GBIGM.test {GeneGeneInteR} | R Documentation |
GBIGM.test
performs a Gene-Gene Interaction (GGI) analysis by contrasting the information entropy between cases and controls.
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 DeltaR1,2. |
p.value |
The p-value for the test. |
estimate |
The estimation of DeltaR1,2. |
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.
data(gene.pair) GBIGM.test(Y=gene.pair$Y, G1=gene.pair$G1,G2=gene.pair$G2,n.perm=500)