@christofseiler.bsky.social

Applying statistics to biomedicine. ORCID: https://orcid.org/0000-0001-8802-3642

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 😀

Susan Holmes in an orange and pink dress, laughing.

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.

The speaker in front of her title slide.

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.

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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.

The speaker with her title slide

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.

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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.

The speaker showing a slide with a photo of people, including Susan, at a conference. In Switzerland.

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.

The speaker with his title slide

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.

The speaker and his title slide.

🌟 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

Flyer of the event.

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.

Ascona 2025 - Schedule

Tentative Conference Schedule

sites.google.com

Mark Robinson@markrobinsonca.bsky.social · 2y ago

so one last call .. abstracts due today (6pm, time zone of your choice 😀) .. Ascona, Switzerland in March 2025 .. conference about all things benchmarking: sites.google.com/view/ascona2... Abstract submission link: t.co/zGGZ9Xd60E

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...

LEMUR simplified | const-ae

A simplified implementation of the LEMUR algorithm.

const-ae.name

Constantin Ahlmann-Eltze@const-ae.bsky.social · 2y ago

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⬇️

Overview of the LEMUR steps: (1) subspace alignment, (2) differential expression, (3) DE neighborhoods, (4) pseudobulking.