construct_covmat_multi {LTFHPlus} | R Documentation |
Constructing a covariance matrix for multiple phenotypes
Description
construct_covmat_multi
returns the covariance matrix for an
underlying target individual and a variable number of its family members
for multiple phenotypes.
Usage
construct_covmat_multi(
fam_vec = c("m", "f", "s1", "mgm", "mgf", "pgm", "pgf"),
n_fam = NULL,
add_ind = TRUE,
genetic_corrmat,
full_corrmat,
h2_vec,
phen_names = NULL
)
Arguments
fam_vec |
A vector of strings holding the different family members. All family members must be represented by strings from the following list:
|
n_fam |
A named vector holding the desired number of family members.
See |
add_ind |
A logical scalar indicating whether the genetic component of the full liability as well as the full liability for the underlying individual should be included in the covariance matrix. Defaults to TRUE. |
genetic_corrmat |
A numeric matrix holding the genetic correlations between the desired phenotypes. All diagonal entries must be equal to one, while all off-diagonal entries must be between -1 and 1. In addition, the matrix must be symmetric. |
full_corrmat |
A numeric matrix holding the full correlations between the desired phenotypes. All diagonal entries must be equal to one, while all off-diagonal entries must be between -1 and 1. In addition, the matrix must be symmetric. |
h2_vec |
A numeric vector representing the liability-scale heritabilities for all phenotypes. All entries in h2_vec must be non-negative and at most 1. |
phen_names |
A character vector holding the phenotype names. These names will be used to create the row and column names for the covariance matrix. If it is not specified, the names will default to phenotype1, phenotype2, etc. Defaults to NULL. |
Details
This function can be used to construct a covariance matrix for
a given number of family members. Each entry in this covariance
matrix equals either the percentage of shared DNA between the corresponding
individuals times the liability-scale heritability h^2
or the
percentage of shared DNA between the corresponding individuals times
the correlation between the corresponding phenotypes.
That is, for the same phenotype, the covariance between all
combinations of the genetic component of the full liability
and the full liability is given by
\text{Cov}\left( l_g, l_g \right) = h^2,
\text{Cov}\left( l_g, l_o \right) = h^2,
\text{Cov}\left( l_o, l_g \right) = h^2
and
\text{Cov}\left( l_o, l_o \right) = 1.
For two different phenotypes, the covariance is given by
\text{Cov}\left( l_g^1, l_g^2 \right) = \rho_g^{1,2},
\text{Cov}\left( l_g^1, l_o^2 \right) = \rho_g^{1,2},
\text{Cov}\left( l_o^1, l_g^2 \right) = \rho_g^{1,2}
and
\text{Cov}\left( l_o^1, l_o^2 \right) = \rho_g^{1,2} + \rho_e^{1,2},
where l_g^i
and l_o^i
are the genetic component
of the full liability and the full liability for phenotype i
,
respectively, \rho_g^{i,j}
is the genetic correlation between
phenotype i
and j
and \rho_e^{1,2}
is the
environmental correlation between phenotype i
and j
.
The family members can be specified using one of two possible formats.
Value
If either fam_vec
or n_fam
is used as the argument and if it is of the
required format, if genetic_corrmat
and full_corrmat
are two numeric and symmetric matrices
satisfying that all diagonal entries are one and that all off-diagonal
entries are between -1 and 1, and if h2_vec
is a numeric vector satisfying
0 \leq h2_i \leq 1
for all i \in \{1,...,n_pheno\}
,
then the output will be a named covariance matrix.
The number of rows and columns corresponds to the number of phenotypes times
the length of fam_vec
or n_fam
(+ 2 if add_ind=TRUE
).
If both fam_vec
and n_fam
are equal to c()
or NULL
,
the function returns a (2 \times n_pheno) \times (2\times n_pheno)
matrix holding only the correlation between the genetic component of the full
liability and the full liability for the underlying individual for all
phenotypes. If both fam_vec
and n_fam
are specified, the user is asked to
decide on which of the two vectors to use.
Note that the returned object has a number different attributes,namely
fam_vec
, n_fam
, add_ind
, genetic_corrmat
, full_corrmat
,
h2
and phenotype_names
.
See Also
get_relatedness
, construct_covmat_single
and
construct_covmat
.
Examples
construct_covmat_multi(fam_vec = NULL,
genetic_corrmat = matrix(c(1, 0.5, 0.5, 1), nrow = 2),
full_corrmat = matrix(c(1, 0.55, 0.55, 1), nrow = 2),
h2_vec = c(0.37,0.44),
phen_names = c("p1","p2"))
construct_covmat_multi(fam_vec = c("m","mgm","mgf","mhs1","mhs2","mau1"),
n_fam = NULL,
add_ind = TRUE,
genetic_corrmat = diag(3),
full_corrmat = diag(3),
h2_vec = c(0.8, 0.65))
construct_covmat_multi(fam_vec = NULL,
n_fam = stats::setNames(c(1,1,1,2,2), c("m","mgm","mgf","s","mhs")),
add_ind = FALSE,
genetic_corrmat = diag(2),
full_corrmat = diag(2),
h2_vec = c(0.75,0.85))