cor_heatmap: Create correlation heatmaps of taxa and another continuous...

In CharlieCarpenter/tidy.micro: A Pipeline For Microbiome Analysis And Visualization

Description

Calculated the correlation between a specified continuous variable and some taxa measure. Correlation type and taxa measure (count, relative abundance, etc.) can be specified by the user but is "spearman" and relative abundance, respectively, by default

Usage

cor_heatmap(
  micro_set,
  table,
  ...,
  y = clr,
  low_grad,
  high_grad,
  method = "spearman",
  main = NULL,
  xlab = NULL,
  ylab = NULL,
  subtitle = NULL,
  legend_title = "Correlation"
)

Arguments

micro_set	A tidy_micro data set
table	The OTU table
...	Continuous variables of interest
y	The taxa information: cts, ra, etc. The centered log ratio (clr) is recommended.
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
method	Correlation type; must be supported by cor. By default it is "spearman" to use with clr. If you'd like to use taxa ra, it is recommend you switch to Kendall's correlation to account for the large number of ties common in taxa ra (lots of 0s)
main	Plot title
xlab	x-axis label
ylab	y-axis label
subtitle	Plot label
legend_title	Title for the legend

Details

The output will give gray columns if there are missing values in the supplied continuous variable

Value

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

Examples

data(phy); data(cla); data(ord); data(fam); data(met)
otu_tabs = list(Phylum = phy, Class = cla, Order = ord, Family = fam)
set <- tidy_micro(otu_tabs = otu_tabs, meta = met) %>%
filter(day == 7) ## Only including the first week

set %>% cor_heatmap(table = "Family", gestational_age, weight)

CharlieCarpenter/tidy.micro documentation built on Jan. 19, 2020, 6:28 p.m.