R_ldsc | R Documentation |
Calculate matrix of error correlations using LD-score regression.
R_ldsc(
Z_hat,
ldscores,
ld_size,
N,
return_gencov = FALSE,
make_well_conditioned = TRUE,
cond_num = 1e+05 - 1,
blocks = NULL,
ncores = 1
)
Z_hat |
matrix of z-scores |
ldscores |
vector of ldscores |
ld_size |
Number of variants used to compute ldscores |
N |
vector of sample sizes, length equal to number of columns of Z_hat |
return_gencov |
If TRUE, the function will return genetic covariance in addition to residual covariance/correlation. |
make_well_conditioned |
If TRUE, residual covariance will be projected to the nearest positive definite matrix with condition number at least cond_num |
cond_num |
Condition number used if make_well_conditioned = TRUE |
blocks |
If not NULL, use jackknife to estimate the standard error of estimates. |
ncores |
Number of cores to use for jackknifing |
A list with some or all of the following elements. Se: Estimate of residual covariance Ve: Variance of Se. Sg: genetic covariance Vg: Variance fo Sg. Rg: Genetic correlation, VRg: Variance of Rg.
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