Description Usage Arguments Value Author(s) References See Also Examples

View source: R/entropyFunctions.r

A test evaluates the significance of the mutual information between two (high-dimensional) multivariate random variables. The null distribution is obtained via an efficient permutation resampling algorithm.

1 2 | ```
mutInfTest(Y, X, nPerm = 1000, method = "normal", k = 1, center = TRUE,
rescale = TRUE, lowCiThres=0.10, ncpus=1, verbose=FALSE)
``` |

`Y` |
(High-dimensional) matrix. Columns are assumed to represent the samples, and rows represent the samples' genes or traits. |

`X` |
(High-dimensional) matrix. Columns are assumed to represent the samples, and rows represent the samples' genes or traits. The number of columns of |

`nPerm` |
Number of permutations. |

`method` |
Distributional assumption under which mutual information is to be estimated. |

`k` |
k-nearest neighbor parameter. |

`center` |
Logical indicator: should the rows of |

`rescale` |
Logical indicator: should |

`lowCiThres` |
A value between 0 and 1. Determines speed of efficient p-value calculation.
If the probability of a p-value being below |

`ncpus` |
Number of cpus used for the permutations. |

`verbose` |
Logical indicator: should intermediate output be printed on the screen? |

Object of `miTest`

-class.

Wessel N. van Wieringen: [email protected]

Van Wieringen, W.N., Van der Vaart, A.W. (2011), "Statistical analysis of the cancer cell's molecular entropy using high-throughput data", *Bioinformatics*, 27(4), 556-563.

Van Wieringen, W.N., Van de Wiel, M.A., Van der Vaart, A.W. (2008), "A test for partial differential expression", *Journal of the American Statistical Association*, 103(483), 1039-1049.

1 2 3 4 5 6 7 8 9 | ```
# load data
data(pollackCN16)
data(pollackGE16)
Y <- t(exprs(pollackGE16))
X <- t(copynumber(pollackCN16))
# perform testing and print test results
testRes <- mutInfTest(Y, X, nPerm = 1000)
summary(testRes)
``` |

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