MIT Deep Learning Genomics - Lecture 11 - RNA, PCA, t-SNE, Embeddings (Spring20)

MIT Lecture 11. Spring 2020 Course website: Lecture slides: Outline: 1. Gene expression analysis: The Biology of RNA-seq 2. Supervised (Classification) vs. unsupervised (Clustering) 3. Supervised: Differential expression analysis 4. Unsupervised: Embedding into lower dimensional space 5. Linear reduction of dimensionality - Principle Component Analysis - Singular Value Decomposition 6. Non-linear dimensionality reduction: embeddings - t-distributed Stochastic Network Embe