Description Usage Arguments Value Examples
Violin plot of variance fraction for each gene and each variable
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | 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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # 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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