gene.trait.pvalue {BUS} | R Documentation

## Calculate p-value for gene-trait interaction

### Description

To calculate p-value for null hypothesis that there is no interaction between gene and trait. There are MxT interactions between M genes and T traits. Results are given with 3 possibilities 1 for single p-value, and 3 for different types of correction. p-values are calculated based on the adjacency matrix for gene-gene interaction computed by function gene.trait.similarity.

### Usage

    gene.trait.pvalue(EXP, trait, measure, method.permut = 2, n.replica = 400)

### Arguments

`EXP` | Gene expression data in form of a matrix. Row stands for genes and column for experiments.
`trait` | Trait data in form of matrix. Row stands for traits and column for experiments.
`measure` | Metric used to calculate similarity: "corr" for correlation, "MI" for mutual information.
`method.permut` | A flag to indicate correction style when multiple hypotheses testing is considered. 1 for multiple traits correction, 2 for multiple genes and 3 for both genes and traits correction. The default value is 2.
`n.replica` | Number of permutations for the correction of multiple hypothesis testing; default value is 400.

### Details

According to a permutation method, we use the empirical distribution of some statistics to estimate the p-value. For single p-value the empirical distribution is a vector of P (number of random replicates for each test) test values. It is then possible to correct p-value in different ways: method.permut = 1, it is the empirical distribution of a vector with length of TxP, corrects for the multiple traits tested; method.permut = 2, it is the empirical distribution of a vector with length of MxP, corrects for the multiple genes tested; method.permut = 3, it is empirical distribution of a vector with length of MxTxP, corrects for the multiple traits and genes tested.

### Value

`single.perm.p.value` | A matrix of single p-values obtained with permutation method + beta distribution for extreme values (for MI) or obtained with the exact distribution computed directly by cor.test (for correlation)
`multi.perm.p.value` | A matrix of corrected p-values obtained with permutation method

### Author(s)

Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini

### See Also

`gene.trait.similarity`

### Examples

    data(tumors.mRNA)
    data(tumors.miRNA)
    exp<-tumors.mRNA
    trait<-tumors.miRNA
    gene.trait.pvalue(EXP=exp[1:10,],trait=trait[1:5,],measure="MI")

[Package BUS version 1.50.0 Index]