Gethsemane

For most DNA it now sits at ~Q20 (1%) which is a big improvement - there was also some hacky stuff like HERRO and duplex sequencing which improved it substantially. For routine genome sequencing it's definitely suitable, and the long-read advantage helps resolve some of those trickier regions

Fastest/cheapest sequencing based method would likely be to collect samples in DNA preserving agent (zymo DNA shield is decent for this), then have an automated platform for extracting DNA and preparing amplicon sequencing libraries (rbcL + matK probably?). Worth having a look at how Plasmidsaurus did this, they did have a similar service for microbiome analysis (https://plasmidsaurus.com/sample-prep/microbiome#16S-extract... - looks like they don't accept raw samples anymore though...). Oxford nanopore sequencing is a decent technology for this as it's fairly straightforward to get working and easy to scale :) As an added bonus, you could perhaps also carry out 16S sequencing in parallel from the sample to get an idea of the microbiome of the sewer.

Have you written about your experience anywhere? It would be interesting to see how you approached the research sector as a layperson. Are there any plans to move to in vivo? Best of luck with your research!

With AIs as teachers, I disagree. But with AIs assisting routine grading, filling in the university's assessment_framework_draft_v3_final_FINAL.docx, and otherwise freeing up time to actually focus on students - maybe? Although I fear that any productivity gains will be swallowed up by further reductions in lecturer headcount...

Very nice! I also like working from pandoc where possible - being able to split the output into a latex/typst file as well as a docx is very handy, especially when working with collaborators who are more comfortable with word. I wish markdown would see more support in scientific writing - it would solve so many of the headaches with formatting etc (and reduce microsoft's dominance in research)

Ultimately you're not going to find a service that can guarantee privacy, but your best bet might be to extract DNA at home (though tricky without a centrifuge etc...) and submit it to a standard sequencing provider novogene, plasmidsaurus etc. Realistically, they'll hold onto the data for a couple of months as part of the order, then delete it to clear up space. A bunch of discordant sets of DNA sequence without metadata isn't exactly useful for nefarious purposes! I wouldn't recommend sequencing at home unless you are very enthusiastic...

It's very context-dependent - the seqera rewrites so far seem to be pretty reliable, most of the work was spent merging the functions of multiple data QC tools into a single program (previously, there was a lot of redundancy that wasted compute). The success of other rewrites that I've seen tends to depend on the author's care/experience and usefulness. In my experience, bioinformaticians are fairly slow on the uptake of new software which might actually be an advantage here :-)

In defense of a lot of these bioinformatics-specific rewrites, there are some really dodgy coding practices and bugs that exist in well used tools, so there is scope for genuine improvement. The most recent release of minimap2 fixed some bugs identified in a rewrite, for example: https://github.com/lh3/minimap2/releases/tag/v2.31

I somewhat agree, in that most of these life science adjacent demos are essentially "find good drug targets for $DISEASE", which mostly overfit to existing, well-classified drugs and targets. The biggest gains IMO will be in improved connectors with autonomous lab platforms, better sharing and annotation of relevant data sets, and yes also improving the pathway to clinical trials.

At the moment, it feels like releases like this overcommit and overpromise on "PhD level reasoning", which I wouldn't say is the absolute bottleneck in clinical research.

It's also all too easy to arbitrarily label something as "bureaucratic" and demand that it gets razed and rebuilt. I'm sure Palantir has some level of bureaucracy internally with all the new contracts it has won - perhaps we should also rip that apart?

Fact is that a university that must simultaneously handle education, research, publishing, estate management, legal stuff, media coverage, health and safety etc etc etc ends up being somewhat bureaucratic.

A highlight of my time in Turkey was the cats - thank you for your efforts! Antalya had a lot of cat hotels in the park and most looked very healthy.

If I was less lazy I could probably find this answer online, but how do you find the battery life these days? I'd love to make the switch, but that's the only thing holding me back...

I'd love to see some benchmarks for this on some common genomic formats (fa, fq, sam, vcf). Will be doubly interesting to see its applicability to nanopore data - lots of useful data is lost because storing FAST5/POD5 is a pain.

Unfortunately, when you write a program that doesn't wrap output FASTAs, you have a bunch of people telling you off because SOME programs (cough bioperl cough) have hard limits on line length :)

I really want to like typer, and frequently go down the rabbit hole of rewriting all my argparse into typer, but I keep getting put off by it's high import cost and that development seems to be a bit up in the air (see https://github.com/fastapi/typer/issues/678#issuecomment-319...). A shame because otherwise it's a really nice library!

Agreed, there’s been some interesting developments in this space recently (e.g. AgroNT). Very excited for it, particularly as genome sequencing gets cheaper and cheaper!

I’d pitch this paper as a very solid demonstration of the approach, and im sure it will lead to some pretty rapid developments (similar to what Rosettafold/alphafold did)

Something I found useful is that you can create a much more minimal pandoc template for typst than for latex. Obviously if familiar with latex it probably won't be an issue, but when I tried to make my own barebones pandoc template (i.e., stripping out beamer) I gave up.

I've similarly found the combination of pandoc + typst to be quite exciting. I've found it particularly useful for typesetting academic papers - I'm quite averse to word in general, don't require extensive mathematical typesetting support, and find latex to generally be quite unapproachable (just look at the size of the default pandoc template!), and so it gives me a method of making a decent pdf whilst simultaneously producing a .docx for my collaborators. Being able to track changes with git is also a huge advantage, although never had the chance to work with someone who is comfortable using git :(

The recently added support for PDF/A is also quite exciting, as I've never found a satisfactory solution to this with latex. Now I just wish journals would support markdown submissions...

I am a fan of the colour scheme they selected in figure 2 - very relevant. https://pubs.rsc.org/image/article/2024/na/d4na00601a/d4na00...

As an example of a more informative map of income/deprivation, I recently encountered the Scottish Index of Multiple Deprivation website (https://simd.scot). Only applicable to Scotland (obviously), but it is interesting to see how each city is a mosaic of social status. From personal experience, it is extremely accurate down to the street level!

50% CPU usage on the home page, and the firefox inspect tool crashes before it can open! The content itself doesn't load either - just a large blue box

It is a shame. Twitter used to be quite a popular platform for (useful and interesting) networking in academia, but after it began to fall apart everyone started looking for alternatives. I felt that LinkedIn should be a decent alternative as it could strike that balance between professional and personal content, but there is just no way for a genuine community to develop on LinkenIn in its current form.

Even now LinkedIn is possibly the worst platform for being polluted with "AI slop", I cannot understand why they are looking to advance this further. Hell, when you go to write a post now there is a big flashing button saying "USE AI TO WRITE THIS POST"...?!?!

Sounds like your laptop is wholly out of date, you need to buy the next generation of laptops on Amazon that can handle the modern SEO load. I recommend the:

LEEZWOO 15.6" Laptop - 16GB RAM 512GB SSD PC Laptop, Quad-Core N95 Processor Up to 3.1GHz, Laptop Computers with Touch ID, WiFi, BT4.2, for Students/Business

Name rolls off the tongue doesn’t it

I agree that it's perhaps not the most robust choice, but at least for my field (bioinformatics) it's a good balance between accessibility and performance. That being said, in most cases when I come across a paper >1 year old presenting the latest-and-greatest Shiny web app, it is wholey broken when I try to use it :|

Shiny is an R package that is quite popular for building data analysis web tools, I suppose this would be a useful extension for it! Despite R tending to give people 'the ick' it regardless seems to have become quite a solid platform for building web apps

On the latest iOS update, searching for the Files app also returns a shortcut to the scanner. Weirdly, searching for "scan" or similar doesn't return it... The icon is similar in design to the control centre so you'd think it could be added there, but again, it's unavailable...

It does seem like a bit of an unfair comparison. That being said, I am not aware of any k-mer python packages that have great performance. If k-mer counting performance was really important, I'd probably start to think about reaching for one of the more performant counters, such as KMC.

The real benefit of python in bioinformatics is the number of libraries available that let you interact with a bunch of software, perhaps do some light analysis, maybe make some pretty plots. And if you want to do some more intensive "useful" analysis, then all the ML packages, numpy, polars etc are quite hard to dismiss.