cor_plot: Correlation Plot

In dunbarlabNIH/barcodetrackR: Functions for Analyzing Cellular Barcoding Data

Description

Plots the pairwise correlation between the specified assay of each sample-sample pair in the provided SummarizedExperiment.

Usage

cor_plot(
  your_SE,
  assay = "proportions",
  plot_labels = colnames(your_SE),
  method_corr = "pearson",
  your_title = "",
  grid = TRUE,
  label_size = 8,
  plot_type = "color",
  no_negatives = FALSE,
  return_table = FALSE,
  color_scale = "default",
  number_size = 3,
  point_scale = 1
)

Arguments

your_SE	A Summarized Experiment object.
assay	The choice of assay to use for the correlation calculation. Set to "proportions" by default.
plot_labels	Vector of x axis labels. Defaults to colnames(your_SE).
method_corr	Character. One of "pearson", "spearman", or "kendall".
your_title	Character. The title for the plot.
grid	Logical. Include a grid or not in the correlation plot
label_size	Numeric. The size of the column labels.
plot_type	Character. One of "color", "circle", or "number".
no_negatives	Logical. Whether to make negative correlations = 0.
return_table	Logical. Whether or not to return table of p-values, confidence intervals, and R values instead of displaying a plot.
color_scale	Character. Either "default" or an odd-numbered color scale where the lowest value will correspond to -1, the median value to 0, and the highest value to 1.
number_size	Numeric. Size of the text label when plot_type is "number".
point_scale	Numeric. The size of the largest point if the plot_type is "circle"

Value

Plots pairwise correlation plot for the samples in your_SE.

Examples

data(wu_subset)
cor_plot(your_SE = wu_subset, plot_type = "color")
# "

dunbarlabNIH/barcodetrackR documentation built on April 26, 2021, 6:20 p.m.