plotStratify: plotStratify

In GabrielHoffman/variancePartition: Quantify and interpret drivers of variation in multilevel gene expression experiments

plotStratify

Description

Plot gene expression stratified by another variable

Usage

plotStratify(
  formula,
  data,
  xlab,
  ylab,
  main,
  sortBy,
  colorBy,
  sort = TRUE,
  text = NULL,
  text.y = 1,
  text.size = 5,
  pts.cex = 1,
  ylim = NULL,
  legend = TRUE,
  x.labels = FALSE
)

Arguments

formula	specify variables shown in the x- and y-axes. Y-axis should be continuous variable, x-axis should be discrete.
data	data.frame storing continuous and discrete variables specified in formula
xlab	label x-asis. Defaults to value of xval
ylab	label y-asis. Defaults to value of yval
main	main label
sortBy	name of column in geneExpr to sort samples by. Defaults to xval
colorBy	name of column in geneExpr to color box plots. Defaults to xval
sort	if TRUE, sort boxplots by median value, else use default ordering
text	plot text on the top left of the plot
text.y	indicate position of the text on the y-axis as a fraction of the y-axis range
text.size	size of text
pts.cex	size of points
ylim	specify range of y-axis
legend	show legend
x.labels	show x axis labels

Value

ggplot2 object

Examples

# Note: This is a newer, more convient interface to plotStratifyBy()

# load library
# library(variancePartition)

# load simulated data:
data(varPartData)

# Create data.frame with expression and Tissue information for each sample
GE <- data.frame(Expression = geneExpr[1, ], Tissue = info$Tissue)

# Plot expression stratified by Tissue
plotStratify(Expression ~ Tissue, GE)

# Omit legend and color boxes grey
plotStratify(Expression ~ Tissue, GE, colorBy = NULL)

# Specify colors
col <- c(B = "green", A = "red", C = "yellow")
plotStratify(Expression ~ Tissue, GE, colorBy = col, sort = FALSE)

GabrielHoffman/variancePartition documentation built on April 20, 2024, 7:29 p.m.