Dot Plots Mimicking Violin Plots.

dotsViolin. Dot Plots Mimicking Violin Plots

Modifies dot plots to have different sizes of dots mimicking violin plots and identifies modes or peaks for them (Rosenblatt, 1956; Parzen, 1962).

dotsViolin, an R package (R Core Team, 2023) uses gridExtra (Auguie, 2017), gtools (Bolker et al., 2022), tidyr (Wickham et al., 2023c), stringr (Wickham, 2022), dplyr (Wickham et al., 2023b), ggplot2 (Wickham et al., 2023a), lazyeval (Wickham, 2019), magrittr (Bache and Wickham, 2022), rlang (Henry and Wickham, 2023), scales (Wickham and Seidel, 2022), tidyselect (Henry and Wickham, 2022)

Documentation was written with R-packages roxygen2 (Wickham et al., 2022), knitr (Xie, 2023), Rmarkdown (Allaire et al., 2023).

Academic presentation related (Roa-Ovalle, 2019)

Installation

devtools::install_gitlab(repo = "ferroao/dotsViolin")

Releases

News

Citation

To cite package ‘dotsViolin’ in publications use:

Roa-Ovalle F, Telles M (2023). dotsViolin: Integrated tables in dot and violin R ggplots. R package version 0.0.1, https://gitlab.com/ferroao/dotsViolin.

To write citation to file:

sink("dotsViolin.bib")
toBibtex(citation("dotsViolin"))
sink()

Authors

Fernando Roa
Mariana PC Telles

Plot window

Define your plotting window size with something like par(pin=c(10,6)), or with svg(), png(), etc.

In VSCode, you could use something like this

{
  "r.plot.useHttpgd": false,
  "r.plot.devArgs": {
    "width": 800,
    "height": 600
  }
}

Examples

1 Discrete Data:

library(dotsViolin)

fabaceae_mode_counts <- get_modes_counts(fabaceae_clade_n_df, "clade", "parsed_n")

fabaceae_mode_counts

library(dotsViolin)

fabaceae_clade_n_df_count <- make_legend_with_stats(fabaceae_mode_counts, "label_count", 1, TRUE)
fabaceae_clade_n_df$label_count <- fabaceae_clade_n_df_count$label_count[match(
  fabaceae_clade_n_df$clade,
  fabaceae_clade_n_df_count$clade
)]
desiredorder1 <- unique(fabaceae_clade_n_df$clade)

fabaceae_clade_n_df
                        tip.label          clade parsed_n
1     KX374504_Abarema_centiflora      Mimosoids       13
2   KX213142_Adenodolichos_bussei Papilionoideae       11
3      KX792912_Almaleea_cambagei Papilionoideae        8
4 KP109982_Amphithalea_cymbifolia Papilionoideae        9
5 KP230727_Argyrolobium_tuberosum Papilionoideae       13
6        GU220019_Ateleia_arsenii Papilionoideae       14
                              label_count
1 Mimosoids             13   26 14  (221)
2 Papilionoideae         8   11  7 (1410)
3 Papilionoideae         8   11  7 (1410)
4 Papilionoideae         8   11  7 (1410)
5 Papilionoideae         8   11  7 (1410)
6 Papilionoideae         8   11  7 (1410)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4,
  "ownwork",
  violin = FALSE
)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4,
  dots = FALSE
)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_n_df, "clade", "label_count", "parsed_n", 2,
  30, "Chromosome haploid number", desiredorder1, 1, .85, 4
)

2 Continuous Data:

Define your plotting window size with something like par(pin=c(10,6)), or with svg(), png(), etc.

library(dotsViolin)

fabaceae_Cx_peak_counts_per_clade_df <- get_peaks_counts_continuous(
  fabaceae_clade_1Cx_df,
  "clade", "Cx", 2, 0.25, 1, 2
)

fabaceae_Cx_peak_counts_per_clade_df

library(dotsViolin)

namecol <- "labelcountcustom"
fabaceae_clade_1Cx_modes_count_df <- make_legend_with_stats(
  fabaceae_Cx_peak_counts_per_clade_df,
  namecol, 1, TRUE
)
fabaceae_clade_1Cx_df$labelcountcustom <-
  fabaceae_clade_1Cx_modes_count_df$labelcountcustom[match(
    fabaceae_clade_1Cx_df$clade,
    fabaceae_clade_1Cx_modes_count_df$clade
  )]
desiredorder <- unique(fabaceae_clade_1Cx_df$clade)

fabaceae_clade_1Cx_df
                              name     clade     Cx      genus ownwork
6      'Silene_latifolia_JF715055' outgroups 2.7000     Silene      no
7  'Fagopyrum_esculentum_NC010776' outgroups 1.4350  Fagopyrum      no
11    'Helianthus_annuus_NC007977' outgroups 2.4250 Helianthus      no
12        'Daucus_carota_NC008325' outgroups 2.8375     Daucus      no
14        'Olea_europaea_NC013707' outgroups 1.9500       Olea      no
18       'Coffea_arabica_NC008535' outgroups 0.6000     Coffea      no
                                      labelcountcustom
6  outgroups                     0.48 1.38,2.76    (9)
7  outgroups                     0.48 1.38,2.76    (9)
11 outgroups                     0.48 1.38,2.76    (9)
12 outgroups                     0.48 1.38,2.76    (9)
14 outgroups                     0.48 1.38,2.76    (9)
18 outgroups                     0.48 1.38,2.76    (9)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  "ownwork"
)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  dots = FALSE
)

par(mar = c(0, 0, 0, 0), omi = rep(0, 4))

dots_and_violin(
  fabaceae_clade_1Cx_df, "clade", "labelcountcustom", "Cx", 3,
  3, "Genome Size", desiredorder, 0.03, 0.25, 2,
  "ownwork",
  violin = FALSE
)

References

R-packages

Academia