Tool: A new pilot project for genomics analysis — AriaDNA
I've been building a side project I'm happy to finally share: AriaDNA — a genomic viewer that runs entirely in your browser.
No install, no uploads. You open a file and it's parsed and rendered locally, so your data never leaves your machine.
It brings several viewers into one workspace:
- Sequences (FASTA / GenBank) with translation, features and GC content
- Multiple sequence alignments
- Phylogenetic trees (NJ, UPGMA, MST, GoeBURST) with iTOL-style rendering
- Distance matrices and heatmaps
- Sanger chromatograms (AB1)
- VCF, SAM/BAM and BLAST results
It's free, needs no account, and works on any modern browser. Built with React, D3 and a lot of canvas rendering.
It's a Pilot yet. I'd genuinely value your feedback — what's useful, what's missing, what breaks.
Thank you very much
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davidmaimoun •
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Can you elaborate what it offers that the IGV doesn't? No install is "cool", but after all installing IGV takes like 30'' so it's no bottleneck at all and there is intallers for all major OSs.
Fair point — install time isn't the real argument, and I'm not trying to replace IGV for what it's best at (browsing large BAM/VCF over a reference genome — IGV is excellent there and AriaDNA doesn't compete on that). IGV it's very good! My tool targets a different workflow. It's a multi-format inspection and phylogenetics tool, more oriented toward microbial typing and quick look-ups than reference-based read alignment.
Specifically it does several things IGV doesn't:
Sanger chromatograms (AB1) with base-call editing and FASTA export.
The "no install" part matters less for the 30 seconds and more for the context: sending a colleague or a classroom a link that opens on any device with zero setup, and the fact that everything runs client-side so data never leaves the machine — which is relevant for sensitive/clinical data where uploading isn't an option.
So it's complementary to IGV rather than a replacement.
Since I am more a developer than bioinformatician (I am both, but my bioinformatics stills need improvement), I'd appy to hear which workflows you'd find most useful — that's exactly the kind of feedback I'm looking for.