Data Analysis Rigor and Reproducibility, Part 2 - Analysis Tools
September 24, 2019
Sofie Van Gassen, Ph.D.
VIB-UGent Center for Inflammation Research
Moderated by Lola Martinez Garcia
About the Presenter
Sofie Van Gassen received her M.S. degree in Computer Science from Ghent University in 2013 and her Ph.D. in Computer Science Engineering from Ghent University in 2017. During her Ph.D., she developed machine learning techniques for flow and mass cytometry data. Since 2018, she is an ISAC Marylou Ingram Scholar, and as a postdoc she is further developing and improving machine learning techniques for single cell data in the DaMBi group (VIB - UGent Center for Inflammation Research).
Some of the current data analysis tools will be presented, including tools for visualization (e.g. SPADE, tSNE, UMAP), for automated gating (e.g. flowDensity, flowLearn) and for population discovery (e.g. Citrus, FlowSOM, CellCNN). Detailed pros and cons of these methods will be highlighted along with a discussion on how to pick a good tool.
- Learn about the dimensionality reduction algorithms, clustering algorithms and population discovery tools.
- Discuss guidelines and learn how to select which tool is best depending on a given situation.
Who Should Attend
Anyone exploring which analysis tools they could apply to their cytometry data.