computeQuantileMatrix: Compute quantile transformations
In divergence: Divergence: Functionality for assessing omics data by divergence with respect to a baseline
Description
Usage
Arguments
Value
Examples
Description
Function for computing the quantile transformation for one or more samples
supplied as columns of a matrix.
Usage
1
computeQuantileMatrix(seMat)
Arguments
seMat
A data matrix in SummarizedExperiment form, with each column corresponding to a sample and each row
corresponding to a feature.
Value
A matrix of the same dimensions with the quantile data.
Examples
1
2
3
baseMat = breastTCGA_Mat[, breastTCGA_Group == "NORMAL"]
seMat.base = SummarizedExperiment(assays=list(data=baseMat))
assays(seMat.base)$quantile = computeQuantileMatrix(seMat.base)
divergence documentation built on Nov. 8, 2020, 8:02 p.m.
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Description Usage Arguments Value Examples
Description
Function for computing the quantile transformation for one or more samples supplied as columns of a matrix.
Usage
1 | computeQuantileMatrix(seMat)
|
Arguments
seMat |
A data matrix in SummarizedExperiment form, with each column corresponding to a sample and each row corresponding to a feature. |
Value
A matrix of the same dimensions with the quantile data.
Examples
1 2 3 | baseMat = breastTCGA_Mat[, breastTCGA_Group == "NORMAL"]
seMat.base = SummarizedExperiment(assays=list(data=baseMat))
assays(seMat.base)$quantile = computeQuantileMatrix(seMat.base)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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