Description Usage Arguments Details Value References See Also Examples

`GBIGM.test`

performs a Gene-Gene Interaction (GGI) analysis by contrasting the information entropy between cases and controls.

1 | ```
GBIGM.test(Y, G1, G2, n.perm = 1000)
``` |

`Y` |
numeric or factor vector with exactly two different values. |

`G1` |
SnpMatrix object.
Must have a number of rows equal to the length of |

`G2` |
SnpMatrix object.
Must have a number of rows equal to the length of |

`n.perm` |
positive integer. |

First, the conditional entropy and information gain rate are computed for each gene `G1`

and `G2`

. In a second step, information gain rate for the gene pair (`G1`

,`G2`

) is computed. A p-value is estimated using permutations of `Y`

. More details can be found in Li et al. (2015).

A list with class `"htest"`

containing the following components:

`statistic` |
The value of the statistic |

`p.value` |
The p-value for the test. |

`estimate` |
The estimation of |

`parameter` |
The number of permutations used to estimate the p-value. |

`alternative` |
a character string describing the alternative. |

`method` |
a character string indicating the method used. |

`data.name` |
a character string giving the names of the data. |

J. Li, et al.. A gene-based information gain method for detecting gene-gene interactions in case-control studies. European Journal of Human Genetics, 23 :1566-1572, 2015.

1 2 |

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