Press Play on Bioinformatics: Snakemake in Action

🐍 Ever wish running a bioinformatics pipeline was as easy as pressing “play”?

That’s basically what Snakemake does!

Think of it like a recipe book for data analysis:

• You list your ingredients (raw data)
• Write down each step (rules and scripts for preprocessing, analysis, plots)
• Hit “go” and it automatically cooks the entire meal for you!

The magic?

✅ No more re-running everything when just one step changes

✅ Works on your laptop or scales up to an HPC cluster

✅ Makes your analysis reproducible, so six months later (or on someone else’s machine) you get the same results

To put this into practice, I recently built a Snakemake workflow for cervical cancer gene expression analysis.

It:

🔹 Fetches data directly from GEO

🔹 Runs preprocessing + differential expression analysis

🔹 Generates a volcano plot for quick visualization

You basically write a Snakefile describing each step (preprocessing, analysis, visualization), and then run just one command:

snakemake --cores 4

That’s it! Snakemake figures out the order of tasks, runs only what’s needed, and makes sure results are reproducible.

✨ The BEST part? With the config file updated for your dataset, ANYONE can reproduce the full analysis with just that one command!

🟢 I’ve shared the pipeline on GitHub here 👉 https://lnkd.in/eS6G7W75

If you’re curious about Snakemake or just want to peek at a reproducible cancer genomics workflow, check it out!