Visualize how lineage definitions were used in analysis

Usage

plot_actual_defs(
  provoc_obj,
  type = "coverage",
  fun = mean,
  ...,
  main = NULL,
  col = hcl.colors(n = 21, palette = "Dark Mint", rev = TRUE)
)

Arguments

provoc_obj: The result of calling provoc.
type: "used" for the total number of times a mutation was used in the analysis and "coverage" for information about the coverage. Default "coverage".
fun: The function used to summarise coverage (when type = "coverage"). Default mean.
...: Further arguments passed on to fun
main: A main title for the plot.
col: Colours to be used in plotting. Default hcl.colors(n = 21, palette = "Dark Mint", rev = TRUE). Single-hue sequential colour palettes recommended.

Examples


data(Baaijens)
b2 <- Baaijens [Baaijens$sra %in% unique(Baaijens$sra)[1:30], ]
b2$mutations <- parse_mutations(b2$label)

lineage_defs <- astronomize() |>
    filter_lineages(c("B.1.617.1", "B.1.617.2", "B.1.617.2+K417N",
        "B.1.427", "B.1.429", "B.1.1.7"))
res <- provoc(
    formula = count / coverage ~ .,
    lineage_defs = lineage_defs,
    data = b2, 
    by = "sra",
    bootstrap_samples = 0)
#> Warning: first element used of 'length.out' argument
#> Warning: one-dimensional optimization by Nelder-Mead is unreliable:
#> use "Brent" or optimize() directly
#> Warning: one-dimensional optimization by Nelder-Mead is unreliable:
#> use "Brent" or optimize() directly
plot_actual_defs(res, type = "coverage", fun = max, na.rm = TRUE)