This function creates the gene plot.
Usage
getcountplot(
df,
intgroup = "group",
factor.levels,
title = NULL,
ylab = "Normalized counts",
color = "gene",
nrow = 2,
ymin = NULL,
ymax = NULL,
log = TRUE,
freey = FALSE,
trendline = "smooth",
facet = NULL,
legend = TRUE,
boxes = TRUE,
rotate_x_labels = 30
)Arguments
- df
data.frame with gene counts
- intgroup
metadata variable to plot on x-axis
- factor.levels
levels of intgroup to show on x-axis
- title
title of plot
- ylab
y-axis label
- color
metadata variable to color by
- nrow
number of rows to plot if faceting
- ymin
y-axis lower limit
- ymax
y-axis upper limit
- log
should y-axis be log10-transformed?
- freey
should y-axes of faceted plots have independent scales?
- trendline
type of trendline to draw
- facet
metadata variable to facet by
- legend
show legend?
- boxes
show boxes?
- rotate_x_labels
angle to rotate x-axis labels (default=30)
Examples
# make example DESeq dataset
dds <- DESeq2::makeExampleDESeqDataSet()
# get gene counts
df <- get_gene_counts(dds, gene = c('gene1', 'gene2'))
# standard gene plot
p <- getcountplot(df, intgroup = "condition", factor.levels = c("A", "B"))
# with genes faceted
p1 <- getcountplot(df, intgroup = "condition", factor.levels = c("A", "B"), facet = "gene")