
Create heatmaps of the supplied dissimilarity matrices ordered by supplied grouping variables
beta_heatmap(
beta_div,
micro_set,
...,
low_grad,
high_grad,
main = NULL,
xlab = NULL,
ylab = NULL,
subtitle = NULL,
natural_order = TRUE,
legend_title = "Dissimilarity"
)
A dissimilarity matrix calculated by beta_div
A tidy_micro data set
Variables for ordering
Colors for the corelation magnitude. Will be fed into scale_fill_gradient
Colors for the corelation magnitude. Will be fed into scale_fill_gradient
Plot title
x-axis label
y-axis label
Plot label
Keep order of axes in the conventional order for dissimilarity matrices
Title for the legend
Returns a ggplot that you can add geoms to if you'd like
# NOT RUN {
data(bpd_phy); data(bpd_cla); data(bpd_ord); data(bpd_fam); data(bpd_clin)
otu_tabs <- list(Phylum = bpd_phy, Class = bpd_cla,
Order = bpd_ord, Family = bpd_fam)
set <- tidy_micro(otu_tabs = otu_tabs, clinical = bpd_clin) %>%
filter(day == 7) ## Only including the first week
## Bray-Curtis beta diversity
bray <- set %>% beta_div(table = "Family")
bray %>% beta_heatmap(micro_set = set, bpd1)
# }
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