mapmixture (version 1.2.0)

scatter_plot: PCA or DAPC Scatter Plot

Description

Plot a scatter plot of PCA or DAPC results.

Usage

scatter_plot(
  dataframe,
  group_ids,
  other_group = NULL,
  type = "points",
  ...,
  labels = NULL,
  axes = c(1, 2),
  colours = NULL,
  centroids = TRUE,
  segments = TRUE,
  point_size = 3,
  point_type = 21,
  centroid_size = 3,
  hvline_type = "dotted",
  hvline_size = 0.5,
  hvline_colour = "black",
  xlab = "Axis",
  ylab = "Axis",
  percent = NULL,
  plot_title = ""
)

Value

A ggplot object.

Arguments

dataframe

data.frame or tibble containing results from a PCA or DAPC (see examples).

group_ids

character vector of IDs representing the group each row belongs to. This is used to colour the scatter plot and (optionally) add centroids and segments. E.g. a vector of site names, a vector of biological categories such as male or female, etc.

other_group

secondary character vector of IDs defining how to colour the scatter plot. E.g. a vector of country names (see examples). If NULL, scatter plot is coloured by group_ids.

type

string defining whether to show points ("points"), labels ("labels"), or text ("text").

...

additional arguments passed to ggplot2::geom_point when type = "points", or to ggplot2::geom_label when type = "labels", or to ggplot2::geom_text when type = "text".

labels

character vector of IDs defining labels when type = "label" or type = "text". If NULL, row names are used (integers from 1:nrow(dataframe)).

axes

integer vector of length two defining which axes to plot.

colours

character vector of colours the same length as the number of groups defined in group_ids or other_group.

centroids

add centroids to plot (TRUE or FALSE).

segments

add segments to plot (TRUE or FALSE).

point_size

numeric value for point size.

point_type

numeric value for point type (shape).

centroid_size

numeric value for centroid label size.

hvline_type

integer or string defining linetype (1 or "dotted"). Input 0 for no horizontal and vertical lines.

hvline_size

integer defining linewidth.

hvline_colour

string defining line colour.

xlab

string defining x axis label.

ylab

string defining y axis label.

percent

numeric vector the same length as ncol(dataframe) defining the percentage of variance explained by each axis.

plot_title

string defining the main title of the plot.

Examples

# Results from a Principal Components Analysis
file <- system.file("extdata", "pca_results.csv", package = "mapmixture")
pca_results <- read.csv(file)

# Define parameters
ind_names <- row.names(pca_results)
site_names <- rep(c("Pop1", "Pop2", "Pop3", "Pop4", "Pop5", "Pop6"), each = 100)
region_names <- rep(c("Region1", "Region2"), each = 300)
percent <- c(5.6, 4.5, 3.2, 2.0, 0.52)

# Scatter plot
scatter_plot(pca_results, site_names)

# Scatter plot with axes 1 and 3 and percent on axis labels
scatter_plot(pca_results, site_names, axes = c(1,3), percent = percent)

# Scatter plot with no centroids and segments
scatter_plot(pca_results, site_names, axes = c(1,2), percent = percent,
             centroids = FALSE, segments = FALSE)

# Scatter plot with custom colours and coloured by other_group
scatter_plot(pca_results, site_names, other_group = region_names,
             percent = percent, colours = c("#f1a340","#998ec3"))

# Scatter plot with individual labels
scatter_plot(pca_results, site_names, type = "labels",
             labels = rownames(pca_results))

# Scatter plot with individual text
scatter_plot(pca_results, site_names, type = "text",
             labels = rownames(pca_results))