computeCorrelation {AffiXcan} | R Documentation

## Compute R and R^2 on a particular row of two SummarizedExperiment assays

### Description

Compute R and R^2 on a particular row of two SummarizedExperiment assays

### Usage

    computeCorrelation(geneName, realExpr, imputedExpr)

### Arguments

`geneName` | A string. The row name in realExpr and imputedExpr objects that identifies the vectors between which R and R^2 have to be computed
`realExpr` | A SummarizedExperiment object containing expression data
`imputedExpr` | The returning object of affiXcanImpute()

### Value

A list of two objects:

- rho: the pearson's correlation coefficient (R) between the real expression values and the imputed GReX for the cross-validation i on the expressed gene y, computed with cor()

- rho.sq: the coefficient of determination (R^2) between the real expression values and the imputed GReX for the cross-validation i on the expressed gene y, computed as pearson^2

- cor.test.p.val: the p-value of the cor.test() between the real expression values and the imputed GReX for the cross-validation i on the expressed gene y

### Examples

    if (interactive()) {
    trainingTbaPaths <- system.file("extdata","training.tba.toydata.rds",
    package="AffiXcan")

    data(exprMatrix)
    data(regionAssoc)
    data(trainingCovariates)

    assay <- "values"

    training <- affiXcanTrain(exprMatrix=exprMatrix, assay=assay,
    tbaPaths=trainingTbaPaths, regionAssoc=regionAssoc, cov=trainingCovariates,
    varExplained=80, scale=TRUE)

    imputedExpr <- affiXcanImpute(tbaPaths=trainingTbaPaths,
    affiXcanTraining=training, scale=TRUE)
    realExpr <- exprMatrix

    geneName <- "ENSG00000256377.1"
    imputedExpr <- SummarizedExperiment::assays(imputedExpr)$GReX
    realExpr <- SummarizedExperiment::assays(realExpr)[[assay]]

    correlation <- computeCorrelation(geneName, realExpr, imputedExpr)
    }

[Package AffiXcan version 1.4.0 Index]