Data Analysis Rigor and Reproducibility, Part 2: Analysis Tools
Recorded On: 09/24/2019
About the Presenter
Sofie Van Gassen, PhD
Gent University Center for Inflammation Research
Sofie Van Gassen received her MS in computer science from Ghent University in 2013 and her PhD in computer science engineering from Ghent University in 2017. During her PhD, she developed machine learning techniques for flow and mass cytometry data. She is an ISAC Marylou Ingram Scholar. 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), automated gating (e.g., flowDensity, flowLearn), and 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 analysis tools they could apply to their cytometry data.
CMLE Credit: .75