pcaPlot: Simple PCA analysis
In martingarrido/biokit: Toolkit for the automatic analysis of omics data
Description
Usage
Arguments
Value
View source: R/data_visualization.R
Description
Performs a principal component analysis of a
normalized expression/abundance matrix and plot the samples
in the bidimensional space formed by the two first principal
components. Samples are colored according to the variable of
interest in the sample information data frame.
Usage
1
pcaPlot(mat, sampInfo, groupCol)
Arguments
mat
The input matrix containing normalized data or counts
sampInfo
The sample information data frame
groupCol
The column name of the grouping variable
Value
A ggplot2 object containing the resulting plot
martingarrido/biokit documentation built on June 27, 2021, 2:21 a.m.
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Description Usage Arguments Value
View source: R/data_visualization.R
Description
Performs a principal component analysis of a normalized expression/abundance matrix and plot the samples in the bidimensional space formed by the two first principal components. Samples are colored according to the variable of interest in the sample information data frame.
Usage
1 | pcaPlot(mat, sampInfo, groupCol)
|
Arguments
mat |
The input matrix containing normalized data or counts |
sampInfo |
The sample information data frame |
groupCol |
The column name of the grouping variable |
Value
A ggplot2 object containing the resulting plot
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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