ideogram VS yadm

> Where are the polished, powerful design tools for biology

User interfaces for biology have drastically improved over the last 10 years.

Domain-specific tools like genome browsers, protein viewers, or phylogenetic explorers [1-3] almost all look and feel a lot better than they did in 2012.

The biggest exception here is UCSC Genome Browser, which has an old-school design and web technology stack. That said, it's steadily added features over the years, has substantially sleekened UX in its periphery, and remains widely used.

There are also bespoke visual design resources for biology applications that are good and getting better, like BioRender and PhyloPic [4-5]. There are multi-tiered packages like Dash Bio that wrap biology components together. There's Blender biology community, too!

---

1. Genome browsers and components: https://jbrowse.org/jb2/, https://www.ncbi.nlm.nih.gov/genome/gdv, https://igv.org/app, https://eweitz.github.io/ideogram

2. Protein viewers: https://pymol.org/, https://nglviewer.org/ngl/

3. Phylogenetic explorers: https://clades.nextstrain.org/

4. https://biorender.com/

5. http://phylopic.org/

6. https://github.com/plotly/dash-bio, https://dash.gallery/Portal/?search=[Pharma]

I'm more interested in read speeds than write speeds. I have about 2 MB of data that I fetch, then parsed and transformed into a heavily nested object for easy look-up by various types of keys.

In my brief experiment, it was 12% faster to read from the web Cache API, re-parse and re-transform that heavily nested object than to read the fully transformed object via IndexedDB. That surprised me! My understanding is that IndexedDB does a structured clone as part of the read, which I suspect is the main cause of slowness of IndexedDB relative to the Cache API approach in my use case.

Related commits to reproduce that finding are in [1], specifically [2].

[1] https://github.com/eweitz/ideogram/pull/285

I created Ideogram.js, a JavaScript library for chromosome visualization [1]. Ideogram supports drawing and animating genome-wide datasets, enabling a variety of genomic views [3].

[1] https://github.com/eweitz/ideogram

[2] https://eweitz.github.io/ideogram

Everyone hand-rolls their own dotfile management system, but YADM already does everything you need:

https://yadm.io/

I've been working around this using tools built on top of git like [yadm](https://github.com/TheLocehiliosan/yadm) and relying on `ls-files` to list all my tracked dotfiles and their paths.

Still having everything in one place would make things much simpler. Great idea!

I wonder if the program i use to manage my dotfiles could help manage your scripts and extend your setup to all your desktops? Its called yadm (https://yadm.io/) it makes it so easy to have a laptop and a desktop or two.

I really like that one but still prefer yadm because you can just edit your files as usual and then yadm add them wherever you are.

If you haven’t already, this is the time to install a tool like yadm and get your computer configuration into version control. Your command-line tools can be managed by yadm directly, your system settings can mostly be managed with a yadm bootstrap script that runs things like defaults write, and the software you install can be managed with a Brewfile that the yadm bootstrap script uses to install software with Homebrew. Don’t manually download Xcode, use xcodes to do it.

I personally use YADM. It's basically a git repo on my home folder, that only tracks what I explicitly set. And you can setup bootstraps to do what you said, install a bunch of stuff or make custom changes. In it's essence, it's a set of bash/sh files that are executed sequentially when you launch the yadm bootstrap command.