Last updated: 2024-06-20

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Knit directory: LocksofLineage/

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File Version Author Date Message
Rmd 24ecbbf Sarah E Taylor 2024-06-17 Added code to save the formatted dataframes.
html 768856f Sarah E Taylor 2024-03-17 Build site.
Rmd 3818f0b Sarah E Taylor 2024-03-17 Analysis for the poster.

Set up

library(tidyverse)
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(janitor)

Attaching package: 'janitor'

The following objects are masked from 'package:stats':

    chisq.test, fisher.test
library(ape)

Attaching package: 'ape'

The following object is masked from 'package:dplyr':

    where
library(phytools)
Loading required package: maps

Attaching package: 'maps'

The following object is masked from 'package:purrr':

    map
#Library for upset plot
library(ComplexUpset)
library(eulerr)
#Map the families onto the superfamilies
superfamily_mapping <- data.frame(
  family = c("Lorisidae", "Galagonidae", "Daubentoniidae","Indridae", "Lemuridae", "Cheirogaleidae", "Megaladapidae", "Tarsiidae", "Cebidae", "Callitrichidae", "Hylobatidae",     "Pongidae", "Hominidae", "Cercopithecidae"),
  superfamily = c("Lorisiformes", "Lorisiformes", "Lemuriformes", "Lemuriformes", "Lemuriformes", "Lemuriformes", "Lemuriformes","Tarsiiformes", "Platyrrhini", "Platyrrhini", "Hominoidea", "Hominoidea", "Hominoidea", "Cercopithecoidea"))


df_trait_values <- read_csv("data/Raw_Data/data_to_use.csv") %>%
  clean_names() %>%  
  mutate(
    natal_coat = if_else(natal_coat == "Yes", 1, 0),
    sexual_dichromatism = if_else(sexual_dichromatism == "Yes", 1, 0)
  ) %>%
  mutate(
    natal_coat_type_simple = case_when(
      natal_coat_type %in% c("Con to dad", "con to both", "con to mom") ~ "conspicuous",
      natal_coat_type == "incon" ~ "inconspicuous",
      TRUE ~ "none"  # This catches all other cases
    )
  ) %>%
  mutate(
    natal_coat_conspicuous = ifelse(natal_coat_type_simple == "conspicuous", 1, 0),
    natal_coat_inconspicuous = ifelse(natal_coat_type_simple == "inconspicuous", 1, 0),
    natal_coat_present = ifelse(natal_coat_type_simple %in% c("conspicuous", "inconspicuous"), 1, 0)
  ) %>%
  mutate(
    maturation_color_change = case_when(
      natal_coat_type == "Con to dad" ~ "Males only",
      natal_coat_type == "con to mom" ~ "Females only",
      natal_coat_type == "con to both" ~ "Both",
      TRUE ~ "None"
    ),
    maturation_males_only = as.integer(maturation_color_change == "Males only"),
    maturation_females_only = as.integer(maturation_color_change == "Females only"),
    maturation_both = as.integer(maturation_color_change == "Both"),
    maturation_none = as.integer(maturation_color_change == "None")
  ) %>%
  mutate(sexual_dichromatism_complete = ifelse(sexual_dichromatism_type == "Complete", 1, 0),
         sexual_dichromatism_partial = ifelse(sexual_dichromatism_type == "Partial", 1, 0),
         sexual_dichromatism_present = ifelse(sexual_dichromatism_type %in% c("Complete", "Partial"), 1, 0)
  ) %>%
  mutate(
  all_color_traits = ifelse(natal_coat | sexual_dichromatism | 
                            maturation_both | maturation_females_only | maturation_males_only, 1, 0)
)%>%
  select(
    family, genus, species,
    natal_coat, natal_coat_type, natal_coat_type_simple, natal_coat_conspicuous,       natal_coat_inconspicuous, natal_coat_present,
    sexual_dichromatism, sexual_dichromatism_type, sexual_dichromatism_complete, sexual_dichromatism_partial, sexual_dichromatism_present,
    size_dimorphism, maturation_color_change,
    maturation_males_only, maturation_females_only, 
    maturation_both, maturation_none,
    all_color_traits
  )
Rows: 238 Columns: 17
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (16): family, Genus, species, subspecies, Sexual_dimorphism, Sexual_Dimo...
dbl  (1): Size_Dimorphism

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#read in mammal tree
mammaltree <- read.tree("data/Raw_Data/MamPhy_BDvr_Completed_v2_tree0000.tre")
summary(mammaltree)

Phylogenetic tree: mammaltree 

  Number of tips: 5987 
  Number of nodes: 5986 
  Branch lengths:
    mean: 2.680715 
    variance: 24.17565 
    distribution summary:
       Min.     1st Qu.      Median     3rd Qu.        Max. 
  0.0000000   0.5284341   1.3073255   2.9454665 106.6007500 
  No root edge.
  First ten tip labels: X_Shuotherium 
                        X_Pseudotribos
                        X_Asfaltomylos
                        X_Obdurodon
                        Zaglossus_bartoni
                        Zaglossus_bruijnii
                        Zaglossus_attenboroughi
                        Tachyglossus_aculeatus
                        Ornithorhynchus_anatinus
                        X_Teinolophos
  No node labels.
# Assuming mammaltree has already been loaded with read.tree() as in the provided code
Binary_traits_combined <- df_trait_values %>%
  unite("species", genus, species, sep = "_") %>%
  mutate(species = str_to_title(species)) %>%
  mutate(family = str_to_title(family)) %>%
  filter(species %in% mammaltree$tip.label) 

# Format tree to match data
pruned.tree <- drop.tip(mammaltree, setdiff(mammaltree$tip.label, Binary_traits_combined$species))

data_pruned_ordered <- Binary_traits_combined %>%
  arrange(match(species, pruned.tree$tip.label)) %>%
  left_join(superfamily_mapping, by = "family") %>%
  column_to_rownames("species")
# Optionally save the data frame to a csv
write.csv(data_pruned_ordered, file = "~/Desktop/GitHub/LocksofLineage/data/data_pruned_ordered.csv", row.names = TRUE)

# Optionally save the tree into a .nex file
write.nexus(pruned.tree, file = "pruned_tree.nex")

Run the phytools fitPagel model

natal_coats <- setNames(data_pruned_ordered$natal_coat,rownames(data_pruned_ordered))
sexual_dichromatism <- setNames(data_pruned_ordered$sexual_dichromatism,rownames(data_pruned_ordered)) 
size_dimorphism <- setNames(data_pruned_ordered$size_dimorphism,rownames(data_pruned_ordered))
all_color_traits <- setNames(data_pruned_ordered$all_color_traits,rownames(data_pruned_ordered))
# Correlations between natal coats and sexual dichromatism
natal_coats_and_sexual_dichrom_pagel <- fitPagel(pruned.tree, natal_coats, sexual_dichromatism)

anova(natal_coats_and_sexual_dichrom_pagel)
                                        log(L) d.f.      AIC       weight
independent                          -284.6806    4 577.3613 2.328933e-08
natal_coats_and_sexual_dichrom_pagel -263.1054    8 542.2107 1.000000e+00
# Correlations between size dimorphism and the color traits (natal coats and sexual dichromatism)
# size_and_color_pagel <- fitPagel(pruned.tree, size_dimorphism, all_color_traits)
# Plot the natal coat and sexual dichromatism model
plot(natal_coats_and_sexual_dichrom_pagel, lwd.by.rate=TRUE)

Version Author Date
768856f Sarah E Taylor 2024-03-17 
#plot(size_and_color_pagel, lwd.by.rate=TRUE)

Other plots for the poster

#scale_fill_manual(values=c("Lorisidae" = "darkseagreen", "Galagonidae"= "mediumseagreen", "Daubentoniidae" = "chocolate4", "Indridae" = "chocolate2", "Lemuridae" = "salmon", "Cheirogaleidae" = "coral3", "Megaladapidae" = "sienna3", "Tarsiidae" = "gold", "Cebidae" = "cyan", "Callitrichidae" = "turquoise",   "Cercopithecidae" = "burlywood2", "Hylobatidae" = "maroon", "Pongidae" = "violetred2", "Hominidae" = "deeppink1"),)

# Color palatte for streps
tailwind_colors <- c(
  "Blue" = "#000cee",
  "Zaffre" = "#2107a7",
  "ElectricIndigo" = "#6200ff",
  "Indigo" = "#5c0096",
  "DarkViolet" = "#9c00b8",
  "HotMagenta" = "#ea2cda",
  "Fandango" = "#b8008a",
   "Cyan (RGB)" = "#00fffb",
  "Spring Green" = "#00f56a",
  "Forest Green" = "#009138",
  "Gold" = "#ffd500",
  "Pumpkin" = "#ff6a00",
  "Turkey Red" = "#ac0000"
)



# Define the traits
set_attributes <- c(
  'natal_coat_present',
  'natal_coat_conspicuous', 
  'size_dimorphism',
  'sexual_dichromatism_complete', 
  'sexual_dichromatism_partial',
  'maturation_males_only',
  'maturation_females_only',
  'maturation_both')

# Create the plot
upset(
    data_pruned_ordered,
    set_attributes,  
    base_annotations = list(
        'Intersection size' = intersection_size(
            counts = TRUE,
            mapping = aes(fill = family)  # Ensure 'family' is the correct column
        ) + scale_fill_manual(values = c(
            "Lorisidae" = "#ea2cda", 
            "Galagonidae" = "#b8008a", 
            "Daubentoniidae" = "#9c00b8", 
            "Indridae" = "#5c0096", 
            "Lemuridae" = "#000CEE", 
            "Cheirogaleidae" = "#6200ff", 
            "Megaladapidae" = "#2107a7", 
            "Tarsiidae" = "#00fffb",  
            "Cebidae" = "#00f56a", 
            "Callitrichidae" = "#009138", 
            "Cercopithecidae" = "#ffd500", 
            "Hylobatidae" = "#ff6a00", 
            "Pongidae" = "#ac0000", 
            "Hominidae" = "#ac0000"
        ))
    ),
    width_ratio = 0.1
)
Warning in upset_data(data, intersect, mode = mode, encode_sets = encode_sets,
: Converting non-logical columns to binary: natal_coat_present,
natal_coat_conspicuous, size_dimorphism, sexual_dichromatism_complete,
sexual_dichromatism_partial, maturation_males_only, maturation_females_only,
maturation_both
Warning in upset_data(data, intersect, mode = mode, encode_sets = encode_sets,
: Detected missing values in the columns indicating sets, coercing to FALSE
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.

Version Author Date
768856f Sarah E Taylor 2024-03-17 
upset(
    data_pruned_ordered, set_attributes, width_ratio=0.1,
    annotations =list(
        'Family Percentages'=list(
            aes=aes(x=intersection, fill=family),
            geom=list(
                geom_bar(stat='count', position='fill', na.rm=TRUE),
                geom_text(
                    aes(
                        label=!!aes_percentage(relative_to='group'),
                        group=family,
                        color=ifelse(family == 'Cercopithecidae', 'show', 'hide')
                    ),
                    stat='count',
                    position=position_fill(vjust = .5)
                ),
                scale_y_continuous(labels=scales::percent_format())
            )
        )
    )
)
Warning in upset_data(data, intersect, mode = mode, encode_sets = encode_sets,
: Converting non-logical columns to binary: natal_coat_present,
natal_coat_conspicuous, size_dimorphism, sexual_dichromatism_complete,
sexual_dichromatism_partial, maturation_males_only, maturation_females_only,
maturation_both
Warning in upset_data(data, intersect, mode = mode, encode_sets = encode_sets,
: Detected missing values in the columns indicating sets, coercing to FALSE
Warning: The dot-dot notation (`..prop..`) was deprecated in ggplot2 3.4.0.
ℹ Please use `after_stat(prop)` instead.
ℹ The deprecated feature was likely used in the ComplexUpset package.
  Please report the issue at
  <https://github.com/krassowski/complex-upset/issues>.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.text.align` theme element is not
defined in the element hierarchy.
Warning in plot_theme(plot): The `legend.title.align` theme element is not
defined in the element hierarchy.

Version Author Date
768856f Sarah E Taylor 2024-03-17 
VennDiag <- euler(c("A" = 62 + 67, "B" = 13 + 67, "A&B" = 67))
plot(VennDiag, quantities = TRUE, font = 1, cex = 1, alpha = 0.5, fill=c("#F38C79","#D8EDDB"), labels = c("Natal Coats", "Sexual Dichromatism"))

Version Author Date
768856f Sarah E Taylor 2024-03-17 

sessionInfo()
R version 4.3.3 (2024-02-29)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.5

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

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

time zone: America/Denver
tzcode source: internal

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

other attached packages:
 [1] eulerr_7.0.2       ComplexUpset_1.3.3 phytools_2.1-1     maps_3.4.2        
 [5] ape_5.8            janitor_2.2.0      lubridate_1.9.3    forcats_1.0.0     
 [9] stringr_1.5.1      dplyr_1.1.4        purrr_1.0.2        readr_2.1.5       
[13] tidyr_1.3.1        tibble_3.2.1       ggplot2_3.5.1      tidyverse_2.0.0   
[17] workflowr_1.7.1   

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1        farver_2.1.2            optimParallel_1.0-2    
 [4] fastmap_1.2.0           combinat_0.0-8          promises_1.3.0         
 [7] digest_0.6.35           timechange_0.3.0        lifecycle_1.0.4        
[10] processx_3.8.4          polylabelr_0.2.0        magrittr_2.0.3         
[13] compiler_4.3.3          rlang_1.1.3             sass_0.4.9             
[16] tools_4.3.3             igraph_2.0.3            utf8_1.2.4             
[19] yaml_2.3.8              knitr_1.45              phangorn_2.11.1        
[22] clusterGeneration_1.3.8 labeling_0.4.3          bit_4.0.5              
[25] mnormt_2.1.1            scatterplot3d_0.3-44    expm_0.999-9           
[28] withr_3.0.0             numDeriv_2016.8-1.1     polyclip_1.10-6        
[31] grid_4.3.3              fansi_1.0.6             git2r_0.33.0           
[34] colorspace_2.1-0        scales_1.3.0            iterators_1.0.14       
[37] MASS_7.3-60.0.1         cli_3.6.2               crayon_1.5.2           
[40] rmarkdown_2.27          generics_0.1.3          rstudioapi_0.16.0      
[43] httr_1.4.7              tzdb_0.4.0              cachem_1.1.0           
[46] parallel_4.3.3          vctrs_0.6.5             Matrix_1.6-5           
[49] jsonlite_1.8.8          callr_3.7.6             patchwork_1.2.0        
[52] hms_1.1.3               bit64_4.0.5             foreach_1.5.2          
[55] jquerylib_0.1.4         glue_1.7.0              codetools_0.2-19       
[58] ps_1.7.6                stringi_1.8.4           gtable_0.3.5           
[61] later_1.3.2             quadprog_1.5-8          munsell_0.5.1          
[64] pillar_1.9.0            htmltools_0.5.8.1       R6_2.5.1               
[67] doParallel_1.0.17       rprojroot_2.0.4         vroom_1.6.5            
[70] evaluate_0.23           lattice_0.22-5          highr_0.10             
[73] snakecase_0.11.1        httpuv_1.6.15           bslib_0.7.0            
[76] Rcpp_1.0.12             fastmatch_1.1-4         coda_0.19-4.1          
[79] nlme_3.1-164            whisker_0.4.1           xfun_0.44              
[82] fs_1.6.4                getPass_0.2-4           pkgconfig_2.0.3