Blog post on "The AI Rewrite Dilemma": lh3.github.io/2026/04/17/t...

Completely agree. Even without AI the first step should be a friendly ping to see if the original author is interested or maybe would prefer not to have versions of their work floating around.

Reaching out to the original author as a first step should be a given, absolutely.

I have mixed feelings about re-writing existing tools (fragmentation, maintenance burden, etc) but a ton of thought has gone into the `rewrites` manifest. Worth discussing.

Fingers and toes crossed

I’ll read up once I’m back home - thanks! I’m still rooting for a future where the reference genome digest is mandatory in the SAM header but this helps in the meantime :)

I struggle with this. Do I want to see LLM-created writing and art? No, absolutely not. Do I need to acknowledge that AI is having a significant impact on cancer research, drug design and trials? Also yes. Can we have one without the other?

Do you have a sense of the differences to refGet and SequenceCollections?

Such a cool project from @nilshomer.com.

Please tell me you are wearing magnifying glasses, as is proper.

I'm constantly trying (/failing) to get this point across.

If you're a trained expert in a field, then it may be worthwhile to question the scientific consensus of your peers.

If you're not, the scientific consensus is absolutely the best you can do and it's arbitrary foolishness to disregard it.

Are there any R users working for the Australian federal dept of health? I’d love to hear from you!

New gig, new people to meet :)

I think it's best for everyone to understand that the unified class project of billionaires right now is to do to white collar workers what globalization and neoliberalism did to blue collar workers.

I am surprised my following algorithm didn't fall over. Science, board games and social politics. The perfect trifecta in one tweet.

I've been in SF for four days and on each day I've had multiple conversations where people (self included) express deep feelings, fear, wonder and worry about their skills being replaced or (this is less named explicitly but an assumed driver I think) no longer valued by others. Big threats to feel

he VEP command looks correct, but the issue is that VEP is annotating based on ALL transcripts/features in the region, and "downstream_gene_variant" is being picked as the consequence. Since you didn't specify --pick or --pick_allele, VEP returns consequences for multiple transcripts, and your code is just taking the first one. Let me check how you're extracting the consequence from the VEP output: Found it! You're extracting only the second field from the CSQ column with map_chr(2). This is getting the consequence from the first transcript annotation, which might be a pseudogene or non-canonical transcript. Let me check what a VEP CSQ field actually contains: Perfect! I can see the issue now. The VEP CSQ field contains multiple transcript annotations separated by commas. The first annotation is for TSC2 (a different gene!) and shows "downstream_gene_variant". But if you look at the second annotation (after the first comma), you'll see it's for PKD1 ENST00000262304 and shows "3_prime_UTR_variant" for exon 46 (which is correct - exon 46 contains the 3' UTR). Your code is only extracting the consequence from the first transcript annotation (TSC2), not the PKD1 transcript! The fix is to parse all transcript annotations and filter for the PKD1 canonical transcript (ENST00000262304). Let me create the fix: PKD1_mutation_rate.qmd+24-1 Now let's test the fix by re-running the code to see if we get proper consequences for exons 40-46: Perfect! The fix worked! Now you're seeing proper consequences for exons 40-46: Missense variants (the most common)

was banging my head against a bug (VEP classifying my in-exon variants as 'downstream') that Claude Sonnet 4.5 fixed in about 5 minutes. I can understand the scepticism on LLMs being jammed into every corner of life, but there's merit in these tools

Oh! Could we combine them with Inkwell preorders?

I love this so much. Will absolutely copy this, finally a reason to reach out to all the lovely artists I am following.

Screencap of post from tumblr user nitewrighter Me: I don't get it. I thought I was doing a lot better than I was a few years ago. I'm like 10 times more on top of things than I used to be. How does everything feel terrible now? The Tiny Me in OSHA-approved Hi-Vis Gear Who lives in my brain and pulls all the levers: Boss, it's the fascism. You're completely gunked up with cortisol due to the fact that your entire daily life is now underscored with a haunting awareness of the rapid erosion of your rights, dignity, and any and all social safety nets, and you're also bearing witness to the most vulnerable people immediately being persecuted. This creates a natural stress response that basically means you're going to continue having memory and organizational problems, as well as emotional imbalances. Me: BUT I HAVE A BULLET JOURNAL AND I MEDITATE NOW. Tiny OSHA Me: BOSS, THE FASCISM.

Reminder for everyone operating at situationally-diminished capacity.

Getting older is like being out on the ocean in the Ship of Theseus but then at some point the guys just decided against replacing the decayed parts.

The comments on this are all about how sweet it is and I feel insane. Using AI to make fake memories of your grandma with dementia and telling her they happened and then filming her reaction

Got introduced to that via Chris Thile by way of the Goat Rodeo album of all things and still keep discovering fun new takes on it.

Release 2.3.0 - Spotted Nightjar · nf-core/oncoanalyser What's Changed Post release bump by @scwatts in #246 Improve samplesheet validation by @scwatts in #247 Important! Template update for nf-core/tools v3.5.1 by @scwatts @nf-core-bot in #266 Apply H...

Pipeline release! nf-core/oncoanalyser v2.3.0 - 2.3.0 - Spotted Nightjar!

Please see the changelog: github.com/nf-core/oncoanalyser/rel...

We strongly suggest using the following labels: praise: Praises highlight something positive. Try to leave at least one of these comments per review. Do not leave false praise (which can actually be damaging). Do look for something to sincerely praise. nitpick: Nitpicks are trivial preference-based requests. These should be non-blocking by nature. suggestion: Suggestions propose improvements to the current subject. It’s important to be explicit and clear on what is being suggested and why it is an improvement. Consider using patches and the blocking or non-blocking decorations to further communicate your intent. issue: Issues highlight specific problems with the subject under review. These problems can be user-facing or behind the scenes. It is strongly recommended to pair this comment with a suggestion. If you are not sure if a problem exists or not, consider leaving a question. todo: TODO’s are small, trivial, but necessary changes. Distinguishing todo comments from issues: or suggestions: helps direct the reader’s attention to comments requiring more involvement. question: Questions are appropriate if you have a potential concern but are not quite sure if it’s relevant or not. Asking the author for clarification or investigation can lead to a quick resolution. thought: Thoughts represent an idea that popped up from reviewing. These comments are non-blocking by nature, but they are extremely valuable and can lead to more focused initiatives and mentoring opportunities. chore: Chores are simple tasks that must be done before the subject can be “officially” accepted. Usually, these comments reference some common process. Try to leave a link to the process description so that the reader knows how to resolve the chore. note: Notes are always non-blocking and simply highlight something the reader should take note of.

I recently discovered Conventional Comments (conventionalcomments.org) for providing a pseudo-standard set of labels for feedback and just tried it for an article review and it was really helpful to specify issues vs. thoughts vs. suggestions, etc. Hopefully it's helpful for the authors too!

Welcome! You are invited to join a meeting: Clinical Genomics Laboratory Meeting. After registering, you will receive a confirmation email about joining the meeting. The topic for this meeting will be AI and LLMs in Variant Classification

Join the Clinical Genomics Laboratory Community (CGLC) meeting on 24 November. This session will explore how artificial intelligence and large language models (LLMs) are transforming variant interpretation. Register for the meeting: us02web.zoom.us/meeting/regi...

You have to wonder if White House staffers are simply showing him AI videos at this point and he thinks it's reality.

Acetaminophen Use During Pregnancy and Children’s Risk of Autism, ADHD, and Intellectual Disability This nationwide cohort study with sibling control analysis examines the association of acetaminophen use during pregnancy with children’s risk of autism, ADHD, and intellectual disability.

Reminder: a large (2.5M+) sibling control study found "no evidence of increased risk of autism, ADHD, or intellectual disability associated with acetaminophen use". Precisely the kind of data that requires serious consideration before declaring mission accomplished.

jamanetwork.com/journals/jam...

Heads up: ignore samtools dot org, similarly minimap2 dot com and likely others. It's owned by a known phishing site and while the binaries they offer look valid currently (but note they may be serving us different binaries to others), that could change.

Ie: it's not us (Samtools team)! Be warned

One of the last, best hopes for saving the open web and a free press is dead The Google ruling is a disaster. Let the AI slop flow and the writers, journalists and creators get squeezed.

Breaking Google up was one of the last best hopes for preventing the free press from getting squeezed into oblivion and harvested into AI slop, and for saving the open web. The ruling that effectively lets Google continue operating as a monopoly isn't just disappointing, it's a disaster.

At scale, the way that we store (and process) data matters! Many may think that the way we keep data, the file formats we adopt, and the way that we compress data are unimportant details, but they are, in fact, critical considerations to allow science to move forward at scale!