Plot expression data in a scatter plot

plot_scatter(
  data,
  smoothing_method = "lm",
  group_colors = RColorBrewer::brewer.pal(9, "Set1"),
  title_color = "black",
  title = NULL,
  col_title = NULL,
  row_title = NULL,
  legend_title = NULL,
  legend_position = "bottom",
  margins = "both",
  marginal_type = NULL,
  margins_size = 10,
  compute_correlation = TRUE,
  compute_correlation_method = "pearson",
  keep_aspect_ratio = TRUE,
  facet = FALSE,
  se = FALSE,
  pointdensity = TRUE
)

Arguments

data: Input data.
smoothing_method: Method for smoothing curve, lm or loess.
group_colors: Colors for different groups.
title_color: Color for the title.
title: Main title for the plot.
col_title: Title for the x-axis.
row_title: Title for the y-axis.
legend_title: Title for the legend.
legend_position: The position of legend.
margins: The position of marginal figure ("both", "x", "y").
marginal_type: The type of marginal figure (density, histogram, boxplot, violin, densigram).
margins_size: The size of marginal figure, note the bigger size the smaller figure.
compute_correlation: Whether to compute and print correlation on the figure.
compute_correlation_method: Method to compute correlation (pearson or spearman).
keep_aspect_ratio: Logical value, whether to set aspect ratio to 1:1.
facet: Faceting variable. If setting TRUE, all settings about margins will be inalidation.
se: Display confidence interval around smooth.
pointdensity: Plot point density when only provide 1 cluster.

Value

ggplot object

Examples

data("example_matrix")
test_data <- data.frame(
  example_matrix[1:200, c(1, 7)],
  c = c(
    rep("c1", 40),
    rep("c2", 40),
    rep("c3", 40),
    rep("c4", 40),
    rep("c5", 40)
  )
)

p1 <- plot_scatter(
  test_data
)
p2 <- plot_scatter(
  test_data,
  marginal_type = "boxplot"
)
p1 + p2


p3 <- plot_scatter(
  test_data,
  facet = TRUE
)
p3

p4 <- plot_scatter(
  test_data[, 1:2],
  marginal_type = "histogram"
)
p4