Check out our new study entitled "Navigating sampling bias in discrete phylogeographic analysis: assessing the performance of an adjusted Bayes factor" and now published in Molecular Biology & Evolution: academic.oup.com/mbe/article/... (1/9)

A great opportunity to present and discuss about current research projects in the respective teams and beyond, enhancing interdisciplinarity, and opening new collaboration opportunities

Ongoing at the @ulbruxelles.bsky.social: the 4th edition of the Health Geography and Spatial Epidemiology workshop organised by the homonymous FNRS contact group (www.healthgeographygroup.eu)

that can test the impact of continuous environmental factors on the diffusion velocity of viral lineages. In order to evaluate the different methods, we also implemented two simulation frameworks to test and compare their statistical performance. - 4/8

We then use these two dispersal metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations. Our comparative analysis reveals a broad range of IBD patterns and diffusion coefficients (4/7)

a lineage dispersal velocity, a diffusion coefficient, and an isolation-by-distance (IBD) signal metric. Our results reveal that the diffusion coefficient and IBD signal metrics appear to be robust to the number of samples considered for the phylogeographic reconstruction (3/7)