Learn the fundamentals of Principal Component Analysis (PCA) in this 20-minute educational video. Explore key concepts such as dimensions, variance, covariance, and loading scores. Discover how to interpret PCA and MDS plots commonly found in RNA-seq results. Follow along with step-by-step explanations of PCA performance, including practical examples using R code. Gain insights into diagnostics using scree plots and understand the relationship between loadings and eigenvectors. Perfect for those seeking a clear and concise explanation of this essential statistical technique used in data analysis and dimensionality reduction.
Overview
Syllabus
Awesome song and introduction
An introduction to dimensions
Why we can omit dimensions
Principal components in terms of variance and covariance!!!
Transforming samples with loading scores
Review of main ideas
Scree plots for diagnostics
Loadings and Eignvectors
Taught by
StatQuest with Josh Starmer
