library(ape)
library(phytools)
#> Loading required package: maps
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following object is masked from 'package:ape':
#> 
#>     where
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyr)

A few attributes in bugphyzz only have ‘TRUE’ annotations. Other attributes have both ‘TRUE’ and ‘FALSE’ annotations.

Tips that are uncertain could be treated as FALSE annotations (imputed data) or uncertain annotations with prior probabilities set to 0.5 for TRUE and 0.5 for FALSE. In any case, ASR is not very reliable with any of these approaches, especially when the percentage of tips with annotations is low.

data('primate.tree')
data('primate.data')
tree <- primate.tree
data <- primate.data
data <- data[tree$tip.label,]
# rownames(data) <- paste0('taxon', 1:nrow(data))
# tree$tip.label <- paste0('taxon', 1:Ntip(tree))
myMod <- 'ARD' # 'ARD'
myPi <- 'fitzjohn'
original <- data |>
    tibble::rownames_to_column(var = 'Taxa') |>
    select(Taxa, Activity_pattern) |>
    mutate(Presence = 1) |>
    pivot_wider(
        names_from = 'Activity_pattern', values_from = 'Presence',

                values_fill = 0
    ) |>
    arrange(Taxa) |>
    tibble::column_to_rownames(var = 'Taxa') |>
    select(Diurnal) |> 
    mutate(
        not_diurnal = ifelse(Diurnal == 0, 1, 0)
    ) |> 
    as.matrix()
colnames(original) <- c('A--TRUE', 'A--FALSE')
head(sort(table(sub('^(\\w+)_.*$', '\\1', rownames(original))), decreasing = TRUE))
#> 
#>       Eulemur        Galago        Ateles    Callithrix Cercopithecus 
#>             4             4             3             3             3 
#>        Macaca 
#>             3

Original

fit <- fitMk(tree = tree, x = original,
              model = myMod, pi = myPi,
              lik.func = "pruning", logscale = TRUE)
ace <- ancr(fit, tips = TRUE)
plot(ace, args.plotTree = list(direction = "upwards"))
title(main = '0% uncertain tips', line = -1)

m1 <- original
m1[which(grepl('^Macaca_', rownames(m1))), 1] <- 1
m1[which(!grepl('^Macaca_', rownames(m1))), 1] <- 0
m1[,2] <- ifelse(m1[,1] == 1, 0, 1)
fit1 <- fitMk(tree = tree, x = m1,
              model = myMod, pi = myPi,
              lik.func = "pruning", logscale = TRUE)
ace1 <- ancr(fit1, tips = TRUE)
plot(ace1, args.plotTree = list(direction = "upwards"))
title(main = 'Macaca TRUE', line = -1, sub = '0/1 T/F for unknowns')

m2 <- original
m2[] <- 0.5
m2[which(grepl('^Macaca_', rownames(m2))), 1] <- 1
m2[,2] <- ifelse(m2[,1] == 1, 0, 0.5)
fit2 <- fitMk(tree = tree, x = m2,
              model = myMod, pi = myPi,
              lik.func = "pruning", logscale = TRUE)
ace2 <- ancr(fit2, tips = TRUE)
plot(ace2, args.plotTree = list(direction = "upwards"))
title(main = 'Macaca TRUE', line = -1, sub = '0.5 T/F for unknowns')

m3 <- original
m3[] <- 0.5
m3[which(grepl('^Macaca_', rownames(m3))), 1] <- 1
m3[which(grepl('^Macaca_', rownames(m3))), 2] <- 0
m3[which(grepl('^Galago_', rownames(m3))), 2] <- 1
m3[which(grepl('^Galago', rownames(m3))), 1] <- 0
fit3 <- fitMk(tree = tree, x = m3,
              model = myMod, pi = myPi,
              lik.func = "pruning", logscale = TRUE)
ace3 <- ancr(fit3, tips = TRUE)
plot(ace3, args.plotTree = list(direction = "upwards"))
title(main = 'Macaca TRUE - Galago FALSE', line = -1, sub = '0.5 T/F for unknowns')

Session information

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.1 (2024-06-14)
#>  os       Ubuntu 22.04.4 LTS
#>  system   x86_64, linux-gnu
#>  ui       X11
#>  language en
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Etc/UTC
#>  date     2024-11-21
#>  pandoc   3.2 @ /usr/bin/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package           * version    date (UTC) lib source
#>  ape               * 5.8        2024-04-11 [1] RSPM (R 4.4.0)
#>  bslib               0.8.0      2024-07-29 [1] RSPM (R 4.4.0)
#>  cachem              1.1.0      2024-05-16 [1] RSPM (R 4.4.0)
#>  cli                 3.6.3      2024-06-21 [1] RSPM (R 4.4.0)
#>  clusterGeneration   1.3.8      2023-08-16 [1] RSPM (R 4.4.0)
#>  coda                0.19-4.1   2024-01-31 [1] RSPM (R 4.4.0)
#>  codetools           0.2-20     2024-03-31 [2] CRAN (R 4.4.1)
#>  combinat            0.0-8      2012-10-29 [1] RSPM (R 4.4.0)
#>  DEoptim             2.2-8      2022-11-11 [1] RSPM (R 4.4.0)
#>  desc                1.4.3      2023-12-10 [1] RSPM (R 4.4.0)
#>  digest              0.6.37     2024-08-19 [1] RSPM (R 4.4.0)
#>  doParallel          1.0.17     2022-02-07 [1] RSPM (R 4.4.0)
#>  dplyr             * 1.1.4      2023-11-17 [1] RSPM (R 4.4.0)
#>  evaluate            1.0.1      2024-10-10 [1] RSPM (R 4.4.0)
#>  expm                1.0-0      2024-08-19 [1] RSPM (R 4.4.0)
#>  fansi               1.0.6      2023-12-08 [1] RSPM (R 4.4.0)
#>  fastmap             1.2.0      2024-05-15 [1] RSPM (R 4.4.0)
#>  fastmatch           1.1-4      2023-08-18 [1] RSPM (R 4.4.0)
#>  foreach             1.5.2      2022-02-02 [1] RSPM (R 4.4.0)
#>  fs                  1.6.5      2024-10-30 [1] RSPM (R 4.4.0)
#>  generics            0.1.3      2022-07-05 [1] RSPM (R 4.4.0)
#>  glue                1.8.0      2024-09-30 [1] RSPM (R 4.4.0)
#>  htmltools           0.5.8.1    2024-04-04 [1] RSPM (R 4.4.0)
#>  htmlwidgets         1.6.4      2023-12-06 [1] RSPM (R 4.4.0)
#>  igraph              2.1.1      2024-10-19 [1] RSPM (R 4.4.0)
#>  iterators           1.0.14     2022-02-05 [1] RSPM (R 4.4.0)
#>  jquerylib           0.1.4      2021-04-26 [1] RSPM (R 4.4.0)
#>  jsonlite            1.8.9      2024-09-20 [1] RSPM (R 4.4.0)
#>  knitr               1.49       2024-11-08 [1] RSPM (R 4.4.0)
#>  lattice             0.22-6     2024-03-20 [2] CRAN (R 4.4.1)
#>  lifecycle           1.0.4      2023-11-07 [1] RSPM (R 4.4.0)
#>  magrittr            2.0.3      2022-03-30 [1] RSPM (R 4.4.0)
#>  maps              * 3.4.2.1    2024-11-10 [1] RSPM (R 4.4.0)
#>  MASS                7.3-61     2024-06-13 [2] RSPM (R 4.4.0)
#>  Matrix              1.7-0      2024-04-26 [2] CRAN (R 4.4.1)
#>  mnormt              2.1.1      2022-09-26 [1] RSPM (R 4.4.0)
#>  nlme                3.1-165    2024-06-06 [2] RSPM (R 4.4.0)
#>  numDeriv            2016.8-1.1 2019-06-06 [1] RSPM (R 4.4.0)
#>  optimParallel       1.0-2      2021-02-11 [1] RSPM (R 4.4.0)
#>  phangorn            2.12.1     2024-09-17 [1] RSPM (R 4.4.0)
#>  phytools          * 2.3-0      2024-06-13 [1] RSPM (R 4.4.0)
#>  pillar              1.9.0      2023-03-22 [1] RSPM (R 4.4.0)
#>  pkgconfig           2.0.3      2019-09-22 [1] RSPM (R 4.4.0)
#>  pkgdown             2.1.1      2024-09-17 [1] RSPM (R 4.4.0)
#>  purrr               1.0.2      2023-08-10 [1] RSPM (R 4.4.0)
#>  quadprog            1.5-8      2019-11-20 [1] RSPM (R 4.4.0)
#>  R6                  2.5.1      2021-08-19 [1] RSPM (R 4.4.0)
#>  ragg                1.3.2      2024-05-15 [1] RSPM (R 4.4.0)
#>  Rcpp                1.0.13-1   2024-11-02 [1] RSPM (R 4.4.0)
#>  rlang               1.1.4      2024-06-04 [1] RSPM (R 4.4.0)
#>  rmarkdown           2.29       2024-11-04 [1] RSPM (R 4.4.0)
#>  sass                0.4.9      2024-03-15 [1] RSPM (R 4.4.0)
#>  scatterplot3d       0.3-44     2023-05-05 [1] RSPM (R 4.4.0)
#>  sessioninfo         1.2.2      2021-12-06 [1] RSPM (R 4.4.0)
#>  systemfonts         1.1.0      2024-05-15 [1] RSPM (R 4.4.0)
#>  textshaping         0.4.0      2024-05-24 [1] RSPM (R 4.4.0)
#>  tibble              3.2.1      2023-03-20 [1] RSPM (R 4.4.0)
#>  tidyr             * 1.3.1      2024-01-24 [1] RSPM (R 4.4.0)
#>  tidyselect          1.2.1      2024-03-11 [1] RSPM (R 4.4.0)
#>  utf8                1.2.4      2023-10-22 [1] RSPM (R 4.4.0)
#>  vctrs               0.6.5      2023-12-01 [1] RSPM (R 4.4.0)
#>  withr               3.0.2      2024-10-28 [1] RSPM (R 4.4.0)
#>  xfun                0.49       2024-10-31 [1] RSPM (R 4.4.0)
#>  yaml                2.3.10     2024-07-26 [1] RSPM (R 4.4.0)
#> 
#>  [1] /usr/local/lib/R/site-library
#>  [2] /usr/local/lib/R/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────