Generate Taxa Barplots for Longitudinal Data — generate_taxa_barplot

This function generates barplots to visualize the taxonomic composition of samples for longitudinal data. It also provides options for grouping and stratifying data.

Usage

generate_taxa_barplot_long(
  data.obj,
  subject.var,
  time.var,
  group.var = NULL,
  strata.var = NULL,
  feature.level = "original",
  feature.dat.type = c("count", "proportion", "other"),
  feature.number = 20,
  features.plot = NULL,
  t0.level = NULL,
  ts.levels = NULL,
  base.size = 10,
  theme.choice = "bw",
  custom.theme = NULL,
  palette = NULL,
  pdf = TRUE,
  file.ann = NULL,
  pdf.wid = 11,
  pdf.hei = 8.5,
  ...
)

Arguments

data.obj

A list object in a format specific to MicrobiomeStat, which can include components such as feature.tab (matrix), feature.ann (matrix), meta.dat (data.frame), tree, and feature.agg.list (list). The data.obj can be converted from other formats using several functions from the MicrobiomeStat package, including: 'mStat_convert_DGEList_to_data_obj', 'mStat_convert_DESeqDataSet_to_data_obj', 'mStat_convert_phyloseq_to_data_obj', 'mStat_convert_SummarizedExperiment_to_data_obj', 'mStat_import_qiime2_as_data_obj', 'mStat_import_mothur_as_data_obj', 'mStat_import_dada2_as_data_obj', and 'mStat_import_biom_as_data_obj'. Alternatively, users can construct their own data.obj. Note that not all components of data.obj may be required for all functions in the MicrobiomeStat package.

subject.var

Character string specifying the column name in metadata containing unique subject IDs. Required to connect samples from the same subject.

time.var

Character string specifying the column name in metadata containing the time variable. Required to order and connect samples over time.

group.var

Character string specifying the column name in metadata containing group identifiers. Default is NULL.

strata.var

Character string specifying the column name in metadata containing stratum identifiers. Default is NULL.

feature.level

The column name in the feature annotation matrix (feature.ann) of data.obj to use for summarization and plotting. This can be the taxonomic level like "Phylum", or any other annotation columns like "Genus" or "OTU_ID". Should be a character vector specifying one or more column names in feature.ann. Multiple columns can be provided, and data will be plotted separately for each column. Default is NULL, which defaults to all columns in feature.ann if `features.plot` is also NULL.

feature.dat.type

The type of the feature data, which determines how the data is handled in downstream analyses. Should be one of: - "count": Raw count data, will be normalized by the function. - "proportion": Data that has already been normalized to proportions/percentages. - "other": Custom abundance data that has unknown scaling. No normalization applied. The choice affects preprocessing steps as well as plot axis labels. Default is "count", which assumes raw OTU table input.

feature.number

A numeric value indicating the number of top abundant features to retain in the plot. Features with average relative abundance ranked below this number will be grouped into 'Other'. Default 20.

features.plot

A character vector specifying which feature IDs (e.g. OTU IDs) to plot. Default is NULL, in which case features will be selected based on `top.k.plot` and `top.k.func`.

t0.level

Character or numeric, baseline time point for longitudinal analysis, e.g. "week_0" or 0. Required.

ts.levels

Character vector, names of follow-up time points, e.g. c("week_4", "week_8"). Required.

base.size

A numeric value indicating the base font size for the plot.

theme.choice

Plot theme choice. Specifies the visual style of the plot. Can be one of the following pre-defined themes: - "prism": Utilizes the ggprism::theme_prism() function from the ggprism package, offering a polished and visually appealing style. - "classic": Applies theme_classic() from ggplot2, providing a clean and traditional look with minimal styling. - "gray": Uses theme_gray() from ggplot2, which offers a simple and modern look with a light gray background. - "bw": Employs theme_bw() from ggplot2, creating a classic black and white plot, ideal for formal publications and situations where color is best minimized. - "light": Implements theme_light() from ggplot2, featuring a light theme with subtle grey lines and axes, suitable for a fresh, modern look. - "dark": Uses theme_dark() from ggplot2, offering a dark background, ideal for presentations or situations where a high-contrast theme is desired. - "minimal": Applies theme_minimal() from ggplot2, providing a minimalist theme with the least amount of background annotations and colors. - "void": Employs theme_void() from ggplot2, creating a blank canvas with no axes, gridlines, or background, ideal for custom, creative plots. Each theme option adjusts various elements like background color, grid lines, and font styles to match the specified aesthetic. Default is "bw", offering a universally compatible black and white theme suitable for a wide range of applications.

custom.theme

A custom ggplot theme provided as a ggplot2 theme object. This allows users to override the default theme and provide their own theme for plotting. Custom themes are useful for creating publication-ready figures with specific formatting requirements.

To use a custom theme, create a theme object with ggplot2::theme(), including any desired customizations. Common customizations for publication-ready figures might include adjusting text size for readability, altering line sizes for clarity, and repositioning or formatting the legend. For example:

“`r my_theme <- ggplot2::theme( axis.title = ggplot2::element_text(size=14, face="bold"), # Bold axis titles with larger font axis.text = ggplot2::element_text(size=12), # Slightly larger axis text legend.position = "top", # Move legend to the top legend.background = ggplot2::element_rect(fill="lightgray"), # Light gray background for legend panel.background = ggplot2::element_rect(fill="white", colour="black"), # White panel background with black border panel.grid.major = ggplot2::element_line(colour = "grey90"), # Lighter color for major grid lines panel.grid.minor = ggplot2::element_blank(), # Remove minor grid lines plot.title = ggplot2::element_text(size=16, hjust=0.5) # Centered plot title with larger font ) “`

Then pass `my_theme` to `custom.theme`. If `custom.theme` is NULL (the default), the theme is determined by `theme.choice`. This flexibility allows for both easy theme selection for general use and detailed customization for specific presentation or publication needs.

palette

A character vector specifying the names of colors to use for the plot. The vector should contain color names that will be matched to the levels of the taxonomic grouping variable (feature.level). Default is NULL, which will use a pre-defined set of colors from the package ggh4x.

pdf

A logical value indicating whether to save the plot as a PDF. Default is TRUE.

file.ann

A string for additional annotation to the file name. Default is NULL.

pdf.wid

A numeric value specifying the width of the PDF file. Default is 11.

pdf.hei

A numeric value specifying the height of the PDF file. Default is 8.5.

...

Additional arguments to be passed to the function.

Value

A ggplot object of the taxa barplot.

Details

This function generates a barplot of taxa proportions for longitudinal data. The barplot can be stratified by a group variable and/or other variables. It also allows for different taxonomic levels to be used and a specific number of features to be included in the plot. The function also has options to customize the size, theme, and color palette of the plot, and to save the plot as a PDF.

Examples

if (FALSE) { # \dontrun{
library(ggh4x)
library(vegan)
data(ecam.obj)
generate_taxa_barplot_long(
  data.obj = ecam.obj,
  subject.var = "studyid",
  time.var = "month_num",
  group.var = "delivery",
  strata.var = "diet",
  feature.level = "Family",
  feature.dat.type = "proportion",
  feature.number = 30,
  t0.level = NULL,
  ts.levels = NULL,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  file.ann = NULL
)

generate_taxa_barplot_long(
  data.obj = ecam.obj,
  subject.var = "studyid",
  time.var = "month_num",
  group.var = "delivery",
  strata.var = "diet",
  feature.level = "Genus",
  feature.dat.type = "proportion",
  feature.number = 30,
  t0.level = NULL,
  ts.levels = NULL,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  file.ann = NULL
)

generate_taxa_barplot_long(
  data.obj = ecam.obj,
  subject.var = "studyid",
  time.var = "month_num",
  group.var = "delivery",
  strata.var = "diet",
  feature.level = "Genus",
  feature.dat.type = "proportion",
  features.plot = unique(ecam.obj$feature.ann[,"Genus"])[1:10],
  feature.number = 30,
  t0.level = NULL,
  ts.levels = NULL,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  file.ann = NULL
)

data(subset_T2D.obj)
generate_taxa_barplot_long(
  data.obj = subset_T2D.obj,
  subject.var = "subject_id",
  time.var = "visit_number_num",
  group.var = "subject_race",
  strata.var = "subject_gender",
  feature.level = c("Genus"),
  feature.dat.type = "count",
  feature.number = 40,
  t0.level = NULL,
  ts.levels = NULL,
  base.size = 10,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  pdf.wid = 49,
  file.ann = NULL
)

generate_taxa_barplot_long(
  data.obj = subset_T2D.obj,
  subject.var = "subject_id",
  time.var = "visit_number_num",
  group.var = "sample_body_site",
  strata.var = "subject_race",
  feature.level = c("Family"),
  feature.dat.type = "count",
  feature.number = 20,
  t0.level = NULL,
  ts.levels = NULL,
  base.size = 10,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  pdf.wid = 49,
  file.ann = NULL
)

generate_taxa_barplot_long(
  data.obj = subset_T2D.obj,
  subject.var = "subject_id",
  time.var = "visit_number_num",
  group.var = "subject_race",
  strata.var = "subject_gender",
  feature.level = c("Genus"),
  feature.dat.type = "count",
  features.plot = unique(subset_T2D.obj$feature.ann[,"Genus"][1:6]),
  feature.number = 40,
  t0.level = NULL,
  ts.levels = NULL,
  base.size = 10,
  theme.choice = "bw",
  palette = NULL,
  pdf = TRUE,
  pdf.wid = 49,
  file.ann = NULL
)
} # }