Leo Lahti

Join us as Assistant/Associate/Full Professor Computational Biology at Institute of Biology Leiden (IBL) / @leidenscience.bsky.social / @unileiden.bsky.social

Application deadline on 15 March 2026
👇
careers.universiteitleiden.nl/job/Assistan...

Metax looks really nice for taxonomic profiling: www.biorxiv.org/content/10.6...

One more day to submit an abstract (talk / poster / demo / workshop) at the European Bioconductor conference EuroBioC2026 in Finland, June 1-5. DL Feb 13!

If you study microbiome Time series (gut, soil or mangroves -> like me) you want to know this...

#miaTime (new on #Bioconductor3.22) gives you:

🟢 Divergence
🟢 Short-term change
🟢 Bimodality

Thanks to the devs: @antagomir.bsky.social @tuomasborman.bsky.social

#RStats #Microbiome #Bioconductor

Posterior-SBC now also with peer-review stamp in Statistics and Computing doi.org/10.1007/s112... (update your bib files)

A Bayesian approach to differential prevalence analysis with applications in microbiome studies Recent evidence suggests that analyzing the presence/absence of taxonomic features can offer a compelling alternative to differential abundance analysis in microbiome studies. However, standard approa...

A Bayesian approach to differential prevalence analysis with applications in microbiome studies ("DiPPER") arxiv.org/abs/2602.05938

Digitaalinen itsenäisyys – Suomen seuraava kohtalonkysymys 🇫🇮

Suomi on riippuvainen yhdysvaltalaisista teknologiajäteistä. Riippuvuus ei lähitulevaisuudessa vähenny vaan syvenee.

#DigitaalinenItsenäisyys #Suomi #Kansalaisaloite

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🚀 We’ve just kicked off the first edition of the course ORCHESTRATING MICROBIOME ANALYSIS WITH @bioconductor.bsky.social !
Excited to dive deep into microbiome data analysis using powerful Bioconductor tools with @antagomir.bsky.social & @tuomasborman.bsky.social

#Microbiome #Bioinformatics

Vastusta avoimen koodin uhkasakkoa – allekirjoita vetoomus COSS on laatinut toimitettavaksi lausunnon hallituksen esityksestä, joka koskee EU:n kyberkestävyysasetuksen (CRA) toimeenpanoa Suomessa.

Suomi kiristäisi avoimen koodin sääntelyä haitallisesti - vastusta ylimääräistä uhkasakkoa avoimelle koodille ja allekirjoita vetoomus coss.fi/uutiset/suom...

Orchestrating Microbiome Analysis with Bioconductor 2–6 February 2026

Are you working with #microbiome data and looking for a clear, practical way to analyse it in @bioconductor.bsky.social?
Last places available for our online course with @antagomir.bsky.social @antagomir.bsky.social @tuomasborman.bsky.social 2–6 February

www.physalia-courses.org/courses-work...

Biomedical and life science articles by female researchers spend longer under review Women are underrepresented in academia, especially in STEMM fields, at top institutions, and in senior positions. This study analyzes millions of biomedical and life science articles, revealing that f...

Cost of being female lead/corresponding author in biomedical sciences: "[T]he median amount of time spent under review is 7.4%–14.6% longer for female-authored articles than for male-authored articles" even in disciplines where women well-represented. #AcademicSky

journals.plos.org/plosbiology/...

ELLIS Institute Finland @ellisinstitute.fi has open call for postdocs (DL Feb 9) www.ellisinstitute.fi/postdoc-recr...

There are 45 PIs to choose from, and you can apply to work also with me on computational Bayesian modeling and Bayesian workflow!

Rarefaction is better than robust Aitchison PCA and other compositional data analysis methods at controlling for uneven sequencing effort www.biorxiv.org/content/10.6... #jcampubs

Exploring and Analyzing LC-MS Data This resource hosts tutorials and end-to-end workflows describing how to analyze LC-MS/MS data, from raw files to annotation, using Bioconductor packages.

🚀 New release: Metabonaut v1.4.0 is here!

1️⃣ New integration with the notame package for robust feature selection. 2️⃣ Added GNPS2 FBMN export for molecular networking.

Explore the updates: rformassspectrometry.github.io/Metabonaut/

#Metabolomics #RStats #OpenScience #MassSpec #Bioconductor

Omicslog – tidyomicsBlog Providing logging capabilities for SummarizedExperiment objects.

Reproducibility is key to science. In computational biology, we routinely manipulate high-dimensional data (spatial, single-cell, bulk) through filtering, normalisation and transformation. Capturing those steps clearly improves reproducibility and transparency.

tidyomics.github.io/tidyomicsBlo...

Keystone concept revisited: insights into microbial community dynamics and control - Nature Reviews Microbiology In this Perspective, Garza et al. revisit the keystone concept and discuss its relevance for microbial keystone taxa and functions. For this, they explore the different mechanisms behind keystoneness,...

www.nature.com/articles/s41...

Orchestrating Microbiome Analysis with Bioconductor 2–6 February 2026

Master #microbiome analysis with R/ @bioconductor.bsky.social ! Join our live online course Feb 2–6, with @antagomir.bsky.social & @tuomasborman.bsky.social
Dive into data import, diversity metrics, differential abundance, and multi-omics integration.
www.physalia-courses.org/courses-work...

We Made It! 🎉

25 days. Complete modern R package development workflow. From usethis automation to CRAN submission. You have everything you need!

#rstats #CRAN #RPackageAdvent2025 #ThatsAWrap

Screenshot of the course website

CSAMA 2026 - Biological Data Science Summer School
Bressanone-Brixen, South Tyrol / Italy
24-29 May 2026
csama2026.bioconductor.eu

Statistical & computational methods for single cell and spatial omics, with lectures and hands-on exercises in R/Bioconductor.

Benchmarking TCR-pMHC structure prediction: a unified evaluation and CDR3-based functional insights https://www.biorxiv.org/content/10.64898/2025.11.30.691400v1

Comparative Assessment of Large Language Models for Microbial Phenotype Annotation Large language models (LLMs) are increasingly used to extract knowledge from text, yet their coverage and reliability in biology remain unclear. Microbial phenotypes are especially important to assess...

New preprint out now!
Comparative Assessment of Large Language Models for Microbial Phenotype Annotation
www.biorxiv.org/content/10.1...

Orchestrating Microbiome Analysis with Bioconductor 2–6 February 2026

Join our online course Orchestrating Microbiome Analysis with @bioconductor.bsky.social (2–6 Feb 2026)! Learn hands-on microbiome data analysis, diversity metrics, and multi-omics integration with @antagomir.bsky.social & Tuomas Borman .

www.physalia-courses.org/courses-work...

We have a date for the free-to-attend #anvio workshop and ECR Symposium for 2026, and we look forward to meeting you at the @hifmb.de in Oldenburg, Germany!

Please find more information on the venue, program, and the application form here, and spread the word 😇

anvio.org/workshops/20...

Sisäministeri Rantanen saa oman ICE:n? Ei säännöksiä eduskunnan osallistumisesta, oikeasuhtaisuudesta, välttämättömyydestä. Ei tarvittaisi edes hallituksen päätöstä vaan sisäministeri päättäisi itse. Poliisilakiin ehdotetun uuden 15k §:n 3 mom. antaisi avoimen harkintavallan lähettää ICE kaduille

A table showing profit margins of major publishers. A snippet of text related to this table is below. 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.

A figure detailing the drain on researcher time. 1. The four-fold drain 1.2 Time The number of papers published each year is growing faster than the scientific workforce, with the number of papers per researcher almost doubling between 1996 and 2022 (Figure 1A). This reflects the fact that publishers’ commercial desire to publish (sell) more material has aligned well with the competitive prestige culture in which publications help secure jobs, grants, promotions, and awards. To the extent that this growth is driven by a pressure for profit, rather than scholarly imperatives, it distorts the way researchers spend their time. The publishing system depends on unpaid reviewer labour, estimated to be over 130 million unpaid hours annually in 2020 alone (9). Researchers have complained about the demands of peer-review for decades, but the scale of the problem is now worse, with editors reporting widespread difficulties recruiting reviewers. The growth in publications involves not only the authors’ time, but that of academic editors and reviewers who are dealing with so many review demands. Even more seriously, the imperative to produce ever more articles reshapes the nature of scientific inquiry. Evidence across multiple fields shows that more papers result in ‘ossification’, not new ideas (10). It may seem paradoxical that more papers can slow progress until one considers how it affects researchers’ time. While rewards remain tied to volume, prestige, and impact of publications, researchers will be nudged away from riskier, local, interdisciplinary, and long-term work. The result is a treadmill of constant activity with limited progress whereas core scholarly practices – such as reading, reflecting and engaging with others’ contributions – is de-prioritized. What looks like productivity often masks intellectual exhaustion built on a demoralizing, narrowing scientific vision.

A table of profit margins across industries. The section of text related to this table is below: 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.

The costs of inaction are plain: wasted public funds, lost researcher time, compromised scientific integrity and eroded public trust. Today, the system rewards commercial publishers first, and science second. Without bold action from the funders we risk continuing to pour resources into a system that prioritizes profit over the advancement of scientific knowledge.

We wrote the Strain on scientific publishing to highlight the problems of time & trust. With a fantastic group of co-authors, we present The Drain of Scientific Publishing:

a 🧵 1/n

Drain: arxiv.org/abs/2511.04820
Strain: direct.mit.edu/qss/article/...
Oligopoly: direct.mit.edu/qss/article/...

Orchestrating Microbiome Analysis with Bioconductor The expansion of microbiome research has led to the accumulation of interlinked datasets encompassing versatile taxonomic and functional assays. The analysis of increasingly large and heterogeneous…

Orchestrating Microbiome Analysis with Bioconductor. #Microbiome #DataAnalysis #Bioconductor @biorxivpreprint.bsky.social
www.biorxiv.org/content/10.1...

Orchestrating Microbiome Analysis with Bioconductor https://www.biorxiv.org/content/10.1101/2025.10.29.685036v1

Greetings from Brisbane, Int'l Data Week #IDW2025, SciDataCon25 & CODATA ExComm this week - -

Looking fwd to catch up! Also check this one:

"Open data science and responsible research" summarizing the national policy work on open methods in #Finland (Wed 2pm) lnkd.in/d7zBrNNn

mitochondria from bipolar patients are closer to the nucleus in these images; control patients' are spread out further

15 years in the making, we confirmed that mitochondria - the powerhouse of the cell - have an unusual localization in patients who experience psychosis (including schizophrenia and bipolar disorders). You’ll never guess what kind of patient cells we used to make this discovery… 🧵

Just published an interactive article about a magical algorithm known as the Burrows-Wheeler Transform, which powers sequence alignment tools like bowtie and bwa: sandbox.bio/concepts/bwt

It's also notoriously unintuitive so I'm hoping this article helps you build that intuition.