computeDrStat {RTopper} | R Documentation

## Computes gene-to-phenotype associations scores

### Description

`computeDrStat` Computes gene-to-phenotype associations scores, using as input the output from `convertToDr`.

### Usage

    computeDrStat(data, columns = c(1:(ncol(data)-1)), method = "dev", integrate = TRUE)

### Arguments

`data` | a list of data.frames containing genomic measurements. Each element of `dataIntersection` must account for the same set of patients(columns) and genes (rows)
`columns` | a data.frame indicating patients' phenotypic class
`method` | character, the number of genomic platforms
`integrate` | logical, wheter to integrate the gene-to-phenotype scores across platform or return separates scores for each platform

### Details

This function allows computing gene-to-phenotype association scores, using as input the gene-centered list produced by `computeDr`. The `computeDrStat` function works separately on each gene-centered data.frame created by the `convertToDr` function, assuming that the phenotype information is stored in the last column named `"response"`. It is possible computing both separate association scores for each platform, as well as an integrated score, as specified by the `integrate` arguments. There are currently three methods available for obtaining the scores (see Tyekucheva et al, manuscript under review), as specified by the `methods` argument:

`"dev"`: this approach computes the score as the difference of deviances;

`"aic"`: this approach computes the score as the Akaike information criterion for model selection;

`"bic"`: this approach computes the score as the penalized likelihood ratio;

### Value

A list of named vectors containing separate or integrared gene-to-phenotype association scores.

### Author(s)

Luigi Marchionni marchion@jhu.edu

### References

Svitlana Tyekucheva, Luigi Marchionni, Rachel Karchin, and Giovanni Parmigiani. "Integrating diverse genomic data using gene sets." Manuscript submitted.

### Examples

    ###load data
    data(exampleData)

    ###convert
    dataDr <- convertToDr(dat, pheno, 4)

    ###compute the integrated score
    bicStatIntegrated <- computeDrStat(dataDr, columns = c(1:4), method="bic", integrate = TRUE)

    ###compute separate scores for each genomic platform
    bicStatSeparate <- computeDrStat(dataDr, columns = c(1:4), method="bic", integrate = FALSE)

[Package RTopper version 1.40.1 Index]