PCA identifies linear combinations of genes such that each combination (called a Principal Component) explains the maximum variance. It's often used to make data easy to explore and visualize. We learned in the previous tutorial - https://www.youtube.com/watch?v=xuQYDMolqNM

, to build a PCA plot. This is an alternative method of PCA visualization using PCA draw, where you can analyze a table of gene expression and get a PDF scatterplot generated by an R script. Use this method to quickly view what is in your data. 

Learn about how PCA draw could be used to get a PCA plot for the dataset taken in the video attached and to unravel the step wise process for PCA exploratory analysis, visit - https://www.youtube.com/watch?v=1iXSkCCjVRI

To learn more about the basics of PCA and how to analyze the PCA plot, visit: https://learn.omicslogic.com/courses/course/course-5-transcriptomics