scoring.boot: Calculating differential score
In berryni/mDINGO: DINGO: Differential Network Analysis in Genomics

This function calculates standard errors for edge-wise partial correlation differences obtained from DIGNO model.

1	scoring.boot(stddat,z,Omega,A,B,boot.B=100,verbose=T)

`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

`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