null_distri {hierBipartite} | R Documentation |
Null distribution of dissimilarity measures
Description
Generates null distribution of dissimilarity measures between group 1 (X1, Y1) and group 2 (X2, Y2).
Usage
null_distri(X1, Y1, X2, Y2, n.perm = 100, parallel = FALSE, maxCores = 7)
Arguments
X1 |
an n x p matrix of variable set 1 (e.g. gene expression) from group 1 |
Y1 |
an n x q matrix of variable set 2 (e.g. drug sensitivity) from group 1 |
X2 |
an n x p matrix of variable set 1 (e.g. gene expression) from group 2 |
Y2 |
an n x q matrix of varaible set 2 (e.g. drug sensitivity) from group 2 |
n.perm |
number of null dissimilarity measures to generate |
parallel |
boolean for whether to parallelize permutation |
maxCores |
maximum number of cores to use (only applicable when parallel = TRUE) |
Value
vector of length n.perm of null dissimilarity measures
Examples
# Get data for group squamous cell carcinoma, esophagus and for group
# squamous cell carcinoma, upper aerodigestive
data(ctrp2)
groups = ctrp2$groups
X = ctrp2$X
Y = ctrp2$Y
x1 = X[groups[["squamous_cell_carcinoma_esophagus"]], ]
y1 = Y[groups[["squamous_cell_carcinoma_esophagus"]], ]
x2 = X[groups[["squamous_cell_carcinoma_upper_aerodigestive"]], ]
y2 = Y[groups[["squamous_cell_carcinoma_upper_aerodigestive"]], ]
## Not run:
dissimilarities = null_distri(x1, y1, x2, y2, n.perm = 100)
## End(Not run)
[Package hierBipartite version 0.0.2 Index]