Heatmap of correlations between metabolites

Usage

create_correlations_heatmap(
  dat,
  type = "completed",
  threshold = 0.3,
  metabolites_to_display = "all",
  interactive = TRUE
)

Arguments

dat: a raw_data object, the output of the read_data() function. The data have to be completed, for example using the complete_data() function.
type: default to completed, which creates a heatmap of correlations between the metabolites after imputation. If both, then correlations between the metabolites before and after imputation are shown.
threshold: a numeric value specifying the minimum absolute correlation to display (only metabolites specified in metabolites_to_display are taken into account).
metabolites_to_display: a vector of names or number of metabolites to display. If a number is provided, the first metabolites are selected. Defaults to all.
interactive: logical. If TRUE (default), a ggiraph interactive plot is returned; otherwise, a standard ggplot object is produced.

Examples

path <- get_example_data("small_biocrates_example.xls")
dat <- read_data(path)
dat <- complete_data(dat, "limit", "limit", "limit")
#> Completing 109 < LOD values...
#> Completing 6 < LLOQ values...
#> Completing 9 < ULOQ values...
print(create_correlations_heatmap(dat))
print(create_correlations_heatmap(dat, type = "both"))
#> Warning: There were 8 warnings in `mutate()`.
#> The first warning was:
#> ℹ In argument: `across(everything(), suppressWarnings(as.numeric))`.
#> Caused by warning:
#> ! NAs introduced by coercion
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 7 remaining warnings.