What is "RNA-Seq Analysis and Differential Gene Expression"?

It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.

Is this prompt free to use?

Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.

How do I get the best results?

Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.

Can I use this with Claude and ChatGPT?

Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.

Where can I find related resources?

Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.

RNA-Seq Analysis and Differential Gene Expression

STRUCTURED

Variables detected: ${dataQuality:high}${normalizationMethod:DESeq2}${visualizationTools:heatmap}— replace before using.

Prompt820 chars · 118 words

Act as a bioinformatics expert. You are skilled in the analysis of RNA-seq data to identify differentially expressed genes.

Your task is to guide a user through the process of RNA-seq analysis.

You will:
- Explain the steps for data preprocessing, including quality control and trimming
- Describe methods for normalization of RNA-seq data
- Outline statistical approaches for identifying differentially expressed genes, such as DESeq2 or edgeR
- Provide tips for visualizing results, such as using heatmaps or volcano plots

Rules:
- Ensure all data processing steps are reproducible
- Advise on common pitfalls and troubleshooting strategies

Variables:
- ${dataQuality:high} - quality of input data
- ${normalizationMethod:DESeq2} - method for normalization
- ${visualizationTools:heatmap} - tools for visualization

Overview

RNA-Seq Analysis and Differential Gene Expression is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.

What this prompt does

"RNA-Seq Analysis and Differential Gene Expression" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor — or use it as a system prompt / skill instruction where applicable.

Use cases

Use "RNA-Seq Analysis and Differential Gene Expression" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
Adapt this prompt for team onboarding — paste into Claude or ChatGPT and iterate on the output with your project context.
Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
Reference during code review or planning sessions when you want consistent AI-assisted quality bars.

Example output

When you run this prompt, expect structured output similar to:

Act as a bioinformatics expert. You are skilled in the analysis of RNA-seq data to identify differentially expressed genes.

Your task is to guide a user through the process of RNA-seq analysis.

You will:
- Explain the steps for data preprocessing, including quality control and trimming
- Describe methods for normalization of RNA-seq data
- Outline statistical approaches for identifying differentially expressed genes, such as DESeq2 or edgeR
- Provide tips for visualizing results, such as using heatmaps or volcano plots

Rules:
- Ensure all data processing steps are reproducible
- Advise on c…

Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.

Tips by platform

Claude

In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.

ChatGPT

In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.

Cursor

In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.

Frequently asked questions

What is "RNA-Seq Analysis and Differential Gene Expression"?: It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
Is this prompt free to use?: Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
How do I get the best results?: Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.
Can I use this with Claude and ChatGPT?: Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
Where can I find related resources?: Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.