WIP - Cladogram plot

[sdgamboa]

Opening a PR to work on the function for plotting the cladogram.

If internal nodes are of interest, some extra steps need to be taken. This is done
with the lefserAllRank function.

Related issues

• Discussion in issue variables are collinear #41.
• Visualization options #54 Request for adding visualization options.
• Provide option of colorblind-friendly palette #49 Provide palette options. Also PR Add .selectPalette function. #60.

suppressPackageStartupMessages(library(lefser))
data("zeller14")
z14 <- zeller14[, zeller14$study_condition != "adenoma"]
tn <- get_terminal_nodes(rownames(z14))
z14tn <- z14[tn, ]
z14tn_ra <- relativeAb(z14tn)

## Run lefser at all taxonomic levels and merge into a
## single result
resAll <- lefserAllRanks(relab = z14tn_ra, groupCol = "study_condition")
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> Warning in lefser(relab = x, ...): Convert counts to relative abundances with
#> 'relativeAb()'
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
#> The outcome variable is specified as 'study_condition' and the reference category is 'control'.
#>  See `?factor` or `?relevel` to change the reference category.
pp <- suppressWarnings(lefsePlotClad(x = resAll))
pp
#> Warning: Removed 457 rows containing missing values or values outside the scale range
#> (`geom_point_g_gtree()`).
#> Warning: Removed 549 rows containing missing values or values outside the scale range
#> (`geom_point_g_gtree()`).
#> Warning: Removed 1165 rows containing missing values or values outside the scale range
#> (`geom_label_repel()`).

^{Created on 2024-09-13 with reprex v2.1.1}

[shbrief]

Do we still need cladogramPlot.R?

[lwaldron]

I like it!

1. Is there any way to deal with the overlapping labels for publication? Maybe an option to only label internal nodes instead?
2. An option to choose other color palettes (including a color-blind option) would be great.