Bioinformatics, computational biology, and data science updates from the field. Occasional posts on programming.

Use the constructive package instead of dput() to construct R objects with idiomatic R code for human-readable reproducible examples

Construct objects with idiomatic R code

Polyglot data science pipeline (R+Python+Julia) with rixpress, EuroBioC2025/BCN, Python packaging for R devs, Python in 2025, R/Pharma, DARPA, ASHG, the R Data Scientist, Quarto, universities and AI

Weekly recap (Oct 24, 2025)

Something a little different for this week’s recap. I’ve been thinking a lot lately about the practice of data science education in this era of widely available (and really good!) LLMs for code. Commentary at the top based on my own data science teaching experience, with a deep dive into a few recent papers below.

Listen now | Balancing growth with guidance: teaching data science in the age of AI assistants

AI in data science education

This is part 1 of a series on uv. Other posts in this series:


 This post


 uv, part 2: building and publishing packages


 uv, part 3: Python in R with reticulate


 uv, part 4: uv with Jupyter

Lately I’ve heard a lot great things about uv, an extremely fast Python package and project manager, written in Rust.

Over the past year I’ve heard a lot great things about uv, an extremely fast Python package and project manager, written in Rust.

uv, part 1: running scripts and tools

I’ve written a lot about Ollama here. Ollama lets you run open-weight models like Llama, Gemma, Mistral, Qwen, DeepSeek, etc. on your own computer. You don’t have to pay for a frontier model like ChatGPT, Claude, or Gemini, and all the inputs and outputs stay on your computer, minimizing any privacy and security concerns. Until recently Ollama was a command-line only tool.

Ollama's new app has a built-in user interface. It has a model selector, you can drop in files, and it supports multimodal and vision models like Gemma3 and reasoning models like DeepSeek-R1.

Ollama now has a GUI

AI in science, Quarto, biodiversity, changed grant titles, new papers &amp;

Weekly Recap (Oct 31, 2025)

59 new software packages, updates for genomics, single-cell transcriptomics, spatial omics, QC tooling, core I/O, GFF/CIGAR handling, much more.

Bioconductor 3.22 Released

WIRED published a special issue with 17 readings from the furthest reaches of the AI age

WIRED: AI of a Thousand Faces

Note:
 
 After I wrote this post last week, the Tidyverse team released ragnar 0.2.0 on July 12. Everything here should still work, but take a look at the release notes to learn about some nice new features that aren’t covered here.

I’ve written a little about retrieval-augmented generation (RAG) here before.

Retrieval augmented generation in R using the ragnar package. Demonstration: scraping text from relevant links on a website and using RAG to ask about a university's grant funding.

Tidy RAG in R with ragnar

Over 100 recorded talks from posit::conf(2025) are now available on YouTube

posit::conf(2025) talks on YouTube

In Google's new paper, "An AI system to help scientists write expert-level empirical software" an AI supposedly "invents" new methods in bioinformatics and infectious disease modeling &amp; forecasting.

Single-cell analysis and infectious disease forecasting: Google's new AI scientist

Weekly Recap (Nov 21, 2025)

AI x biosecurity, R updates (Blaze, RWeekly, R Consortium), genome engineering &amp; conservation, AI &amp;

Weekly recap (Oct 10, 2025)

I'm not going to listen to opinions about AI from people who don't use AI.

Quoting Kevin Roose (NYT / Hard Fork)

Moving from Google Docs to Word will break your Zotero citations/bibliography linkages unless you do this first.

Switching word processors with Zotero

R updates (from rOpenSci, Blaze, R Works, RWeekly, Posit), Slidecrafting, AI highs &amp;

Weekly recap (Oct 3, 2025)

Successively clicking the first link in a Wikipedia article almost always leads to Philosophy

All Roads Lead to Philosophy

Positron allows you to export dplyr/SQL code for actions you take in the data explorer (like sorting and filtering)

Positron: data explorer exports dplyr code

LLMs for learning to code, R updates (R Data Scientist, R Weekly), RAG, layoffs &amp; AI, DuckDB for data science, Anthropic+Iceland, AI in science, AI in drug discovery, Nextflow &amp;

Weekly Recap (Nov 7, 2025)

29 talks from the 2025 Nextflow Summit are now available on YouTube

Nextflow Summit 2025 Talks on YouTube

posit::conf(2025) &amp; Nextflow Summit talks, bioRxiv+medRxiv AI reviews, R updates (R Data Scientist, R weekly), Claude Scientific Skills, Python package development for R users, new papers &amp;

Weekly Recap (Nov 14, 2025)

I'm still catching up on papers from my late 2024 backlog. This week’s recap highlights autonomous microbial sensors for detecting TNT in soil, genome size estimation from long reads, STABIX for indexing and compressing GWAS summary statistics, and Clair3-RNA for deep learning-based small variant calling on long-read RNA-seq data.

Stephen Turner

Autonomous microbial sensors for detecting TNT in soil, genome size estimation from long reads, indexing + compressing GWAS summary stats, Clair3-RNA for small variant calling on long-read RNA-seq...

Weekly Recap (Jan 2025 part 2)

An AI Manhattan Project for Science and Biotech

The Genesis Mission

R updates (R Data Scientist, R+AI conference, R weekly), Claude 4.5 Opus, Genesis Mission, AI+science, AI updates (Posit, AI Data Scientist), missing heritability, AI+edu, biotech, AIxBio, new papers

Weekly Recap (Nov 26, 2025)

This week’s recap highlights compendium of human gene functions derived from evolutionary modelling from the Gene Ontology Consortium, an AI reasoning model applied to rare disease diagnosis, an agentic AI for scRNA-seq data exploration, and applying FAIR principles to scientific workflows.

Comprehensive evolutionary modeling of human gene function, an AI reasoning model for rare disease diagnosis, an AI agent for scRNA-seq data exploration, FAIR scientific workflows, ...

Weekly Recap (May 2025, part 2)

RAND Report: Why biology still favors the offense in biosecurity

Asymmetries in Biosecurity

Most graduate students propose to do too much

Bioconductor on GPUs, tidyomics, Quarto 1.8, Anthropic red-teaming on AIxBio, PGS in the clinic, Shock Doctrine in genome engineering, GenAI for data viz with R, Datapalooza, 4 compact rejections

Weekly recap (Oct 17, 2025)

In the spirit of learning in public,1 today I learned about the .keep argument in dplyr. This doesn’t add anything you can’t do with a select or transmute, but might help simplify some of your dplyr pipelines.2 In the examples below I’m using a few rows from the built-in iris dataset to demonstrate how to use the .keep argument by creating a new ratio variable that’s the ratio of the sepal length to width.

Use the .keep argument in dplyr::mutate() to control which variables to retain after mutating to create new variables.

TIL: dplyr::mutate()'s .keep argument

If you use ChatGPT, Claude, or even some local model through Ollama or HuggingFace Assistants, you’ll know that the chat interface makes it challenging to feed in an entire repo like a Python or R package, because functions, tests, etc. can be scattered across many files throughout a repo.

The open source repo2txt web app will take a GitHub repo URL, displays the directory structure, lets you choose which files to include, and provides a single plain text file you can feed into any LLM.

Turn a GitHub repo into a single text file for LLM-friendly input

Last year I wrote a post describing an R package I put together that fetches recent bioRxiv preprints from a given subject and summarizes them in a couple of sentences using a local LLM running through Ollama:  That tool has a limitation in that it’s using the bioRxiv RSS feed to pull recent paper titles and abstracts, and the RSS feeds currently only provide the 30 most recent preprints in each subject area.

Collect metadata and publication details for &gt;200k preprints over a 10 year period, investigate trends, and scrape full text for sentiment analysis

Exploring the bioRxiv API with R, httr2, rvest, tidytext, and Datawrapper

This week’s recap highlights the Rust-based wgatools for manipulating alignments and visualizing in the terminal, the nf-core scnanoseq Nextflow pipeline for ONT scRNA-seq, sawfish for better SV discovery and genotyping with long reads, the BINSEQ high-performance binary formats for nucleotide sequence data, and a unified analysis of atlas single-cell data.

Rust-based wgatools for alignment manipulation &amp;

Weekly Recap (July 2025, part 1)

Recap of the first R User Group event in Charlottesville VA

Charlottesville R Users

AI-generated genomes, R news for my posit::conf() FOMO, biosecurity, mirror life, teaching and AI, ELSI for AI, in defense of CRAN, Anthropic Economy Index, OpenAI report on how people use ChatGPT

Weekly recap (Sep 19, 2025)

Cite:

Stephen Turner. “Learning in Public.”

 Paired Ends

(2024). DOI: https://doi.org/10.59350/xwgsf-nj906. I wrote my first public blog post in 2009. I started Getting Genetics Done to share what I was learning at the end of my PhD/postdoc through my first few years as faculty.

A short essay on writing about what you're learning

Learning in Public

I am in the middle of writing a review / perspectives paper. One that I’m confident will be exciting once we get it published. Some sections of the review cover subject matter at the outer periphery of my expertise.

Listen now | Inciteful with the Zotero plugin is the perfect combo for filling in gaps in your knowledge of the literature in a particular field. BioloGPT and Semantic Scholar are useful too.

Inciteful+Zotero to find relevant literature

It’s a short week here in the US. As I reflect on the tools that shape modern bioinformatics and data science it’s striking to see how far we’ve come in the 20 years I’ve been in this field. Today’s ecosystem is rich with tools that make our work faster, better, enjoyable, and increasingly accessible.

Data science and bioinformatics tech I'm thankful for in 2024: tidyverse, RStudio, Positron, Bluesky, blogs, Quarto, bioRxiv, LLMs for code, Ollama, Seqera Containers, StackOverflow, ...

Tech I'm thankful for (2024)

This week’s recap highlights a new multispecies codon optimization method, personalized pangenome references with vg, a commentary on the wild west of spike-in normalization, a new pipeline for comprehensive and scalable polygenic scoring across ancestrally diverse populations, a paper showing deep learning / transformer-based methods don’t outperform simple linear models for predicting gene expression after genetic perturbations, and finally, a

What I'm reading this week on multispecies codon optimization, personalized pangenome references, spike-in normalization, automating polygenic scoring, transformers vs linear models, bactoneurons, ...

Weekly Recap (Oct 2024, part 1)

Biobank-scale relatedness estimation, SNP calling and phasing with long RNA-seq reads, predicting expression-altering promoter mutations with DL, cross-species filtering for comparative genomics, ...

Weekly Recap (Sep 2025 part 1)

Here are a few papers that caught my attention recently. I summarize a few in the deep dive at the top, then link to a few other papers of note later on. Subscribe to Paired Ends to get periodic summaries like this delivered to your e-mail.

What I'm reading this week in genomics, bioinformatics, cancer biology, epigenome editing, biosecurity, synthetic biology, single-cell omics, population genetics, microbial genomics, ...

What I'm reading (Aug 2024, part 2)

I started my academic career in biomedical research as faculty in the University of Virginia (UVA) School of Medicine. After eight years I jumped to industry &amp;

Some personal news: I'm joining the University of Virginia as Associate Professor of Data Science and Assistant Dean of Research in UVA's new School of Data Science.

Returning to Academia: UVA Data Science

I had good intentions to give NaNoWriMo a try this year but didn’t get very far. Instead I gave OpenAI’s Creative Writing Coach GPT a try for a (very) short story I had in mind, inspired by my frustration trying to access closed-access research articles for a review article I’m preparing.

A parable of scientific publishing, open access, and preprints

The Enlightenment Conservatory

This week’s recap highlights an AI agent for automated multi-omic analysis (AutoBA), rapid species-level metagenome profiling and containment (sylph), a review on genome-wide association analysis beyond SNPs, private information leakage from scRNA-seq count matrices, and a method to “unlearn” viral knowledge in protein language models as a means to develop safe PLM-based variant effect analysis (PROEDIT).  Others that caught my attention include

What I'm reading in agentic multiomic analysis, metagenome profiling, GWAS beyond SNPs, private information leakage from scRNA-seq, unlearning viral knowledge for safe protein language models, ...

Weekly Recap (Nov 2024, part 2)

karyoploteR

is an R package that’s been in Bioconductor for nearly a decade. It lets you create linear chromosomal representations of any genome with genomic annotations and experimental data plotted along them.

 Bioconductor

: https://bioconductor.org/packages/karyoploteR/

 Tutorial

: https://bernatgel.github.io/karyoploter_tutorial/

 Paper

: Bernat Gel &amp; Eduard Serra. (2017).

Demos plotting genome density, per-base coverage, structural variation, GWAS Manhattan plots, combine multiple data types, gene expression results from DESeq2, epigenetic regulation from ENCODE

Plot Data Along a Genome with karyoploteR

Yesterday I wrote about base R vs. dplyr vs. duckdb for a simple summary analysis. In that post I simulated 100 million rows of a dataset and wrote to disk as CSV. I then benchmarked how long it took to read in and compute a simple grouped mean. One thing I

 didn’t

do here was separate the time it took to read data into memory (for base R and dplyr) versus computing the actual summary.

Parquet is interoperable between Python and R, fast to read+write, works well with databases, and stores complex data types (e.g., tibble listcols). Use it instead of CSV. Many pros, few (no?) cons.

Use nanoparquet instead of readr/CSV

This post expands on a few of the papers I posted in this Twitter thread. I highlight a few in the deep dive at the top, then link to a few other papers of note later on. Subscribe to Paired Ends to get summaries like this delivered to your e-mail as soon as I write them. Subscribe now You might remember me from Getting Genetics Done where I blogged about genetics, statistics, and bioinformatics from 2008-2017.

What I’m reading this week in synthetic biology, population genetics, AI in genomics/bioinformatics, pangenomes, and more

What I'm reading (July 2024, part 2)

This week’s recap highlights nanoMDBG for metagenome assembly from nanopore reads, the SCassist AI-based workflow for single-cell analysis, discovery and characterization of GxE and GxG effects in a vertebrate model, the PIGEON framework for estimating gene-environment interaction for polygenic traits, and long-read alignment with multi-level parallelism.

Metagenome assembly from nanopore reads, AI for single-cell analysis, GxE + epistasis in a vertebrate model, estimating GxE for polygenic traits, long-read alignment, agents, nf-core, ...

Weekly Recap (Aug 2025, part 2)

This post is inspired by the Bluesky Network Analyzer made by @theo.io.

I’m encouraging everyone I know online to join the scientific community on Bluesky. In that post I link to several starter packs — lists of accounts posting about a topic that you can follow individually or all at once to start filling out your network. I started following accounts of people I knew from X and from a few starter packs I came across.

Find people followed by the people you follow, but who you don't follow, using R and the atrrr package

Expand your Bluesky network with R

This week's recap highlights a new pipeline for metagenome quality assessment and taxonomic annotation (MAGFlow &amp;

Nextflow for metagenomics QA &amp; taxonomic classification, SNP/SV benchmarking, SNV calling with nanopore data, assembly polishing with transformers, Nextflow for variant simulation &amp; evaluation, ...

Weekly Recap (Nov 2024, part 1)

I just returned from a week in Barcelona where I attended the Nextflow Summit and nf-core hackathon, and I can hardly contain my excitement for the near term future of bioinformatics, computational biology, and open science in general.

Highlights from the 2024 Nextflow Summit and nf-core hackathon in Barcelona

Nextflow Summit Barcelona 2024

TL;DR
 
 : For a very simple analysis (means by group on 100M rows), duckdb was 125x faster than base R, and 28x faster than readr+dplyr, without having to read data from disk into memory. The duckplyr package wraps DuckDB's analytical query processing techniques in a dplyr-compatible API. Learn more at duckdb.org/docs/api/r and duckplyr.tidyverse.org.

I wanted to see for myself what the fuss was about with DuckDB.

Using DuckDB in R to analyze 100 million rows of data in 3 seconds

DuckDB vs dplyr vs base R

It’s been a big week in the genomics+bioinformatics space. This post expands on a few of the recent papers I posted in a Twitter thread. I highlight a few in the deep dive at the top, then link to a few other papers of note later on. Subscribe (free!) to Paired Ends to get summaries like this delivered to your e-mail as soon as I write them.

What I'm reading this week in SV analysis with long reads, spatial transcriptomics, gene prediction and annotation, synthetic biology, AI in genomics &amp;

What I'm reading (Aug 2024, part 1)

TL;DR:
 
 Codeium offers a free Copilot-like experience in Positron. You can install it from the Open VSX registry directly within the extensions pane in Positron.

Positron doesn't have GitHub Copilot, but Codeium and others are good alternatives.

AI code completion in Positron

This week’s recap highlights a Nextflow pipeline for eQTL detection, an end-to-end pipeline for spatial transcriptomics (visium) data analysis, a method for identification of perturbed cell types in single cell RNA-seq data, a method for guide assignment in single-cell CRISPR screens, a tool for on-target/off-target analysis of gene editing outcomes, and “digital microbes” for collaborative team science on emerging microbes.

A new eQTL Nextflow workflow, spatial transcriptomics / scRNA-seq, guide assignment in CRISPR screens, on-/off-target analysis after CRISPR editing experiments, digital microbes, paleogenomics, ...

Weekly Recap (Sep 2024, part 5)

I recently stumbled across Phil Ewels’s ~18 minute nf-core/bytesize talk on Excalidraw: For years I’ve been using draw.io for making flowcharts and diagrams for documentation, papers, presentations, and for general brainstorming and communication with my team, clients, and collaborators.1 Excalidraw (excalidraw.com) looks like an attractive alternative.

Excalidraw might be my new go-to open-source tool over draw.io for creating and sharing workflow diagrams. It's simple, fast, aesthetically pleasing, and has amazing VS Code integration.

Excalidraw: create and share workflow diagrams with end-to-end encryption

Google has a new experimental1 tool called Illuminate (

 illuminate.google.com

) that takes a link to a preprint2 and creates a podcast discussing the paper. When I tested this with a few preprints, the podcasts it generated are about 6-8 minutes long, featuring a male and female voice discussing the key points of the paper in a conversational style. There are some obvious shortcomings.

Listen now | Google's new Illuminate tool takes a PDF from arXiv and generates a short podcast discussion on the paper's key points

Illuminate preprints with an AI-generated podcast discussion

This week’s recap highlights a new tool from Wei Shen and Zamin Iqbal for efficient sequence alignment against millions of prokaryotic genomes (LexicMap), a new tool from Heng Li for efficiently constructing and querying a sequence index at scale, an R/Bioconductor package for detecting and correcting DNA contamination in RNA-seq data, a method for dating gene age using synteny, how AlphaFold predictions for some types of conformations are

What I'm reading this week in alignment and indexing millions of genomes at scale, gene age and family analysis and visualization, synthetic enhancers and cell fate programming, single cell omics, ...

Weekly Recap (Sep 2024, part 3)

Here we are most of the way through March and I’m just getting around to my first “weekly” recap. It’s been a busy month — I’m writing a few papers of my own which I’ll share here when they’re published, and I took some much needed R&amp;R in Portugal where I traded my stack of research papers for some escapist sci-fi. But I’m back now and making my way through a deep backlog.

Heritable polygenic editing, self-supervised learning in single-cell genomics, predictive modeling with tabular foundation models, ESM3, pangenome graphs in biodiversity genomics, ...

Weekly Recap (March 2025, part 1)

Background


 Bluesky, atrrr, local LLMs

I’ve written a few posts lately about Bluesky — first, Bluesky for Science, about Bluesky as a home for Science Twitter expats after the mass eXodus, another on using the atrrr package to expand your Bluesky network. I’ve also spent some time looking at R packages to provide an interface to Ollama.

Summary, translation, and sentiment analysis of Bluesky posts on a topic using atrrr, tidyverse/ellmer, and mlverse/mall with Claude and other open models, and gistr to put the summary on GitHub.

Bluesky conversation analysis with local and frontier LLMs with R/Tidyverse

Anyone reading this newsletter has surely used the frontier models like ChatGPT, Claude, and Gemini. I’ve written a few posts about using

 local

models but haven’t really talked much about the tools I use to directly interact with these models. Those previous posts interact with local models using tools like ellmer in R or my own biorecap package which interacts with a locally running Ollama server.

Running local LLMs with Ollama, LMStudio, Open WebUI, and others for private and secure chat, vibe coding, image analysis, and "chat with your documents" using RAG

GUIs for Local LLMs with RAG

I originally wrote and published this essay at The Connected Ideas Project, an excellent newsletter by my good friend and colleague Alexander Titus. If you’re not reading TCIP you’re missing out.

After I finished my postdoc I was faculty in academia for eight years before moving to a consulting firm for five years, then joined a biotech startup two years ago.

Thoughts and advice on transitioning from a career in academia to industry biotech. 2.4k words, 11 minute reading time.

Moving from academia to biotech

Happy New Year! I’m still catching up on papers from my late 2024 backlog.

Directed evolution by a protein language model, AI learning to run transcript assemblers, a review/introduction to pangenomics, Alphafold2 refinement for protein design, metagenomic binning...

Weekly Recap (Jan 2025, part 1)

This week’s recap highlights Verkko2 for T2T genome assembly, the GPN-MSA DNA language model trained on multispecies alignments for variant effect prediction that outperforms other methods like CADD, ESM-1b, phyloP, phastCons, nucleotide transformer, and HyenaDNA, fast orthology inference with FastOMA, a foundation model of transcription across cell types, and engineering CRISPR-Cas PAM sites using deep learning.

T2T assembly, DNA language models for variant effect analysis, ortholog inference at scale, a foundation model of transcription across cell types, engineering PAM recognition, &amp; a few great reviews...

Weekly Recap (Feb 2025, part 3)

This week’s recap highlights a new Nextflow workflow for calculating polygenic scores with adjustments for genetic ancestry, a paper demonstrating that whole exome plus imputation on more samples is more powerful than whole genome sequencing for finding more trait associated variants, a new deep-learning-based splice site predictor that improves spliced alignments, a new method for accurate community profiling of large metagenomic datasets, and

Nextflow workflow for polygenic scoring, WES+imputation &gt; WGS, DL method for splice site prediction, metagenomics profiling, and a new NIST/GIAB matched tumor-normal with 13 sequencing modalities

Weekly Recap (Oct 2024, part 3)

The Baader–Meinhof phenomenon (aka the frequency illusion) is the name for that thing that happens when you buy a new car, and suddenly you notice that same model car everywhere you drive.

Something a little different this week: book recommendations! De-extinction is a common theme across a few of the fiction and nonfiction books I read this year.

What I'm reading: de-extinction edition

There was a time in late 2023 to early 2024 when I and probably many others in the R community felt like R was falling woefully behind Python in tooling for development using AI and LLMs. This is no longer the case. The R community, and Posit in particular, have been on an absolute tear bringing new packages online to take advantage of all the capabilities that LLMs provide.

Python isn't the only game in town anymore: R can interact with local and cloud LLM APIs, inspect and modify your local R environment and files, implement RAG, computer vision, NLP, evals, &amp;

The Modern R Stack for Production AI

This week’s recap highlights the WorkflowHub registry for computational workflows, building a virtual cell with AI, a review on bioinformatics methods for prioritizing causal genetic variants in candidate regions, a benchmarking study showing deep learning methods are best for variant calling in bacterial nanopore sequencing, and a new ML model from researchers at Genentech for predicting cell-type- and condition-specific gene expression across

WorkflowHub computational workflow registry, building a virtual cell with AI, bioinformatics for prioritizing causal variants, DL methods for nanopore variant calling, predicting gene expression, ...

Weekly Recap (Dec 2024, part 1)

Llama 3.1 405B is the first open-source LLM on par with frontier models GPT-4o and Claude 3.5 Sonnet. I’ve been running the 70B model locally for a while now using Ollama + Open WebUI, but you’re not going to run the 405B model on your MacBook.

How to create and deploy a free GPT4-class chatbot on HuggingFace Assistants for any GitHub repo, using an R package as an example, in less than 60 seconds

Create a free Llama 3.1 405B-powered chatbot on a GitHub repo in &lt;1 min

This is an experiment... ignore this post

Paired Ends Podcast

Apple gets into protein folding, parsing R/Markdown and Quarto, vibe-coding an R package, AI in biosecurity and writing, nothing about AI is inevitable, conservation applications of de-extinction tech

Weekly recap (Sep 26, 2025)

Today I learned you can create and customize ggplot2 visualizations using your voice alone.

Voice control ggplot2 with ggbot2

Update March 2025
 
 : The preprint described in this paper is now peer-reviewed and published in PLoS ONE.


 
 VP (Pete) Nagraj
 
 is a long time friend, colleague, and collaborator, and is the author of this post. Pete and I have co-authored over a dozen publications, and have taught several graduate courses in data science together.

PLANES provides a set of methods for evaluating the plausibility of epidemiological signals and forecasts. The PLANES methods are available in the rplanes R package and Shiny app.

PLANES: Plausibility Analysis of Epidemiological Signals

I'm still catching up on papers from my late 2024 backlog. This week’s recap highlights a browser application for visualizing pathogen dispersal, a DNA language model evaluation benchmark on regulatory DNA, regularized ensemble polygenic risk prediction with GWAS summary statistics, multimodal analysis of RNA-seq data for complex trait genetics, and a deep dive on blastp’s E-value.

Visualizing pathogen dispersal, DNA language model benchmarks for regulatory DNA, polygenic risk prediction with GWAS summary stats, multimodal analysis of RNA-seq data, blastp's E-value, ...

Weekly Recap (Jan 2025 part 3)

This is part 4 of a series on uv. Other posts in this series:


 uv, part 1: running scripts and tools


 uv, part 2: building and publishing packages


 uv, part 3: Python in R with reticulate

I’ve never been a big fan of notebooks, and I’m not the only one. Out of order code execution, hidden state, difficulty diffing in version control, output bloat, etc.

Using uv with Jupyter: demo using polars and seaborn for analysis and visualization.

uv, part 4: uv with Jupyter

This week’s recap highlights analysis of human de novo mutation rates from a four-generation pedigree reference, how LLMs internalize scientific literature and citation practices, the py_ped_sim forward pedigree and genetic simulator for complex family pedigree analysis, and a review on predicting gene expression from DNA sequence using deep learning models like Enformer and Borzoi.

De novo mutation rates from a 4-gen pedigree, how LLMs internalize scientific literature, pedigree and genetic data simulations, a review on predicting gene expression from DNA sequence using LLMs...

Weekly Recap (Aug 2025, part 3)

I liked Steve Krouse’s essay, “Vibe code is legacy code.” It helped crystalize some half-baked thoughts I have on vibe coding. Here’s an excerpt.Subscribe now

 Maintainability and vibe are inversely correlated

I’ve been using GitHub copilot and chatbots for code for years, and I’ve written about them a lot here.

Vibe code is legacy code

This week’s recap highlights a new method for gene-level alignment of single-cell trajectories, an R package for integrating gene and protein identifiers across biological sequence databases, characterization of SVs across humans and apes, universal prediction of cellular phenotypes, a method to quantify cell state heritability versus plasticity and infer cell state transition with single cell data, and a new AI-driven, natural language-oriented

Gene-level alignment of scRNA-seq trajectories, integrating identifiers across databases, SVs in humans and apes, universal prediction of cellular phenotypes, and a bioinformatics analysis chatbot

Paired Ends

Quoting Kevin Roose (NYT / Hard Fork)

Weekly Recap (December 4, 2025)

The Age of AI in the Life Sciences: Benefits and Biosecurity Considerations

NeurIPS 2025 Workshop on Biosecurity Safeguards for Generative AI