Description Usage Arguments Value Examples

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

1 | ```
computeCorrelation(geneName, realExpr, imputedExpr)
``` |

`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() |

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
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)
}
``` |

AffiXcan documentation built on Nov. 8, 2020, 8:07 p.m.

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