design.score

model to be used for designing the matrix. The default is "additive" which can be extend to any ploidy level but alternative models for polyploids such as "additive","1-dom-alt","1-dom-ref","2-dom-alt","2-dom-ref" are supported based on Rosyara (2016)

model

A numeric value indicating the ploidy level of the organism. The default is 2 which means diploid but higher ploidy levels are supported.

ploidy

min.MAF

max.geno.freq

This function is a wrapper from the GWASpoly package that creates the incidence matrix to be used when calculating the -log10 scores for the markers once the variance components and marker effects are estimated.

Structural multivariate-univariate linear mixed model solver for multiple random effects allowing the specification of variance-covariance structures for random effects and allowing the fit of heterogeneous variance models (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>). ML/REML estimates can be obtained using the Direct-Inversion Newton-Raphson, and Efficient Mixed Model Association algorithms. Designed for genomic prediction and genome wide association studies (GWAS), particularly focused in the p > n problem (more coefficients than observations) to include multiple relationship matrices or other covariance structures. Spatial models can be fitted using the two-dimensional spline functionality in sommer.

design.score: design score for the model to be tested

Description

Usage

Arguments

Value

See Also

Examples