beta_heatmap: Create heatmaps of the supplied dissimilarity matrices

In tidyMicro: A Pipeline for Microbiome Analysis and Visualization

Description

Create heatmaps of the supplied dissimilarity matrices ordered by supplied grouping variables

Usage

beta_heatmap(
  beta_div,
  micro_set,
  ...,
  low_grad,
  high_grad,
  main = NULL,
  xlab = NULL,
  ylab = NULL,
  subtitle = NULL,
  natural_order = TRUE,
  legend_title = "Dissimilarity"
)

Arguments

beta_div	A dissimilarity matrix calculated by beta_div
micro_set	A tidy_micro data set
...	Variables for ordering
low_grad	Colors for the corelation magnitude. Will be fed into scale_fill_gradient
high_grad	Colors for the corelation magnitude. Will be fed into scale_fill_gradient
main	Plot title
xlab	x-axis label
ylab	y-axis label
subtitle	Plot label
natural_order	Keep order of axes in the conventional order for dissimilarity matrices
legend_title	Title for the legend

Value

Returns a ggplot that you can add geoms to if you'd like

Examples

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)

tidyMicro documentation built on Jan. 13, 2021, 6:18 a.m.