Bulk Rna Seq Differential Expression With Omicverse
Analyzes RNA sequencing data for significant differential gene expression changes using OmicerVerse, streamlining complex biological analysis and discovery.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add bulk-rna-seq-differential-expression-with-omicverse npx -- -y @trustedskills/bulk-rna-seq-differential-expression-with-omicverse
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"bulk-rna-seq-differential-expression-with-omicverse": {
"command": "npx",
"args": [
"-y",
"@trustedskills/bulk-rna-seq-differential-expression-with-omicverse"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill performs differential expression analysis on bulk RNA sequencing (RNA-seq) data using the Omicverse framework. It allows users to identify genes that are significantly up or down regulated between different experimental conditions. The tool handles common tasks like quality control, normalization, and statistical testing for identifying differentially expressed genes.
When to use it
- Comparing gene expression profiles in tumor versus normal tissue samples.
- Analyzing the effects of a drug treatment on gene expression in cells.
- Identifying genes associated with disease progression based on RNA-seq data from different stages.
- Investigating differences in gene expression between two different cell types or experimental groups.
Key capabilities
- Differential Expression Analysis
- RNA-seq Data Processing
- Normalization
- Statistical Testing
Example prompts
- "Run differential expression analysis on my RNA-seq data, comparing condition A to condition B."
- "Perform quality control and normalization on this bulk RNA-seq dataset."
- "Identify genes with significantly different expression between the treated and control groups."
Tips & gotchas
- Requires a properly formatted RNA-seq count matrix as input. Ensure your data is prepared according to Omicverse's specifications for optimal results.
Tags
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