View source: R/plot_abund_prev.R
plot_abund_prev | R Documentation |
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, ... )
x |
|
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. |
Check if there are spurious OTUs/ASVs.
A ggplot
plot object.
## Not run: # 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 ## End(Not run)
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