This is a full walkthrough of a bioinformatics project: Run PCA/TSNE on some population genotype data. 00:00 Intro 01:07 Hunting for data 04:55 Inspecting the VCF 06:02 Finding population labels for the samples 10:20 Parsing VCF with pysam 16:02 Going from alleles to numbers for a numpy array 21:47 When to work in colab versus python script 26:00 Saving data with pandas 28:42 Adding population labels from the panel file 33:33 To Colab! 36:54 PCA 40:17 First plot! Mission accomplished :) 42:03 Using Altair for plotting with labels 44:51 Second plot with population labels! 46:05 Merging with the igsr_population.tsv data 49:43 TSNE 53:36 Exercise: PCA on the SNPs 54:21 Conclusion and origin story for this project * Download a VCF of population genotypes from the 1000 Genomes project. * Use pysam to parse it and summarize it into a 2D numpy array to run PCA and save it as a pandas dataframe. * Run PCA and tSNE on it and visualize the results with both matplotlib and Altair, coloring the points based on the ancestry labels. Here is the project ideas videos where I mentioned this project first: https://www.youtube.com/watch?v=VoqbmLuw5Tw -- if you're interested in the origin story. All code including python script, download URLs for input files, and the Colab notebook: https://github.com/MariaNattestad/pca-on-genotypes