get_diffnet_from_exp {snQTL} | R Documentation |
The differential matrix
Description
Given observations from two populations X and Y, compute the differential matrix
D = N(Y) - N(X)
where N() is the covariance matrix, or the weighted adjacency matrices defined as
N_{ij} = |corr(i, j)|^beta
for some constant beta > 0, 1 <= i, j <= p. Let N represent the regular correlation matrix when beta=0, and covariance matrix when beta<0.
Usage
get_diffnet_from_exp(X, Y, adj.beta = -1, trans = FALSE, location = NULL)
Arguments
X |
n1-by-p matrix for samples from the first population. Rows are samples/observations, while columns are the features. |
Y |
n2-by-p matrix for samples from the second population. Rows are samples/observations, while columns are the features. |
adj.beta |
Power to transform correlation matrices to weighted adjacency matrices
by |
trans |
logic variable, whether to only consider the trans-correlation (between genes from two different chromosomes or regions); see "details" |
location |
vector, the (chromosome) locations for items |
Value
The p-by-p differential matrix D = N(Y) - N(X)
.