R: Parallel Mutual Information Estimation Between the Rows of...

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 `mat1`.
`k` | the number of nearest neighbors to consider to estimate the mutual information. Must be less than the number of columns of `mat1`.
`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

`knnmi`

`knnmi.all`

### Examples

    mat1 <- matrix(rnorm(1000), nrow=10)
    mat2 <- matrix(rnorm(1000), nrow=10)
    knnmi.cross(mat1, mat2, 5)

[Package parmigene version 1.0.2 Index]