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PCA.jl

PopGen.jl/src/PCA.jl​

📦 not exported🔵 exported by PopGen.jl

🔵 pca​

pca(data::PopData; maxpc::Int = 0, method::Symbol = :svd, missings::String = "mean", pratio::Float64 = 0.99, center::Bool = false, scale::Bool = true)

Perform a Principal Component Analysis on a PopData object. Returns an indexible MultivariateStats.PCA object.

Arguments

  • data::PopData: a PopData object

Keyword Arguments

  • method::Symbol: The PCA method to use (default: :svd)
    • :cov: based on covariance matrix decomposition
    • :svd: based on Singular Value Decomposition of the input data
  • maxpc::Int: The maximum number of principal components to retain (default: 0 = (min(d, ncol-1)))
  • missings::String: How to treat missing genotypes in the allele frequency matrix (default: mean)
    • "mean": replace missing values with the mean frequency for that allele in that locus
    • "missing": keep missing values as they are
    • "zero": replace missing values with 0
  • pratio::Float64: The maxium ratio of variances preserved in the principal subspace (default = 0.99)
  • center::Bool: whether to center the allele frequency matrix (default: false)
  • scale::Bool: whether to Z-score scale the allele frequency matrix (default: true)