View source: R/one_pairscan_parallel.R
one_pairscan_parallel | R Documentation |
pairscan_kin
and pairscan_noKin
),
as well as to do the permutations of the pairscan
pairscan_null
).This is an internal function to run a single pairscan
It is used both to do the actual pairscan
(pairscan_kin
and pairscan_noKin
),
as well as to do the permutations of the pairscan
pairscan_null
).
one_pairscan_parallel(
data_obj,
phenotype_vector,
genotype_matrix,
int = NULL,
covar_vector = NULL,
paired_markers,
n_perm = 0,
run_parallel = FALSE,
verbose = FALSE,
n_cores = 4
)
data_obj |
a |
phenotype_vector |
A vector of trait values |
genotype_matrix |
A matrix of genotypes for markers to be tested |
int |
the interaction term added to the linear model
when the kinship correction is being used. This term is
calculated in |
covar_vector |
a vector or matrix of covariates to be used. |
paired_markers |
a two-column matrix indicating which
marker pairs should be tested. The pairs are assigned in
|
n_perm |
the number of permutations to be performed. |
run_parallel |
a logical value indicating whether to use parallel computing |
verbose |
a logical value indicating whether progress should be printed to the screen. |
n_cores |
the number of CPUs to use if run_parallel is TRUE. |
This function returns a list with two slots: pairscan_results and pairscan_perm Each of these elements is also a list containing effect sizes, standard errors, and covariance matrices for the pairwise tests.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.