get.eigentraits:
Calculate eigentraits from phenotype matrix
Description
This function performs the singular value decomposition (SVD) on the phenotype matrix after first removing individuals with missing data.
The eigentraits are the left singular vectors of the decomposition. This function optionally mean centers and normalizes the phenotype matrix before performing the SVD.
The object in which all results are stored. See read.population.
scale.pheno
A logical value specifying whether the phenotypes should be mean centered before the SVD is performed. The default, and recommended, value is TRUE.
normalize.pheno
A logical value specifying whether the phenotypes should be quantile normalized before the SVD is performed.
Value
This function adds three new elements to the data.obj list.
ET
The left singular vectors from the SVD. These are the eigentraits.
singular.values
The singular values from the SVD. These are used later internally to convert variant effects from eigentrait space to phenotype space.
right.singular.vectors
The right singular vectors from the SVD. These are used later internally to convert variant effects from eigentrait space to phenotype space.
References
Carter, G. W., Hays, M., Sherman, A., & Galitski, T. (2012). Use of pleiotropy to model genetic interactions in a population. PLoS genetics, 8(10), e1003010. doi:10.1371/journal.pgen.1003010