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.