AMOVA.jl

PopGen.jl/src/AMOVA.jl

📦 not exported	🔵 exported by PopGen.jl

📦 allelicdistance

allelicdistance(x, y)

📦 _missinglocusfilter

_missinglocusfilter(data::PopData, cutoff::Float64)

🔵 AMOVA

AMOVA(data::PopData; kwargs...) = amova(data, kwargs...)

This function is needed for pairwisefst dispatch, so it doesn't use the full AMOVA calculation.

🔵 amova

amova(data::PopData; hierarchy::String, missing_cutoff::Union{Nothing,Float64} = 0.05)

Arguments

• data: A PopData object

Keyword Arguments

• hierarchy: A String of what metadata column has the grouping type you would like to use. This is likely the popultion column in sampleinfo, since heirarchical clustering is not yet supported. The heirarchy API is very likely to change once that feature is implemented.
• missing_cutoff: A threshold to use for filtering out missing data. The default is 0.05, meaning remove loci with greater than 5% missing data. It accepts nothing to indicate you want all data kept.

The result is of type AMOVAResult, which allows it to be nicely printed as a familiar AMOVA/ANOVA table. You can easily access the fields of the result using dot-indexing, e.g. result.SS. Note that sigma-squared uses fancy characters, which will require Julia's built-in ASCII character rendering: \sigma<tab>\^2<tab>, where <tab> is the tab key on your keyboard.

🔵 AMOVAResult

struct AMOVAResult
    source::Vector{String}
    df::Vector{Int}
    SS::Vector{Float64}
    MS::Vector{Float64}
    σ²::Vector{Float64}
    FST::Float64
end

🔵 show

Base.show(io::IO, result::AMOVAResult)

Borrowed heavily from StatsModels.jl to have consistent style with expected model outputs.