hypercube {dkDNA} | R Documentation |
This function construct a diffusion kernel on a p
-dimensional
hypercube, where each genotype takes on two possible configurations.
This graph is obained by the
p
-Cartesian graph product of a complete graph K_2
.
It contains 2^p
vertices corresponding to sequences of
genotypes, and two vertices are adjacent if and only if just one SNP
locus differs.
hypercube(X, theta)
X |
A genotype matrix of |
theta |
The rate of diffusion. |
Diffusion kernel matrix of size n \times n
.
This can be viewed as a covariance among individuals given the
diffusion rate.
Gota Morota morota@unl.edu and Masanori Koyama koyama.masanori@gmail.com
Kondor R and Lafferty J: (2002) Diffusion Kernels on Graphs and Other Discrete Input Spaces. ICML.
Morota G, Koyama M, Rosa GJM, Weigel KA, and Gianola D. (2013). Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data. Genetics Selection Evolution. 45:17.
# set a seed
set.seed(4321)
# create a genotype matrix of 5 individuals with 10 bi-allelic genotypes
X <- matrix(sample(c(0,1), 50, prob=c(0.6,0.4), replace=TRUE), ncol=10)
# set the rate of diffusion equal to 1
theta <- 1
# compute a hypercube kernel
hypercube(X, theta)