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Medical Research Seminar: Extracting the most out of your single-cell data
August 31 @ 12:00 pm - 1:00 pm
Professor Jean Yang
University of Sydney
About the talk: Recent advances in large-scale single-cell transcriptome profiling have allowed for high-resolution studies of cell heterogeneity, developmental dynamics, and cellular communication across a wide range of biological systems. Concerted examination of multiple collections of single-cell data from the same or multiple platforms promises further biological insights that cannot be uncovered with individual datasets. We will discuss a number of approaches developed at the Sydney Precision Bioinformatics to address methodological challenges in this area. This includes the development of algorithms for effective interrogation of multiple single-cell datasets from single-modality, integration of different modalities as well as cell type annotation based on cell type hierarchies constructed from single or multiple annotated datasets as references. All our approaches’ effectiveness is demonstrated through extensive comparisons with other approaches using a large collection of publicly available single-cell data sources. Finally, we show how these methodologies contribute to a generalizable workflow that explores cell-cell interactions in a set of single-cell datasets and assesses molecular patterns associated with disease severity.
About the Speaker: Professor Jean Yang is an applied statistician with expertise in statistical bioinformatics. She was awarded the 2015 Moran Medal in statistics from the Australian Academy of Science in recognition of her work on developing methods for molecular data arising in cutting edge biomedical research. Her research stands at the interface between medicine and methodology development and has centred on the development of methods and the application of statistics to problems in -omics and biomedical research. As a biomedical data scientist, she enjoys research in a collaborative environment, working closely with clinical scientific investigators from diverse backgrounds.
Read more about Professor Jean Yang’s work here.