从物种列表中制作简单的系统发育树状图(树)

Question

我想为海洋生物学课程制作一个简单的系统发育树作为教育的例子.我有一个具有分类等级的物种清单:

    Group <- c("Benthos","Benthos","Benthos","Benthos","Benthos","Benthos","Zooplankton","Zooplankton","Zooplankton","Zooplankton",
"Zooplankton","Zooplankton","Fish","Fish","Fish","Fish","Fish","Fish","Phytoplankton","Phytoplankton","Phytoplankton","Phytoplankton")
Domain <- rep("Eukaryota", length(Group))
Kingdom <- c(rep("Animalia", 18), rep("Chromalveolata", 4))
Phylum <- c("Annelida","Annelida","Arthropoda","Arthropoda","Porifera","Sipunculida","Arthropoda","Arthropoda","Arthropoda",
"Arthropoda","Echinoidermata","Chorfata","Chordata","Chordata","Chordata","Chordata","Chordata","Chordata","Heterokontophyta",
"Heterokontophyta","Heterokontophyta","Dinoflagellata")
Class <- c("Polychaeta","Polychaeta","Malacostraca","Malacostraca","Demospongiae","NA","Malacostraca","Malacostraca",
"Malacostraca","Maxillopoda","Ophiuroidea","Actinopterygii","Chondrichthyes","Chondrichthyes","Chondrichthyes","Actinopterygii",
"Actinopterygii","Actinopterygii","Bacillariophyceae","Bacillariophyceae","Prymnesiophyceae","NA")
Order <- c("NA","NA","Amphipoda","Cumacea","NA","NA","Amphipoda","Decapoda","Euphausiacea","Calanioda","NA","Gadiformes",
"NA","NA","NA","NA","Gadiformes","Gadiformes","NA","NA","NA","NA")                     
Species <- c("Nephtys sp.","Nereis sp.","Gammarus sp.","Diastylis sp.","Axinella sp.","Ph. Sipunculida","Themisto abyssorum","Decapod larvae (Zoea)",
"Thysanoessa sp.","Centropages typicus","Ophiuroidea larvae","Gadus morhua eggs / larvae","Etmopterus spinax","Amblyraja radiata",
"Chimaera monstrosa","Clupea harengus","Melanogrammus aeglefinus","Gadus morhua","Thalassiosira sp.","Cylindrotheca closterium",
"Phaeocystis pouchetii","Ph. Dinoflagellata")   
dat <- data.frame(Group, Domain, Kingdom, Phylum, Class, Order, Species)
dat

我想获得树状图(聚类分析)并使用Domain作为第一个切割点,Kindom作为第二个切割点,Phylum作为第三个切割点,等等.缺失值应该被忽略(没有切割点,而是直线).组应该用作标签的着色类别.

我有点不确定如何从这个数据帧制作距离矩阵.R有很多系统发育树包,他们似乎想要新的数据/ DNA /其他高级信息.因此,对此的帮助将不胜感激.

Answer 1

回答我自己的问题可能有点蹩脚,但我找到了一个更简单的解决方案.也许有一天会帮助别人.

library(ape)
taxa <- as.phylo(~Kingdom/Phylum/Class/Order/Species, data = dat)

col.grp <- merge(data.frame(Species = taxa$tip.label), dat[c("Species", "Group")], by = "Species", sort = F)

cols <- ifelse(col.grp$Group == "Benthos", "burlywood4", ifelse(col.grp$Group == "Zooplankton", "blueviolet", ifelse(col.grp$Group == "Fish", "dodgerblue", ifelse(col.grp$Group == "Phytoplankton", "darkolivegreen2", ""))))

plot(taxa, type = "cladogram", tip.col = cols)

请注意,所有列都必须是因子.这演示了使用R的工作流程.虽然代码本身只是几行=)但需要一周时间才能找到一些东西.