocks to handle parsing errors gracefully
  • Use ignore_offset_discrepancy=True for files with offset inconsistencies

Avoid

  • Do not attempt direct modification of event data in FlowData objects
  • Do not use FlowData constructor for multi-dataset files - use read_multiple_data_sets()
  • Do not assume preprocessing is always desired - set preprocess parameter explicitly

Frequently Asked Questions

What FCS versions are supported?
FlowIO supports FCS versions 2.0, 3.0, and 3.1 for both reading and writing.
How to extract only metadata?
Pass only_text=True to FlowData constructor to skip DATA segment parsing and save memory.
Can I modify event data?
FlowIO does not support direct modification. Extract data with as_array(), modify it, then use create_fcs() to save.
How to handle multi-dataset files?
Use read_multiple_data_sets() function instead of FlowData constructor to get all datasets as a list.
What preprocessing is applied?
By default, FlowIO applies gain scaling, logarithmic transformation using PnE values, and time scaling.
Can this integrate with other tools?
Yes, combine with FlowKit for compensation/gating or export to Pandas DataFrames for analysis.

Developer Details

Author

K-Dense-AI

License

BSD-3-Clause license

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/flowio

Ref

main

File structure

📁 references/

📄 api_reference.md

📄 SKILL.md