ADMIXTURE

This post is a short follow-up to the previous one on Estimating Ancestry Components Using ADMIXTURE. Here, we’ll explore supervised ADMIXTURE, a mode that allows you to explicitly define ancestral populations and infer the ancestry proportions of unassigned individuals based on those references. What Is a Supervised Run? In supervised mode, ADMIXTURE skips the component discovery step and instead uses user-defined groupings to represent ancestral components. The benefit: if you already have solid candidates for reference populations, you can use them to quickly infer ancestry proportions for target or admixed individuals. ...

In this post, I’ll demonstrate how to estimate ancestry proportions using one of the most widely used tools in population genetics: ADMIXTURE. ADMIXTURE is a model-based clustering algorithm that infers individual ancestries from multilocus SNP genotype datasets. Preparing the Dataset Download the appropriate ADMIXTURE binary and either place it in your dataset directory or make it globally accessible. For this run, I included a subset of West Asian populations along with a few adjacent populations (around 150 samples in total). Linkage Disequilibrium (LD) pruning was applied beforehand. If you’re unsure how to prune your dataset, refer to the previous post. ...