plot_score: Plot a Summary Line Plot or Heatmap from an Integrated Data...
In chenyenchung/genofeatutil: Utilities for genomic feature manipulation

Description Usage Arguments Value Examples

plot_score() takes a summary data frame (presumably generated by integrate_score()), and plot a line plot or heatmap to visualize the change of scores in different experiments.

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plot_score(x, facet = NULL, exp.order = NULL, cols.use = NULL,
  predictors.use = NULL, targets.use = NULL, plot.type = "line",
  title = NULL, k.groups = NULL)

`x`	a data frame, presumably generated by `integrate_score()`
`facet`	a character string. Options are "predictor" and "target". If set, the line plot will be separated into multiple panel according to the value of predictor or target
`exp.order`	a character vector containing the column names provided to `plot_score()`, indicating the order of them
`cols.use`	a character vector containing 3 colors to indicate the color used in a heatmap to represent low, mid, and high value respectively
`predictors.use`	a character vector indicating the predictors to plot
`targets.use`	a character vector indicating the predictors to plot
`plot.type`	a character string indicating whether a lineplot (`"line"`), a heatmap (`"heatmap"`), or a hierarchy tree (`"tree"`)should be generated
`title`	a character string indicating the title of the plot
`k.groups`	a numeric value indicating the number of clusters to form in hierarchical clustering for the predictor-target pairs

a ggplot2 object

# Generating a dummy data frame containing predictor, target, and columns of
# scores
intedf <- data.frame(
  "predictor" = c("tf_1", "tf_2", "tf_3", "tf_4"),
  "target" = c("gene_1", "gene_2", "gene_1", "gene_2"),
  "t1" = c(0, 5, 1, 5),
  "t2" = c(0, 3, 0, 1),
  "t3" = c(0, 6, 2, 6),
  "t4" = c(2, 7, 8, 9),
  "t5" = c(9, 2, 2, 7),
  stringsAsFactors = FALSE
)

# Plot a line plot
plot_score(x = intedf, plot.type = "line")

# Plot a heatmap
plot_score(x = intedf, plot.type = "heatmap")