Announcing the Ascona Workshop "Statistical and AI methods for multi-modal multi-scale modeling of biological systems" on 28 June - 3 July 2026 in Ascona, CH www.huber.embl.de/group/events... Reserve the dates!

former BiGCaT colleague Serena Bonaretti has written the #openaccess book about #python: "Learn Python with Jupyter", now available from various stores and online at https://www.learnpythonwithjupyter.com/

🧬 EuroBioC2026 is coming to Turku, Finland, from June 3–5, 2026! Expect 3 exciting days with the Bioconductor community, showcasing the latest advances in Bioconductor software and emerging technologies shaping computational biology. 👉 More details soon at eurobioc2026.bioconductor.org

We close the day by many people thanking Susan Holmes for helping them with their data sets, loving the data, losing their fear of statistics, and her great teaching. Susan thanks everyone for them actually listening and doing what she told them to do 😀

Next up: Diana Proctor: Clonal Candida auris and ESKAPE pathogens on the skin of residents of nursing homes. She thanks Susan for surviving her PhD. Susan inspired her own lab principles, like open data and your code is good enough to publish! New work on Candida: pubmed.ncbi.nlm.nih.gov/40011766/

Next: Catherine Blish: Mapping cell-cell communication to understand host-pathogen interactions She met Susan at a women’s faculty network event that she almost did not go to, and now they published over 30 papers together. Study of the harmony of immune cell communication using Scriabin.

Next: Jess Grembi with ‘Uncovering the latent variable in my statistical trajectory’ Jess was asked to beta-test Susan’s book, which was helpful to both. Working with a statistician is better than trying to become one. Thank you, Susan to make statistical methods accessible for biologists.

Next: Julia Fukuyama: The power of multiple views for exploring diversity across phylogenetic scales There are many ways of measuring distances between communities, taking phylogenetic relations between the species into account.

Next: Pratheepa Jeganathan (online): Spatial Statistics Meets Biology: Extending Constrained Clustering with Spatial Pattern Similarity How can we detect tumor micro-environments? Susan’s book chapter on image analysis has helped us choose appropriate methods.

Next: Nikos Ignatiadis How does variance moderation for differential expression work? How to best analyze small variations in a set of 400k probes (genes) and large numbers of samples measured in two experimental conditions.

After lunch: Wolfgang Huber (online) with: Single cell differential expression without discrete cell types Can we replace +/- cell type characterization with a continuous parameterization? Susan and I wrote a book together: www.huber.embl.de/msmb/ Modern Statistics for Modern Biology

Next: Christof Seiler: Prediction Intervals at the Tour de France Using AI to predict calorie consumption, to plan meals for cyclists. Used variables such as race type, BMI, weather etc. We also can calculate and correct for spillover in flow cytometry data.

Next: Joey McMurdie: From R packages to Human Disease Startups: A Journey in Statistical Biology with guidance from Susan Holmes He shares a timeline of his life with Susan, as his PhD committee, postdoc advisor, advisory board, and co-author. Together, they wrote phyloseq and dada2.

Today I will be attending a conference at Stanford University, in honor of Susan Holmes, who is retiring. She has been an essential driving force for our microbiome research. Bridging Biology and Statistics: Insights and Innovations for Modern Biology www.eventcreate.com/e/stats4mode...

EuroBioC goes south! The most south since… ever? Come join us in Barcelona 🇪🇸 for great science, community, and scholarly chats by the sea 🌊

Heads-up that Genome Biology is starting a new benchmark collection ("Benchmarks v2.0"): www.biomedcentral.com/collections/...

📣 EuroBioC2025: Abstract Submissions Open! Join us in Barcelona, Spain 🇪🇸, Sep 17-19, 2025, for the European Bioconductor Conference! Submit your abstract for a short talk, workshop, or poster by Apr 24. ➡️ Submit https://buff.ly/3EN9w6P #EuroBioC2025 #Bioinformatics #RStats #DataScience

🌟 Upcoming Online Seminar: Immune Dysregulation in Sjögren's Disease 🌟 Our Department of Rheumatology is excited to host this seminar discussing multiomics approaches, spatial techniques, and disease pathology. 📍Zoom: uzh.zoom.us/j/6944721108... 📅 Thursday, June 19, 16.00-17.30 CET

Comparison and evaluation of methods to infer gene regulatory networks from multimodal single-cell data | bioRxiv www.biorxiv.org/content/10.1...

Quick update. We have a pretty exciting lineup of topics/speakers in and around benchmarking that will be presented in Ascona at the end of the month: sites.google.com/view/ascona2... There are few registration slots left, so if you are interested to join us, get in touch.

Lovely little pedagogical note; well worth a look. arxiv.org/abs/2502.02305 'Information-Theoretic Proofs for Diffusion Sampling' - Galen Reeves, Henry D. Pfister

For the Monday morning crowds :) Also take a look at my blog post where I compress the full lemur package into 100 lines of code and explain the core algorithm. const-ae.name/post/2025-01...

After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳 www.nature.com/articles/s41... LEMUR is a tool to analyze multi-condition single-cell data and model differential expression as a continuous function of the cell-state space. Some highlights⬇️

How to do differential expression with scRNAseq data? State of the art is "pseudo-bulk" analysis with RNA-seq methods like edgeR or DESeq2, where "cell type" is encoded as discrete categories. Biologically, discrete categories are not always the most appropriate concept.(1/3) doi.org/10.1038/s415...

1/7 Planning to build a single-cell atlas? Or wondering how atlases can be useful to your research? Read our guide on single-cell atlases www.nature.com/articles/s41... published in Nature Methods, by @lisasikkema.bsky.social, @khrovatin.bsky.social, Malte Luecken, @fabiantheis.bsky.social et al.

Have you been thinking hard about statistical modelling of scATAC-seq data? (No.) Luckily for you, @aaronkwc.bsky.social has! Aaron will help you grok: What's going on? What is TF-IDF? Is there really single-cell level chromatin information? Check it out 👇 www.biorxiv.org/content/10.1... 🧪🧬💻

Major milestone: Tabula Sapiens 2.0 maps tissue composition & TF expression in 175 cell types, identifying 745 ubiquitous & 890 cell type-specific TFs (many still uncharacterized -> #Codebook) w/ roles in tissue homeostasis, stress response & metabolism. #SingleCell www.biorxiv.org/content/10.1...

Now on biorxiv! The JUMP-Cell Painting Consortium’s paper: “Morphological map of under- and over-expression of genes in human cells” This is the genetic perturbation portion of the JUMP’s dataset; our chemical perturbation paper will come in a few months www.biorxiv.org/content/10.1...

Interested in spatial statistics for spatial omics data? Check out our new resource: pasta. We show how different technologies lead to different data modalities give and overview of point-pattern and lattice-based spatial analysis. Feedback welcome! arxiv.org/abs/2412.01561

Not checking nuclear markers like MALAT1 or intronic reads in your scRNA-seq data?🚨 We show their power to flag low-quality cells—even in top public datasets. It’s time to prioritize better QC for cleaner, more reliable genomics research! Read more: bmcgenomics.biomedcentral.com/articles/10.... 1/8

Idea: - Get challenging samples, best would be human disease (e.g. cancer, neurodegeneration) - Do single nuclei experiment with SmartSeq - Image each well, and annotate the images with "intact", "lysed", etc (maybe you annotate a subset, then train a classifier) - Link QC metrics to labels - Profit

A little piece that's been in the works with former MSc, now PhD student, Jiayi Wang & @markrobinsonca.bsky.social in the multi-sample/-condition/-subpopulation theme: ...

spillR: Spillover Compensation in Mass Cytometry Data https://www.biorxiv.org/content/10.1101/2023.10.04.560870v1

Anastasios N. Angelopoulos, Rina Foygel Barber, Stephen Bates Theoretical Foundations of Conformal Prediction https://arxiv.org/abs/2411.11824