Hello Bioinformatics lovers,

Tommy here. It is a long weekend here in the US.

Make sure you take a break and do some activities with your family.

Below is something I feel myself too.

If you've ever felt overwhelmed in bioinformatics—like you're constantly behind, like everyone else is ahead—you’re not alone.

Let me show you why that feeling isn’t failure.
It’s the nature of the field.

In 2012, I started learning bioinformatics.​
Back then, ChIP-seq was the shiny new thing, replacing ChIP-on-chip.
The field moved.

Then came:

• ChIP-exo
• ATAC-seq
• CUT&RUN
• CUT&Tag

Each with its own quirks.
Each demands a slightly different pipeline.
There is no "one tool fits all" anymore.

Bulk RNA-seq used to be the standard.​
We lived inside DESeq and edgeR.
But now?

Single-cell RNA-seq is everywhere.
And spatial transcriptomics and proteomics are changing the game again.

Gene × sample isn’t enough.
Now it’s:
​Gene × cell × location × time.

Short reads used to dominate.​
Illumina ruled the land.
But now PacBio and Nanopore are catching up.

Long-read is real—and necessary.
Especially for genome assembly.

But they’re noisy.
So we pair them with short reads to polish.

It’s a dance of trade-offs.

Want to be an expert in every assay?​
Forget it.
You can’t.

There’s ATAC-seq, CUT&RUN, Hi-C, WES, WGS, CITE-seq, spatial, single-nucleus RNA-seq, proteomics...

Tools multiply like bacteria.
New preprints weekly.
New wrappers monthly.
New file formats constantly.

So how do you keep up?

You don’t.

You focus on what doesn’t change:

• Curiosity
• Core programming skills
• Statistical reasoning
• Biological sanity checks

You don’t just memorize Seurat commands.
You understand how PCA, normalization, and clustering work.

You don’t need to master every new assay.
But you do need to ask:

And most of all—you find mentors.
People who’ve been in the field long enough to spot artifacts with a glance at an IGV track.
Or know which QC metrics matter—and which don’t.

That kind of wisdom? That’s gold.

Key Takeaways:

• You’re not falling behind
• The field evolves fast, but the foundations last
• Learn concepts, not just tools
• Ask questions, watch others, and learn continuously

Bioinformatics isn’t static.
It’s surfing waves of innovation.
Wipeouts happen.

But when you catch the wave—
It’s magic.

Other posts that you may find useful

1. ​12 websites to learn computation and many others! 🧵 Bookmark 👇
2. 🧵 Unix pipes are magic. But real power comes when you build them like LEGO. One piece at a time. 👇
3. 🧵 You shared your code. They used it at a conference. No credit. Should you feel bad? Let's talk​
4. ​5 websites to analyze GEO RNAseq data without a single line of code 👇
5. You just downloaded a 20GB enhancer x sample matrix. One problem: the first column header is missing. How to fix it with a unix one-liner.
6. Whole Exome Sequencing sounds easy. Just sequence and call variants, right? Not even close. caveats!
7. 🧵 You don’t know what you don’t know. And that’s exactly why you need people around you who do.
8. Thread: Multi-omics sounds cool—until you actually try it. Here's are the nuances.
9. You have 50 files. Same header. You want to merge them. Here’s how to do it without going insane. 🧵 👇
10. ​10 courses to get you started with bioinformatics 🧵 Bookmark!
11. Bioinformatics is hard before you even write a single line of code. Here's why. which reference genome should you use?
12. chatomics! 10 videos teaching you how to recreate Figure 1 step by step from a genomics paper with ChIP-seq data have been finally done. Watch here.

Happy Learning!

Tommy aka crazyhottommy

PS:

If you want to learn Bioinformatics, there are other ways that I can help:

1. My free YouTube Chatomics channel, make sure you subscribe to it.
2. I have many resources collected on my github here.
3. I have been writing blog posts for over 10 years https://divingintogeneticsandgenomics.com/​

Stay awesome!