Youtor
UMAP Basics for Cytometry
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=puZuEAp8bJk
Understanding UMAP for High-Dimensional Cytometry in Drug Development • This webinar covers the basics of Uniform Manifold Approximation and Projection (UMAP) for interpreting high-dimensional cytometry data. It compares UMAP with Principal Component Analysis (PCA) and demonstrates how UMAP can more effectively distinguish between distinct cell populations in 2D visualizations. Using examples from published research and real datasets, the tutorial explains the clustering and dimensionality reduction processes, highlighting the advantages of UMAP for identifying rare or subtle cell populations relevant to drug response and toxicity. Ideal for drug developers looking to visualize complex data sets. • 00:00 Introduction • 00:39 Reminder about Principal Component Analysis (PCA) • 01:19 Comparing PCA and UMAP Visualizations • 03:56 Deep Dive into UMAP • 05:40 Real-World Applications of UMAP • 06:40 Simplifying UMAP with Fashion MNIST • 08:24 Applying UMAP to Cytometry Data • 09:10 Conclusion and Benefits of UMAP • References: • Dimensionality reduction for visualizing single-cell data using UMAP, Newell et al: https://www.nature.com/articles/nbt.4314 • UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction, McInnes et al: • https://arxiv.org/abs/1802.03426
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