| scoring.boot.parallel {iDINGO} | R Documentation |
Calculating differential score with parallel bootstrap scoring
Description
This function calculates standard errors for edge-wise partial correlation differences obtained from DINGO model. Bootstrapping is done in parallel using parSapply from the "parallel" library.
Usage
scoring.boot.parallel(stddat,z,Omega,A,B,boot.B=100,verbose=T,cores=1)
Arguments
stddat |
standardized nxp data with colnames as genename |
z |
a length n vector representing a binary covariate |
Omega |
a p x p precision matrix for std dat which implies the global network |
A |
p x p matrix of the MLE for the baseline covariance matrix which is obtained from A value of the Greg.em function. |
B |
p x 2 matrix of the MLE for the regression coefficient which is obtained from B value of the Greg.em function |
boot.B |
a scalar indicating the number of bootstraps |
verbose |
if TRUE, lists the bootstrap replications |
cores |
the number of cores to run in parallel for bootstrapping, set to 1 as a default. |
Value
genepair |
a p(p-1)/2 x 2 matrix indicating all pairs of genes |
levels.z |
a length 2 vector indicating levels of the binary covariate z, the first element is for group 1 and the second element is for group 2 |
R1 |
a length p(p-1)/2 vector indicating partial correlations for group 1 and the order is corresponding to the order of genepair |
R2 |
a length p(p-1)/2 vector indicating partial correlations for group 2 and the order is corresponding to the order of genepair |
boot.diff |
a p(p-1)/2 x boot.B matrix indicating bootstrapped difference, Fisher's Z transformed R1 - R2. The rows are corresponding to the order of gene pair and the columns are corresponding to the bootstrap samples |
diff.score |
a p(p-1)/2 vector of differential score corresponding to genepair |
p.val |
a p(p-1)/2 vector of corrected p-values corresponding to genepair |
Author(s)
Min Jin HA mjha@mdanderson.org, Caleb CLASS caclass@mdanderson.org