Visualize BIOM data with boxplots.
taxa_boxplot(
biom,
x = NULL,
rank = -1,
layers = "x",
taxa = 6,
unc = "singly",
other = FALSE,
p.top = Inf,
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,
transform = "none",
y.transform = "sqrt",
caption = TRUE,
...
)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.
An rbiom object, such as from as_rbiom().
Any value accepted by as_rbiom() can also be given here.
A categorical metadata column name to use for the x-axis. Or
NULL, which puts taxa along the x-axis. Default: NULL
What rank(s) of taxa to display. E.g. "Phylum",
"Genus", ".otu", etc. An integer vector can also be
given, where 1 is the highest rank, 2 is the second
highest, -1 is the lowest rank, -2 is the second
lowest, and 0 is the OTU "rank". Run biom$ranks to
see all options for a given rbiom object. Default: -1.
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"
Which taxa to display. An integer value will show the top n
most abundant taxa. A value 0 <= n < 1 will show any taxa with that
mean abundance or greater (e.g. 0.1 implies >= 10%). A
character vector of taxa names will show only those named taxa.
Default: 6.
How to handle unclassified, uncultured, and similarly ambiguous taxa names. Options are:
"singly" - Replaces them with the OTU name.
"grouped" - Replaces them with a higher rank's name.
"drop" - Excludes them from the result.
"asis" - To not check/modify any taxa names.
Abbreviations are allowed. Default: "singly"
Sum all non-itemized taxa into an "Other" taxa. When
FALSE, only returns taxa matched by the taxa
argument. Specifying TRUE adds "Other" to the returned set.
A string can also be given to imply TRUE, but with that
value as the name to use instead of "Other".
Default: FALSE
Only display taxa with the most significant differences in
abundance. If p.top is >= 1, then the p.top most
significant taxa are displayed. If p.top is less than one, all
taxa with an adjusted p-value <= p.top are displayed.
Recommended to be used in combination with the taxa parameter
to set a lower bound on the mean abundance of considered taxa.
Default: Inf
Dataset field with the statistical groups. Must be
categorical. Default: NULL
Dataset field(s) to use for faceting. Must be categorical.
Default: NULL
How to color the groups. Options are:
TRUE - Automatically select colorblind-friendly colors.
FALSE or NULL - Don't use colors.
Auto-select colors from this set. E.g. "okabe"
Custom colors to use. E.g. c("red", "#00FF00")
Explicit mapping. E.g. c(Male = "blue", Female = "red")
See "Aesthetics" section below for additional information.
Default: TRUE
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 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
Transpose the axes, so that taxa are present as rows instead
of columns. Default: FALSE
Shade every other x position. Default: same as flip
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"
The confidence level for calculating a confidence interval.
Default: 0.95
Method to use for multiple comparisons adjustment of
p-values. Run p.adjust.methods for a list of available
options. Default: "fdr"
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
Angle of the labels at the bottom of the plot.
Options are "auto", '0', '30', and '90'.
Default: "auto".
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
Transformation to apply. Options are:
c("none", "rank", "log", "log1p", "sqrt", "percent"). "rank" is
useful for correcting for non-normally distributions before applying
regression statistics. Default: "none"
The transformation to apply to the y-axis. Visualizing differences of both high- and low-abundance taxa is best done with a non-linear axis. Options are:
"sqrt" - square-root transformation
"log1p" - log(y + 1) transformation
"none" - no transformation
These methods allow visualization of both high- and low-abundance
taxa simultaneously, without complaint about 'zero' count
observations. Default: "sqrt"
Use xaxis.transform or yaxis.transform to pass custom values
directly to ggplot2's scale_* functions.
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.
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.
Other taxa_abundance:
sample_sums(),
taxa_clusters(),
taxa_corrplot(),
taxa_heatmap(),
taxa_stacked(),
taxa_stats(),
taxa_sums(),
taxa_table()
Other visualization:
adiv_boxplot(),
adiv_corrplot(),
bdiv_boxplot(),
bdiv_corrplot(),
bdiv_heatmap(),
bdiv_ord_plot(),
plot_heatmap(),
rare_corrplot(),
rare_multiplot(),
rare_stacked(),
stats_boxplot(),
stats_corrplot(),
taxa_corrplot(),
taxa_heatmap(),
taxa_stacked()
library(rbiom)
biom <- rarefy(hmp50)
taxa_boxplot(biom, stat.by = "Body Site", stripe = TRUE)
taxa_boxplot(biom, layers = "bed", rank = c("Phylum", "Genus"), flip = TRUE)
taxa_boxplot(
biom = subset(biom, `Body Site` %in% c('Saliva', 'Stool')),
taxa = 3,
layers = "ps",
stat.by = "Body Site",
colors = c('Saliva' = "blue", 'Stool' = "red") )
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