Mean Abundance-Prevalence relation — plot_abund

Plots Mean Abundance-Prevalence for taxa. Mean abundance, mean prevalence, and upper and lower confidence interval for each taxa is calculated by random subsampling.

plot_abund_prev(
  x,
  lower.conf = 0.025,
  upper.conf = 0.975,
  bs.iter = 99,
  color = "steelblue",
  dot.opacity = 0.5,
  dot.size = 2,
  label.core = FALSE,
  label.size = NULL,
  label.opacity = NULL,
  label.color = "grey70",
  mean.abund.thres = NULL,
  mean.prev.thres = NULL,
  log.scale = TRUE,
  nudge.label = NULL,
  ...
)

Arguments

x: phyloseq-class object
lower.conf: Lower confidence interval =0.025
upper.conf: Upper confidence interval =0.975
bs.iter: Number of bootstrap iterations =99
color: taxa level to color. Preferably at phylum or just a single color
dot.opacity: Numeric for ggplot alpha. Default is 0.5
dot.size: Numeric size of point
label.core: Logical default is FALSE
label.size: If label_core is TRUE specify text size. Default is NULL
label.opacity: Numeric for ggplot alpha. Defualt is NULL
label.color: Color for labels. Default="grey70"
mean.abund.thres: If label_core is TRUE specify mean abundance threshold. Default is NULL
mean.prev.thres: If label_core is TRUE specify mean prevalence threshold. Default is NULL
log.scale: Plot log10 scale. Default is TRUE abundance criteria. Default is NULL
nudge.label: Argument to pass to ggrepel::geom_text_repel Default is NULL
...: Arguments to pass to sample() function.

Value

A ggplot plot object.

Details

Check if there are spurious OTUs/ASVs.

Examples

if (FALSE) {
# Example data
library(microbiomeutilities)
asv_ps <- zackular2014
asv_ps <- microbiome::transform(asv_ps, "compositional")
asv_ps <- core(asv_ps, detection = 0.0001, prevalence = 0.5)
asv_ps <- format_to_besthit(asv_ps)
set.seed(2349)
p_v <- plot_abund_prev(asv_ps, size = 20, replace = TRUE) +
  geom_vline(xintercept = 0.75, lty = "dashed", alpha = 0.7) +
  geom_hline(yintercept = 0.01, lty = "dashed", alpha = 0.7) +
  scale_color_brewer(palette = "Paired")
p_v
}