Here’s a conundrum. When posting a new preprint, we typically have to juggle up to three DOIs (for the preprint, the code, and the data). How can we cross reference these DOIs? The problem Ideally, we would reference the DOIs of the code and data in the paper, the DOIs of the paper and code […]
Category: computing
Choose Your Fighter: data-driven selection of the best marathon
Running a marathon is a big deal. It takes a lot of time to train to run a good time, and it takes a while to recover. So, if you’re chasing a marathon PB (personal best) time, you need to choose which Marathon to target wisely. How can we use data to help our decision? […]
Adventures in Code VII: getting started with napari
I’ve dabbled a bit with napari – the python-based image viewer – but never needed to use it seriously. I had a real use case so I thought I’d write up the process of how I got going with napari, in case it helps others. My use case I wanted to overlay tracks onto microscopy […]
Let It Flow: recreating a FACS plot with ggplot
It’s plot recreation time! In this post, we’ll look at how we can recreate a plot in R. I thought it might be useful to provide the solution but also to detail the process I went through to get there. We have a FACS plot taken from a BD FACS Aria machine: Briefly, it’s a […]
Stacked Up: my academic software stack
The software that we use to do our work is our academic software stack. I often see requests for advice on which software works well. Since recommendations from labs that have road-tested a few options are quite valuable, I thought I would document what we’re currently using and why. I have tried to note if […]
Tips from the Blog XVII: better Process Folder template in Fiji
The Process_Folder template in Fiji is a wonderful thing. It’s the starting point of most of the ImageJ macros that we use in the lab. However, it has a problem. This post is about how to fix it. tl;dr use this gist instead of the built-in template. The Process_Folder template If you’re reading this, you […]
Exploding, Impacting: looking at bioRxiv preprint view dynamics with R
One of the joys of posting a preprint is seeing that people are viewing, downloading and (hopefully) reading your paper. On bioRxiv you can check out the statistics for your paper in the metrics tab. We posted a preprint recently and it clocked up over 1,000 views in the first day or so. This made […]
King of the Mountain: using R to bag a Strava KOM
One of the best features of Strava is the battle to be King (or Queen) of the Mountain. Originally, in cycling, segments were typically climbs or difficult sections of road, and the simple idea, is who can complete the segment in the quickest time. Hence they would be KOM/QOM, King or Queen of the Mountain. […]
Slacker II: archiving information from a Slack workspace
I wrote previously about how to archive a Slack workspace. Well, now Slack announced a new policy, effective from August 26th, 2024. Under the new policy, messages and files older than one year in workspaces on the free tier will be deleted. This is in addition to the 90 day limit for viewing content in […]
Prehistoric: when do authors preprint their papers?
Previously, I took advantage of a dataset that linked preprints to their published counterparts to look at the fraction of papers in a journal that are preprinted. This linkage can be used to answer other interesting questions. Such as: when do authors preprint their papers relative to submission? And does this differ by journal? There’s […]
