我正在寻找将交配系统的类型（一夫一妻制、一夫多妻制和混杂）绘制到使用caper包构建的系统发育树ggtree()和 nexus 文件格式的超级树上。我曾尝试在 phytools 网站上遵循本教程，但是我对它的理解还不够。我的 S3 比较数据集如下所示：
我想制作一个圆形/扇形系统发育树，显示哺乳动物在树枝上使用的交配系统类型。重申一下，我已经制作了一棵令人满意的树——我想在它上面添加离散字符（MO、PG 或 PR）——将树的树枝向下可视化为三种颜色之一（红色、蓝色、紫色）。
我将这些数据用于我的树：
structure(list(Order = c("Rodentia", "Lagomorpha", "Primates",
"Afrosoricida", "Carnivora", "Carnivora", "Cingulata", "Artiodactyla",
"Lagomorpha", "Rodentia", "Peramelemorphia", "Rodentia", "Rodentia",
"Carnivora", "Artiodactyla", "Artiodactyla", "Artiodactyla",
"Artiodactyla", "Rodentia", "Artiodactyla", "Chiroptera"), Family =
c("Nesomyidae",
"Leporidae", "Galagidae", "Tenrecidae", "Mustelidae", "Mustelidae",
"Dasypodidae", "Antilocapridae", "Leporidae", "Sciuridae", "Thylacomyidae",
"Sciuridae", "Sciuridae", "Canidae", "Bovidae", "Bovidae", "Bovidae",
"Cervidae", "Sciuridae", "Cervidae", "Noctilionidae"), Genus =
c("Cricetomys",
"Sylvilagus", "Otolemur", "Tenrec", "Mustela", "Mustela", "Dasypus",
"Antilocapra", "Romerolagus", "Sciurus", "Macrotis", "Tamias",
"Tamiasciurus", "Cerdocyon", "Aepyceros", "Redunca", "Saiga",
"Alces", "Sciurus", "Hydropotes", "Noctilio"), Species = c("gambianus",
"floridanus", "garnettii", "ecaudatus", "vison", "sibirica",
"novemcinctus", "americana", "diazi", "niger", "lagotis", "sibiricus",
"hudsonicus", "thous", "melampus", "redunca", "tatarica", "alces",
"variegatoides", "inermis", "leporinus"), Common.name = c("Gambian rat",
"Eastern cottontail", "Northern greater galago", "Tenrec", "American mink",
"Siberian weasel", "Nine-banded armadillo", "Pronghorn", "Volcano rabbit",
"Eastern fox squirrel", "Rabbit-bandicoot or bilby", "Siberian chipmunk",
"Red squirrel", "Crab-eating fox", "Impala", "Bohor reedbuck",
"Saiga antelope", "Moose", "Variegated squirrel", "Water deer",
"Greater bulldog bat"), Wild.or.captive = c("Captive", "Captive",
"Captive", "Captive", "Captive", "Captive", "Captive", "Captive",
"Captive", "Captive", "Captive", "Captive", "Captive", "Captive",
"Captive", "Captive", "Captive", "Captive", "Captive", "Captive",
"Captive"), Sample.size.M = c(3L, 1L, 1L, 1L, 2L, 4L, 1L, NA,
1L, 1L, 1L, 4L, 3L, 1L, NA, 1L, 1L, NA, 5L, 3L, 1L), Source.M = c("Weigl,R",
"Weigl,R", "Weigl,R", "Weigl,R", "Weigl,R", "Weigl,R", "Weigl,R",
"Tidiere, R", "Weigl,R", "Weigl,R", "Weigl,R", "Weigl,R", "Weigl,R",
"Weigl,R", "Tidiere, R", "Weigl,R", "Weigl,R", "Tidiere, R",
"Weigl,R", "Weigl,R", "Weigl,R"), Body.weight.F = c(1.235, 1.303,
0.734, 2, 0.9, 0.395, 4.8, 45.4, 0.536, 0.7643, 0.85, 0.0962,
0.213, 4.35, 43.8, 36, 40.9, 500, 0.4688, 17.4, 0.06), Source = c("ADW",
"Swihart", "ADW", "ADW", "Tidiere, R", "ADW", "ADW", "Tidiere, M",
"ADW", "Hayssen, V", "ADW", "Hayssen, V", "Hayssen, V", "Moehlmen",
"Tidiere, M", "Weckerly", "Müller, D", "Charlton & Reby; Weckerly",
"Hayssen, V", "Müller, D", "ADW"), Mating.system = structure(c(1L,
2L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 3L, 2L, 3L, 3L, 1L, 2L, 1L, 2L,
2L, 3L, 1L, 2L), .Label = c("MO", "PG", "PR"), class = "factor"),
Source2 = c("ADW", "ADW", "ADW", "ADW", "ADW", "ADW", "ADW",
"ADW", "ADW", "ADW", "ADW", "ADW", "ADW", "Lukas & Clutton-Brock",
"ADW", "Lukas & Clutton-Brock", "Charlton & Reby", "Charlton & Reby",
"ADW", "Weckerly", "ADW"), log.FM.lifespan = c(0, -0.0500788643433177,
0.0662862655764385, -0.00419611459360813, 0.115531268086469,
-0.180207825250513, 0.221036224623684, -0.0599979296752854,
-0.0160868198934548, 0.237978249916892, 0, -0.0922148917996766,
-0.0718820073061254, 0.106296626552242, 0.407957129429562,
0.0173048582084705, -0.0211892990699381, 0.0634472180602594,
0.130573776504377, -0.119687227857626, 0), Log.MF.mass = c(0,
-0.0209627117984714, 0.0341244425110258, 0, 0.142667503568732,
0.269690243457735, 0.138302698166281, 0.0753379069658646,
-0.109028734719013, 0.00181452456425008, 0.288065018499614,
-0.0128281958077196, -0.236009903809617, 0.198467480104913,
0.113638155890972, 0.0771659548122993, 0.0958468680905946,
0.198106998873402, 0.0589058009532036, 0.0266224801204141,
0.113943352306837), Binomial = c("Cricetomys_gambianus",
"Sylvilagus_floridanus", "Otolemur_garnettii", "Tenrec_ecaudatus",
"Mustela_vison", "Mustela_sibirica", "Dasypus_novemcinctus",
"Antilocapra_americana", "Romerolagus_diazi", "Sciurus_niger",
"Macrotis_lagotis", "Tamias_sibiricus", "Tamiasciurus_hudsonicus",
"Cerdocyon_thous", "Aepyceros_melampus", "Redunca_redunca",
"Saiga_tatarica", "Alces_alces", "Sciurus_variegatoides",
"Hydropotes_inermis", "Noctilio_leporinus")), .Names = c("Order",
"Family", "Genus", "Species", "Common.name", "Wild.or.captive",
"Sample.size.M", "Source.M", "Body.weight.F", "Source", "Mating.system",
"Source2", "log.FM.lifespan", "Log.MF.mass", "Binomial"), class =
"data.frame", row.names = 30:50)
此代码用于创建 S3 比较数据集（SuperTree 是大多数哺乳动物物种的关联文件。我无法传递此文件，因为我是由其他人提供的）
mammalia <- comparative.data(SuperTree, data, Binomial,vcv=TRUE,
na.omit=FALSE)
最后，创建树的这段代码：
library(ggtree)
PreTree <- ggtree(mammalia$phy)
MyTree <- PreTree +
geom_tiplab(size=1) +
xlim(NA,300) +
geom_cladelabel(node=309, label="Carnivora", color="red", offset=40, align=TRUE) +
geom_cladelabel(node=273, label="Artiodactyla", color="#006633", offset=40, align=TRUE) +
geom_cladelabel(node=224, label="Primates", color="#663300", offset=40, align=TRUE) +
geom_cladelabel(node=206, label="Rodentia", color="#666600", offset=40, align=TRUE)
进化枝标签不会完全复制，因为我只提供了完整数据集的样本——希望这不是问题。
感谢您对我的问题和帮助的耐心等待。