Used observablehq plot in a new paper on human brain evolution

[neurogenomics]

Hi all, we recently submitted a manuscript for publication that explores how the human brain got to be so big (spoiler: turns out to unintuitively be the downregulation of mitochondria).

As part of this, I ran an RNAseq experiment to looks at gene expression networks, binning genes into categories called “GO terms.” Rather than a traditional Gene Set Enrichment Analysis (GSEA) plot, I used an observablehq lollipop plot. I found this to be much more intuitive and easy to understand than a traditional GSEA plot for this use case. I’m hoping that the reviewers will agree! So this figure is now live in a publication on a preprint server, undergoing peer review. Just thought I’d share. Cheers!

GO Term Visualization

[tophtucker]

I had a random support call with Jonathon and ended up asking him a million questions about this notebook and egged him on to expand and post it lol. I just wrote up what I learned from our conversation on Twitter / Bluesky.

Two followups on my mind:

• Would be fun to visualize the GO ontology itself. Here’s a “hello, world” notebook loading the graph: Gene Ontology | Toph Tucker | Observable
• Would be nice to have an example of a traditional GSEA plot in a notebook.