Registration is open for the Biological Data Science summer school 11-16 June in Brixen/Bressanone. It's a great opportunity to dive into multi-omics, single cell and spatial analysis, data integration, statistics, R & Bioconductor with top experts in the field. https://csama2023.bioconductor.eu

The one-week intensive summer school Biological Data Science teaches advanced computational analyses of modern molecular data types in biology and biomedicine, including single cell and spatial omics. It comprises lectures covering underlying theory and concepts, practical hands-on exercises, and informal discussion sessions. Lecture topics include modern biotechnologies for quantitative measurements, statistical analysis, visualisation, and computational tools. Hands-on exercises are looking at state-of-the-art datasets, using the R / Bioconductor environment. At the end of the course, you should be better able to design, implement and interpret analyses on your own (multi-)omic, single and/or spatial data, adapt and combine different tools, and make informed and scientifically sound choices about analysis strategies.

Lecture and Lab topics

• RNA-Seq from raw data to DESeq2: (quasi-)alignment, quantification at gene and transcript level, gamma-Poisson model, DESeq2
• Single cell (droplet based) RNA-seq: exploratory analysis, quality assessment, dimension reduction (incl., t-SNE, UMAP)
• Visualisation / graphics, PCA and other low-dimensional embeddings, Clustering, distances, nearest-neighbour graphs (with sc-RNA-Seq examples)
• Statistical hypothesis testing, false discovery rate, multiple testing, filtering and weighting
• Regression: more on design matrices, power, identifiability, diagnostics, generalized linear models for count data
• Classification / supervised machine learning
• Image-based data and Spatial omics (CODEX, MERFISH et al.)
• Introduction to the Bioconductor project (community, organisational structure, website, important infrastructure packages, data structures, annotation resources
• Immunobioinformatics
• Mass spectrometry-based proteomics and metabolomics
• Emerging topics and participant suggestions