Violin plot of variance fractions
Violin plot of variance fraction for each gene and each variable
plotVarPart( obj, col = c(ggColorHue(ncol(obj) - 1), "grey85"), label.angle = 20, main = "", ylab = "", convertToPercent = TRUE, ... ) ## S4 method for signature 'matrix' plotVarPart( obj, col = c(ggColorHue(ncol(obj) - 1), "grey85"), label.angle = 20, main = "", ylab = "", convertToPercent = TRUE, ... ) ## S4 method for signature 'data.frame' plotVarPart( obj, col = c(ggColorHue(ncol(obj) - 1), "grey85"), label.angle = 20, main = "", ylab = "", convertToPercent = TRUE, ... ) ## S4 method for signature 'varPartResults' plotVarPart( obj, col = c(ggColorHue(ncol(obj) - 1), "grey85"), label.angle = 20, main = "", ylab = "", convertToPercent = TRUE, ... )
obj |
|
col |
vector of colors |
label.angle |
angle of labels on x-axis |
main |
title of plot |
ylab |
text on y-axis |
convertToPercent |
multiply fractions by 100 to convert to percent values |
... |
additional arguments |
Makes violin plots of variance components model. This function uses the graphics interface from ggplot2. Warnings produced by this function usually ggplot2 warning that the window is too small.
# load library # library(variancePartition) # Intialize parallel backend with 4 cores library(BiocParallel) register(SnowParam(4)) # load simulated data: # geneExpr: matrix of gene expression values # info: information/metadata about each sample data(varPartData) # Specify variables to consider # Age is continuous so we model it as a fixed effect # Individual and Tissue are both categorical, so we model them as random effects form <- ~ Age + (1|Individual) + (1|Tissue) varPart <- fitExtractVarPartModel( geneExpr, form, info ) # violin plot of contribution of each variable to total variance plotVarPart( sortCols( varPart ) )
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