adiv_boxplot: Visualize alpha diversity with boxplots.

In cmmr/rbiom: Read/Write, Analyze, and Visualize 'BIOM' Data

Visualize alpha diversity with boxplots.

Description

Visualize alpha diversity with boxplots.

Usage

adiv_boxplot(
  biom,
  x = NULL,
  adiv = "Shannon",
  layers = "x",
  stat.by = x,
  facet.by = NULL,
  colors = TRUE,
  shapes = TRUE,
  patterns = FALSE,
  flip = FALSE,
  stripe = NULL,
  ci = "ci",
  level = 0.95,
  p.adj = "fdr",
  outliers = NULL,
  xlab.angle = "auto",
  p.label = 0.05,
  trans = "none",
  caption = TRUE,
  ...
)

Arguments

biom	An rbiom object, such as from as_rbiom(). Any value accepted by as_rbiom() can also be given here.
x	A categorical metadata column name to use for the x-axis. Or NULL, which groups all samples into a single category.
adiv	Alpha diversity metric(s) to use. Options are: "OTUs", "Shannon", "Chao1", "Simpson", and/or "InvSimpson". Set adiv=".all" to use all metrics. Default: "Shannon" Multiple/abbreviated values allowed.
layers	One or more of c("bar", "box" ("x"), "violin", "dot", "strip", "crossbar", "errorbar", "linerange", "pointrange"). Single letter abbreviations are also accepted. For instance, c("box", "dot") is equivalent to c("x", "d") and "xd". Default: "x"
stat.by	Dataset field with the statistical groups. Must be categorical. Default: NULL
facet.by	Dataset field(s) to use for faceting. Must be categorical. Default: NULL
colors	How to color the groups. Options are: TRUE - Automatically select colorblind-friendly colors. FALSE or NULL - Don't use colors. a palette name - Auto-select colors from this set. E.g. "okabe" character vector - Custom colors to use. E.g. c("red", "#00FF00") named character vector - Explicit mapping. E.g. c(Male = "blue", Female = "red") See "Aesthetics" section below for additional information. Default: TRUE
shapes	Shapes for each group. Options are similar to colors's: TRUE, FALSE, NULL, shape names (typically integers 0 - 17), or a named vector mapping groups to specific shape names. See "Aesthetics" section below for additional information. Default: TRUE
patterns	Patterns for each group. Options are similar to colors's: TRUE, FALSE, NULL, pattern names ("brick", "chevron", "fish", "grid", etc), or a named vector mapping groups to specific pattern names. See "Aesthetics" section below for additional information. Default: FALSE
flip	Transpose the axes, so that taxa are present as rows instead of columns. Default: FALSE
stripe	Shade every other x position. Default: same as flip
ci	How to calculate min/max of the crossbar, errorbar, linerange, and pointrange layers. Options are: "ci" (confidence interval), "range", "sd" (standard deviation), "se" (standard error), and "mad" (median absolute deviation). The center mark of crossbar and pointrange represents the mean, except for "mad" in which case it represents the median. Default: "ci"
level	The confidence level for calculating a confidence interval. Default: 0.95
p.adj	Method to use for multiple comparisons adjustment of p-values. Run p.adjust.methods for a list of available options. Default: "fdr"
outliers	Show boxplot outliers? TRUE to always show. FALSE to always hide. NULL to only hide them when overlaying a dot or strip chart. Default: NULL
xlab.angle	Angle of the labels at the bottom of the plot. Options are "auto", '0', '30', and '90'. Default: "auto".
p.label	Minimum adjusted p-value to display on the plot with a bracket. p.label = 0.05 - Show p-values that are <= 0.05. p.label = 0 - Don't show any p-values on the plot. p.label = 1 - Show all p-values on the plot. If a numeric vector with more than one value is provided, they will be used as breaks for asterisk notation. Default: 0.05
trans	Transformation to apply. Options are: c("none", "rank", "log", "log1p", "sqrt"). "rank" is useful for correcting for non-normally distributions before applying regression statistics. Default: "none"
caption	Add methodology caption beneath the plot. Default: TRUE
...	Additional parameters to pass along to ggplot2 functions. Prefix a parameter name with a layer name to pass it to only that layer. For instance, d.size = 2 ensures only the points on the dot layer have their size set to 2.

Value

A ggplot2 plot.
The computed data points, ggplot2 command, stats table, and stats table commands are available as ⁠$data⁠, ⁠$code⁠, ⁠$stats⁠, and ⁠$stats$code⁠, respectively.

Aesthetics

All built-in color palettes are colorblind-friendly. The available categorical palette names are: "okabe", "carto", "r4", "polychrome", "tol", "bright", "light", "muted", "vibrant", "tableau", "classic", "alphabet", "tableau20", "kelly", and "fishy".

Patterns are added using the fillpattern R package. Options are "brick", "chevron", "fish", "grid", "herringbone", "hexagon", "octagon", "rain", "saw", "shingle", "rshingle", "stripe", and "wave", optionally abbreviated and/or suffixed with modifiers. For example, "hex10_sm" for the hexagon pattern rotated 10 degrees and shrunk by 2x. See fillpattern::fill_pattern() for complete documentation of options.

Shapes can be given as per base R - numbers 0 through 17 for various shapes, or the decimal value of an ascii character, e.g. a-z = 65:90; A-Z = 97:122 to use letters instead of shapes on the plot. Character strings may used as well.

See Also

Other alpha_diversity: adiv_corrplot(), adiv_stats(), adiv_table()

Other visualization: adiv_corrplot(), bdiv_boxplot(), bdiv_corrplot(), bdiv_heatmap(), bdiv_ord_plot(), plot_heatmap(), rare_corrplot(), rare_multiplot(), rare_stacked(), stats_boxplot(), stats_corrplot(), taxa_boxplot(), taxa_corrplot(), taxa_heatmap(), taxa_stacked()

Examples

    library(rbiom)
    
    biom <- rarefy(hmp50)
    
    adiv_boxplot(biom, x="Body Site", stat.by="Body Site")
    
    adiv_boxplot(biom, x="Sex", stat.by="Body Site", adiv=c("otu", "shan"), layers = "bld")
    
    adiv_boxplot(biom, x="body", stat.by="sex", adiv=".all", flip=TRUE, layers="p")
    
    
    # Each plot object includes additional information.
    fig <- adiv_boxplot(biom, x="Body Site")
    
    ## Computed Data Points -------------------
    fig$data
    
    ## Statistics Table -----------------------
    fig$stats
    
    ## ggplot2 Command ------------------------
    fig$code
    

cmmr/rbiom documentation built on April 28, 2024, 6:38 a.m.