Bio Flow Cytometry Compensation Transformation
This skill automatically corrects for spectral overlap in flow cytometry data, ensuring accurate quantification of cell populations.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add bio-flow-cytometry-compensation-transformation npx -- -y @trustedskills/bio-flow-cytometry-compensation-transformation
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"bio-flow-cytometry-compensation-transformation": {
"command": "npx",
"args": [
"-y",
"@trustedskills/bio-flow-cytometry-compensation-transformation"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill performs flow cytometry data compensation and transformation. It corrects for spectral overlap between fluorescent channels, allowing for accurate analysis of protein expression levels. The tool can also perform mathematical transformations (e.g., arcsinh) to improve data visualization and statistical analysis.
When to use it
- Analyzing fluorescence-activated cell sorting (FACS) data where multiple fluorochromes are used simultaneously.
- Preparing flow cytometry datasets for downstream statistical analyses or machine learning models.
- Standardizing flow cytometry data across different experiments or laboratories.
- Generating publication-quality figures from flow cytometry results.
Key capabilities
- Compensation matrix calculation
- Spectral overlap correction
- Mathematical transformations (e.g., arcsinh)
- Data normalization
Example prompts
- "Can you compensate this FCS file using the provided compensation matrix?"
- "Transform these flow cytometry data with an arcsinh transformation."
- “Apply a compensation matrix and then perform a logicle transformation on this dataset.”
Tips & gotchas
The accuracy of compensation relies heavily on accurate experimental controls (single-stained samples). Ensure your compensation matrix is properly generated for optimal results.
Tags
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