| knnmi.cross {parmigene} | R Documentation |
Parallel Mutual Information Estimation Between the Rows of Two Matrices
Description
A function that estimates the mutual information between all pairs of
rows of matrices mat1 and mat2 using entropy estimates
from K-nearest neighbor distances.
Usage
knnmi.cross(mat1, mat2, k=3, noise=1e-12)
Arguments
mat1 |
a numeric matrix (for the reconstruction of gene regulatory networks, genes on rows and samples on columns). |
mat2 |
a numeric matrix with the same number of columns as |
k |
the number of nearest neighbors to consider to estimate the
mutual information. Must be less than the number of columns of |
noise |
the magnitude of the random noise added to break ties. |
Details
The function adds a small random noise to the data in order to break ties due to limited numerical precision.
By default, the function uses all the available cores. You can
set the actual number of threads used to N by exporting the
environment variable OMP_NUM_THREADS=N.
References
Kraskov, Alexander and Stogbauer, Harald and Grassberger, Peter. Estimating mutual information. Phys. Rev. E, 2004.
See Also
Examples
mat1 <- matrix(rnorm(1000), nrow=10)
mat2 <- matrix(rnorm(1000), nrow=10)
knnmi.cross(mat1, mat2, 5)