OmicFlow (version 1.5.0)

plot_pairwise_stats: Create pairwise stats plot

Description

Creates a pairwise stats plot from pairwise_adonis or pairwise_anosim results. This function is built into the class omics with method ordination() and inherited by other omics classes, such as; metagenomics and proteomics.

Usage

plot_pairwise_stats(
  data,
  stats_col,
  group_col,
  label_col,
  y_axis_title = NULL,
  plot_title = NULL
)

Value

A ggplot2 object to be further modified

Arguments

data

A data.frame or data.table.

stats_col

A column name of a continuous variable.

group_col

A column name of a categorical variable.

label_col

A column name of a categorical variable to label the bars.

y_axis_title

A character variable to name the Y - axis title (default: NULL).

plot_title

A character variable to name the plot title (default: NULL).

Examples

library("ggplot2")

# Create random data
set.seed(42)
mock_data <- matrix(rnorm(15 * 10), nrow = 15, ncol = 10)

# Create euclidean dissimilarity matrix
mock_dist <- dist(mock_data, method = "euclidean")

# Define group labels, should be equal to number of columns and rows to dist
mock_groups <- rep(c("A", "B", "C"), each = 5)

# Compute pairwise adonis
adonis_res <- pairwise_adonis(x = mock_dist, 
                              groups = mock_groups, 
                              p.adjust.method = "bonferroni", 
                              perm = 99)
# Compute pairwise anosim
anosim_res <- pairwise_anosim(x = mock_dist, 
                              groups = mock_groups, 
                              p.adjust.method = "bonferroni", 
                              perm = 99)

# Visualize PERMANOVA pairwise stats
plot_pairwise_stats(data = adonis_res,
                    group_col = "pairs",
                    stats_col = "F.Model",
                    label_col = "p.adj",
                    y_axis_title = "Pseudo F test statistic",
                    plot_title = "PERMANOVA")

# Visualize ANOSIM pairwise stats
plot_pairwise_stats(data = anosim_res,
                    group_col = "pairs",
                    stats_col = "anosimR",
                    label_col = "p.adj",
                    y_axis_title = "ANOSIM R statistic",
                    plot_title = "ANOSIM")