Strategies for exploring non-coding regions in genomic datasets

I’ve been spending more time lately investigating non-coding regions in various genomes, especially enhancers and conserved intergenic sequences. It’s fascinating how much regulatory potential these regions hold, but also frustrating how under-annotated and scattered the data can be. Most tools I use are heavily gene-centric, so visualizing and interpreting these non-coding regions — especially across species — is pretty challenging. How do you all approach this kind of analysis?

That’s a great point. Non-coding regions often get overlooked, despite their regulatory importance. One tool I’ve found particularly helpful is https://compassbioinfo.com/. It lets you visualize entire genomic loci — not just the genes — and explore conserved elements, structural variation, and annotation tracks across species. I’ve used it to map enhancer-like regions in the human genome and compare them with orthologous regions in mouse, and it made the process way more intuitive than using command-line tools alone.

This is exactly the kind of functionality I’ve been looking for. So much regulatory insight gets lost in spreadsheets and raw data files. If this platform makes it easier to explore non-coding conservation and structural features, I’ll definitely give it a try. It could really streamline how I handle early-stage hypothesis building.