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I am looking for a package similar to ggpubr to calculate and plot the statistic differences between some density plots. it would be great if it could work as a ggplot2 extension.

I've tried ggpubr but I think I should rearrange the data.frame quite a lot to make it work.

Does anyone have any suggestions?

This is an example for one of the plots I'd like to add some stats on top:

library(tidyverse)
library(plotly)
library(pheatmap)
library(RColorBrewer)
library(cowplot)
library(scales)
library(UpSetR)
library(magrittr)
library(multipanelfigure)
library(purrr)
library(igraph)
library(ggraph)
library(grid)
library(gtable)
library(gridExtra)
library(ComplexHeatmap)
library(ggridges)
library(ggplotify)
library(ggpubr)
library(ggpval)


mycols_values <- c("TG_baits" = "darkgrey",   # Colors are coming from RColorbrewer brewer.pal(11, "RdYlBu")
                   "TAL1" = '#d73027',
                   "Promoter_flanking_region" = '#f46d43',
                   "Promoter" = "#fdae61",
                   "Intron" = "#fee090",
                   "intergenic_region" = "#a1d99b",
                   "GATA2" = "#ffffbf",
                   "GATA1" = "#e0f3f8",
                   "FLI1" = "#abd9e9",
                   "Exons" = "#74add1",
                   "Enhancer" = "#4575b4",
                   "CTCF" = "#313695"
                   )

df_var <- structure(list(Promoter.id1 = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), Distance_bait_prey = c(120536, 
118081, 109646, 105159, 97202, 71739, 43239, 42450, 41350, 35391, 
30686, 22941, 2584, 1873, 4264, 10040, 10794, 18074, 32473, 44556, 
292007, 390016, 0, 0, 142512, 131396, 110989, 109562, 104713, 
95261, 86678, 69790, 55695, 35697, 2889, 3958, 38661, 43660, 
44783, 49321, 54148, 99101, 99977, 119272, 1484139, 409111, 386732, 
123910, 118993, 115927, 113762, 79247, 66060, 49530, 40555, 37697, 
30777, 9457, 22946, 36503, 67066, 77248, 205036, 317144, 0, 0, 
685454, 118907, 111509, 82273, 40797, 31511, 2699, 3438, 9215, 
17249, 0, 0, 213732, 94776, 0, 86753, 69263, 67025, 66564, 54178, 
51116, 50332, 43140, 41183, 40896, 34972, 24871, 23565, 10131, 
7517, 24279, 29130, 30790, 33482), node.class2 = c("Intron", 
"Intron", "Intron", "Intron", "Intron", "intergenic_region", 
"Promoter_flanking_region", "Promoter_flanking_region", "Exons", 
"Exons", "Exons", "intergenic_region", "Promoter_flanking_region", 
"Promoter_flanking_region", "Exons", "Promoter", "Promoter", 
"Promoter", "intergenic_region", "Intron", "intergenic_region", 
"Intron", "Intron", "Intron", "Exons", "Intron", "CTCF", "Intron", 
"Intron", "Intron", "Gene_name", "intergenic_region", "intergenic_region", 
"Exons", "Promoter_flanking_region", "Exons", "Promoter_flanking_region", 
"Promoter_flanking_region", "Intron", "Intron", "Exons", "Exons", 
"Intron", "intergenic_region", "Intron", "Enhancer", "Promoter", 
"Intron", "Intron", "Intron", "Intron", "Promoter", "Promoter_flanking_region", 
"Promoter_flanking_region", "Exons", "Exons", "Intron", "Promoter", 
"intergenic_region", "Exons", "Intron", "Exons", "CTCF", "Exons", 
"intergenic_region", "Exons", "Intron", "Intron", "CTCF", "Gene_name", 
"Exons", "Exons", "Promoter_flanking_region", "Exons", "Promoter", 
"Promoter", "Exons", "intergenic_region", "CTCF", "Promoter", 
"Intron", "CTCF", "Promoter", "Promoter", "Promoter", "CTCF", 
"CTCF", "CTCF", "Promoter_flanking_region", "Promoter", "Promoter", 
"Promoter", "CTCF", "CTCF", "Promoter_flanking_region", "Promoter", 
"CTCF", "Promoter", "Promoter", "Promoter")), row.names = c(NA, 
100L), class = "data.frame")

df_var$Distance_bait_prey <- str_replace_all(df_var$Distance_bait_prey, "^0","1000000000000")

ggplot(df_var, aes(x = log10(as.double(Distance_bait_prey)), 
                   y = node.class2, 
                   fill = node.class2), 
       alpha = 0.7) +
  geom_density_ridges(aes(point_color = node.class2),
                      scale = 2, 
                      alpha = 0.6,
                      panel_scaling = TRUE, 
                      #calc_ecdf = TRUE, 
                      #quantiles = c(0.025, 0.975),
                      jittered_points = TRUE,
                      position = position_points_sina(rel_min = 0.02, rel_max = 0.75, seed = NULL),
                      quantile_lines = TRUE,
                      point_size = 0.5,
                      point_alpha = 1) +
  scale_point_color_hue(l = 40, guide=FALSE) +
  scale_discrete_manual(aesthetics = "point_color", values = mycols_values, guide=FALSE) +
  scale_x_continuous(limits = c(2,7), 
                     name = "Distance Bait-prey [log10(bp)]", 
                     breaks = seq(2, 7, by = 1)) +
  labs(title = str_sub(name1, 1,-5),
       fill = "Distances grouped by Feature") +
  scale_fill_manual(values = mycols_values) +
  guides(fill = guide_legend(reverse = TRUE)) +
  theme_classic() +
  theme(plot.title = element_text(size = 54),
        axis.text.x = element_text(angle = 0, size = 16),
        axis.text.y = element_blank(),
        axis.title.y = element_blank(),
        axis.title.x = element_text(size = 0),
        axis.ticks.y = element_blank(),
        legend.title = element_text(size = 30),
        legend.text = element_text(size = 22),
        legend.position = "bottom" ,
        legend.key.size = unit(1, "cm"),
        panel.grid.major = element_line(colour = "grey90",
                                        linetype = "solid",
                                        size = 0.3)) 





sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggpval_0.2.2           ggpubr_0.2.2.999       usethis_1.5.0          devtools_2.0.2        
 [5] ggplotify_0.0.3        ggridges_0.5.1         ComplexHeatmap_1.20.0  gridExtra_2.3         
 [9] gtable_0.3.0           ggraph_1.0.2           igraph_1.2.4.1         multipanelfigure_2.0.2
[13] magrittr_1.5           UpSetR_1.4.0           scales_1.0.0           cowplot_1.0.0         
[17] RColorBrewer_1.1-2     pheatmap_1.0.12        plotly_4.9.0           forcats_0.4.0         
[21] stringr_1.4.0          dplyr_0.8.3            purrr_0.3.2            readr_1.3.1           
[25] tidyr_0.8.3            tibble_2.1.3           ggplot2_3.2.1          tidyverse_1.2.1       

loaded via a namespace (and not attached):
 [1] nlme_3.1-139               fs_1.3.1                   lubridate_1.7.4           
 [4] httr_1.4.0                 rprojroot_1.3-2            tools_3.5.1               
 [7] backports_1.1.4            utf8_1.1.4                 R6_2.4.0                  
[10] lazyeval_0.2.2             colorspace_1.4-1           GetoptLong_0.1.7          
[13] withr_2.1.2                tidyselect_0.2.5           prettyunits_1.0.2         
[16] processx_3.3.1             curl_3.3                   compiler_3.5.1            
[19] cli_1.1.0                  rvest_0.3.3                assertive.properties_0.0-4
[22] xml2_1.2.0                 desc_1.2.0                 labeling_0.3              
[25] assertive.files_0.0-2      callr_3.2.0                digest_0.6.20             
[28] assertive.numbers_0.0-2    pkgconfig_2.0.2            htmltools_0.3.6           
[31] sessioninfo_1.1.1          htmlwidgets_1.3            rlang_0.4.0               
[34] GlobalOptions_0.1.0        readxl_1.3.1               rstudioapi_0.10           
[37] shape_1.4.4                gridGraphics_0.4-1         farver_1.1.0              
[40] generics_0.0.2             jsonlite_1.6               fansi_0.4.0               
[43] Rcpp_1.0.2                 munsell_0.5.0              viridis_0.5.1             
[46] stringi_1.4.3              assertive.base_0.0-7       yaml_2.2.0                
[49] MASS_7.3-51.4              pkgbuild_1.0.3             plyr_1.8.4                
[52] ggrepel_0.8.1              crayon_1.3.4               lattice_0.20-38           
[55] haven_2.1.0                circlize_0.4.6             hms_0.4.2                 
[58] magick_2.0                 ps_1.3.0                   pillar_1.4.2              
[61] rjson_0.2.20               ggsignif_0.6.0             reshape2_1.4.3            
[64] codetools_0.2-16           pkgload_1.0.2              glue_1.3.1                
[67] remotes_2.0.4              data.table_1.12.2          modelr_0.1.4              
[70] tweenr_1.0.1               cellranger_1.1.0           polyclip_1.10-0           
[73] assertthat_0.2.1           ggforce_0.2.2              broom_0.5.2               
[76] assertive.types_0.0-3      viridisLite_0.3.0          rvcheck_0.1.3             
[79] memoise_1.1.0  
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