Population structure

In this notebook, we run a principal components analysis and build a neighbour joining tree on the amplicon sequencing variant data. For the PCA, we will plot PC1 v PC2 and PC3 v PC4, and the variance explained by the model.

Variance explained

The variance explained shows the proportion of total variance in the dataset that is captured by each principal component. Higher values indicate more informative components. As a general rule of thumb, when the variance explained for each PC begins to flatten out, that is when the PCs are no longer informative.

PCA

Principal Component Analysis (PCA) is a dimensionality reduction technique that transforms high-dimensional genetic data into a smaller set of uncorrelated variables (Reich et al., 2008). It helps visualize population structure and genetic relationships between samples.

NJT

Neighbor-Joining Tree (NJT) is a clustering method that reconstructs evolutionary relationships between samples based on genetic distances (Saitou & Nei, 1987). It creates a tree where genetically similar samples cluster together.

excluding extreme outliers from NJT []