This function helps to format the cluster plots from degPatterns(). It allows to control the layers and it returns a ggplot object that can accept more ggplot functions to allow customization.

degPlotCluster(table, time, color = NULL, points = TRUE,
  boxes = TRUE, smooth = TRUE, lines = TRUE, facet = TRUE)

Arguments

table

normalized element from degPatterns() output.

time

column name to use in the x-axis.

color

column name to use to color and divide the samples.

points

Add points to the plot.

boxes

Add boxplot to the plot.

smooth

Add regression line to the plot.

lines

Add gene lines to the plot.

facet

Split figures based on cluster ID.

Value

ggplot2 object.

Examples

data(humanGender) library(SummarizedExperiment) library(ggplot2) ma <- assays(humanGender)[[1]][1:100,] des <- colData(humanGender) des[["other"]] <- sample(c("a", "b"), 85, replace = TRUE) res <- degPatterns(ma, des, time="group", col = "other", plot = FALSE)
#> Working with 100 genes.
#> Working with 72 genes after filtering: minc > 15
#> Joining, by = "merge"
#> Joining, by = "merge"
degPlotCluster(res$normalized, "group", "other")
degPlotCluster(res$normalized, "group", "other", lines = FALSE)