Combine complementary omics measurements to identify biological pathways and model cellular behaviour. Lectures and practicals compare supervised feature selection and integration using LASSO, PLS, LDA, mixOmics and DIABLO with unsupervised MOFA models and deep-learning autoencoders. The final day covers dimensionality reduction, graph-based integration, batch correction and multimodal single-cell analysis using Seurat and weighted nearest neighbours. Participants learn to select and implement an integration strategy suited to their research question. Live online, 15–17 February, 14:00–19:00
In Biostatistics and Statistics
Seminar · Cognition
Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners
Ivan Simpson-Kent · University of Cambridge, MRC CBU
Wed, Jun 2, 2021 · 15:00 UTC
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g. specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior r