Hopefully I will soon break out of this funk of posting about either Mastodon or Twitter. But not yet! This post is to say that: I made a static archive of tweets for @quantixed and for @clathrin. There, you can read all my posts, which ended in 2022. Edit: removed the archives in October 2024. How did I do it and why? I made the archive with this excellent tool written by Darius Kazemi.

Earlier this year I set up a bot on Mastodon. The bot, AlbumsX3, posts an album suggestion twice-a-day. Performance has been good. It has only missed a few posts due – I think – to server glitches. However, I have made a couple of tweaks to upgrade the bot since my last post, so I thought I would detail them here. Preventing duplicate posts In the last post I wrote: Well, it wasn’t long before I needed to revisit this issue.

I migrated my personal Mastodon account from mastodon.social to biologists.social recently. If you’d like to do the same, I found this guide very useful. Note that, once you move, all your previous posts are left behind on the old instance. Before I migrated, I downloaded all of my data from the old instance. I thought I’d take a look at what I had posted to see if anything was worth reposting on biologists.social.

This is a brief review of macOS Mastodon clients that I’ve tried. It is unashamedly incomplete/non-exhaustive, but since the ones I found online from computing magazines literally look at one app, I am ahead of the pack here! tl;dr I prefer Ivory on macOS and prior to that, Mastonaut was OK. For clarity: I have not been asked or received payment to promote any software. Why use an app on desktop/laptop?

We have an analysis routine for proteomics data written for IgorPro. One output is a volcano plot . These plots show the fold change in one sample compared to another and plot that against a p-value to estimate how reproducible any changes observed are. This post is not about that software, but on the topic of how we can recreate this plot in R . What steps need to be considered?

I’ve posted in the past about analysing race results in R (most recently here). I ran the 2023 MK Marathon and wanted to have a look at the finishing times. The days of race results being made available as a csv or xls for easy analysis seem to be behind us. Instead they tend to be served up on multiple webpages of 50 athletes’ results at a time. Oh no, 29 pages of results and now Download option…. let’s scrape the data!

I’m not a big movie person. Nonetheless I have a media library with quite a few films in and I wondered how many “films to see before you die”-type movies I had in the collection, and how many were missing. I used R to find the answers. I’ve described previously how to get a plain text dump of a Plex database using WebTools-NG. I did that for the Movies library of my Plex Media Server.

I like to set up a standardised directory structure for RStudio projects. The idea came from here. In brief, the structure is: Data/ Output/Data/ Output/Plots/ Script/ My typical workflow is therefore to: select File > New Project in RStudio make a new directory and RProj file then use this R script or these shell commands to setup the directories. So far, so good. However, this process is a bit tedious.

I have long admired albums2hear, a Twitter bot that posts albums. You can read a bit more about it here. There was no mastodon equivalent and so I decided to build one. You can follow the bot – currently called Albums Albums Albums (or AlbumsX3) – here. Idea behind the bot The idea is to periodically post an album.

I have a long-running Raspberry Pi camera project to capture images of the view from a window (more details here). A recent post on mastodon, which showed a keogram, encouraged me to take my PiCam images and turn them into art. The finished product This is the finished wall art, printed on canvas. Ready to hang on the wall.