readingAndMatchingTips
Reading trees and matching tips
First, let’s read in a data matrix and inspect it a bit. These are the datasets you’ll need:
- [anolisDataAppended.csv]
# use the complete path
setwd("~/Documents/teaching/comparativeMethods/fall2017UI/exercises/")
anolisData<-read.csv("anolisDataAppended.csv")
mode(anolisData)## [1] "list"dim(anolisData)## [1] 100 11class(anolisData)## [1] "data.frame"#data.frame contains a mix of columns: numeric, character, logical, etc.
# these are the species names
anolisData[,1]## [1] ahli alayoni alfaroi aliniger
## [5] allisoni allogus altitudinalis alumina
## [9] alutaceus angusticeps argenteolus argillaceus
## [13] armouri bahorucoensis baleatus baracoae
## [17] barahonae barbatus barbouri bartschi
## [21] bremeri breslini brevirostris caudalis
## [25] centralis chamaeleonides chlorocyanus christophei
## [29] clivicola coelestinus confusus cooki
## [33] cristatellus cupeyalensis cuvieri cyanopleurus
## [37] cybotes darlingtoni distichus dolichocephalus
## [41] equestris etheridgei eugenegrahami evermanni
## [45] fowleri garmani grahami guafe
## [49] guamuhaya guazuma gundlachi haetianus
## [53] hendersoni homolechis imias inexpectatus
## [57] insolitus isolepis jubar krugi
## [61] lineatopus longitibialis loysiana lucius
## [65] luteogularis macilentus marcanoi marron
## [69] mestrei monticola noblei occultus
## [73] olssoni opalinus ophiolepis oporinus
## [77] paternus placidus poncensis porcatus
## [81] porcus pulchellus pumilis quadriocellifer
## [85] reconditus ricordii rubribarbus sagrei
## [89] semilineatus sheplani shrevei singularis
## [93] smallwoodi strahmi stratulus valencienni
## [97] vanidicus vermiculatus websteri whitemani
## 100 Levels: ahli alayoni alfaroi aliniger allisoni ... whitemaniNow we must reshape our data to prepare for comparative analysis. For almost all analyses in R, species names need to be rownames.
aData<-anolisData[,-1]
rownames(aData)<-anolisData[,1]Now we can read in a phylogenetic tree. This one is in newick format so use read.tree
library(ape)
anolisTree<-read.tree("/Users/lukeharmon/Documents/teaching/r_course/data/anolis.phy")
anolisTree##
## Phylogenetic tree with 100 tips and 99 internal nodes.
##
## Tip labels:
## ahli, allogus, rubribarbus, imias, sagrei, bremeri, ...
##
## Rooted; includes branch lengths.plot(anolisTree)
add.scale.bar()
# can't read the tips!
# better to plot as pdf and control size exactly
# now you DO need to know your working directory, or you can use a whole path
pdf(file="bigTree.pdf", width=18, height=35)
plot(anolisTree)
add.scale.bar()
dev.off()## quartz_off_screen
## 2class(anolisTree)## [1] "phylo"attributes(anolisTree)## $names
## [1] "edge" "Nnode" "tip.label" "edge.length"
##
## $class
## [1] "phylo"
##
## $order
## [1] "cladewise"# we can interact with anolisTree as a list
anolisTree$tip.label## [1] "ahli" "allogus" "rubribarbus"
## [4] "imias" "sagrei" "bremeri"
## [7] "quadriocellifer" "ophiolepis" "mestrei"
## [10] "jubar" "homolechis" "confusus"
## [13] "guafe" "garmani" "opalinus"
## [16] "grahami" "valencienni" "lineatopus"
## [19] "reconditus" "evermanni" "stratulus"
## [22] "krugi" "pulchellus" "gundlachi"
## [25] "poncensis" "cooki" "cristatellus"
## [28] "brevirostris" "caudalis" "marron"
## [31] "websteri" "distichus" "barbouri"
## [34] "alumina" "semilineatus" "olssoni"
## [37] "etheridgei" "fowleri" "insolitus"
## [40] "whitemani" "haetianus" "breslini"
## [43] "armouri" "cybotes" "shrevei"
## [46] "longitibialis" "strahmi" "marcanoi"
## [49] "baleatus" "barahonae" "ricordii"
## [52] "eugenegrahami" "christophei" "cuvieri"
## [55] "barbatus" "porcus" "chamaeleonides"
## [58] "guamuhaya" "altitudinalis" "oporinus"
## [61] "isolepis" "allisoni" "porcatus"
## [64] "argillaceus" "centralis" "pumilis"
## [67] "loysiana" "guazuma" "placidus"
## [70] "sheplani" "alayoni" "angusticeps"
## [73] "paternus" "alutaceus" "inexpectatus"
## [76] "clivicola" "cupeyalensis" "cyanopleurus"
## [79] "alfaroi" "macilentus" "vanidicus"
## [82] "argenteolus" "lucius" "bartschi"
## [85] "vermiculatus" "baracoae" "noblei"
## [88] "smallwoodi" "luteogularis" "equestris"
## [91] "monticola" "bahorucoensis" "dolichocephalus"
## [94] "hendersoni" "darlingtoni" "aliniger"
## [97] "singularis" "chlorocyanus" "coelestinus"
## [100] "occultus"anolisTree$edge.length## [1] 0.044684149 0.034887323 0.067035195 0.137723713 0.127977919
## [6] 0.347724073 0.109078899 0.130888730 0.130888730 0.239967629
## [11] 0.587691702 0.179509950 0.129814050 0.087219218 0.061505998
## [16] 0.257620404 0.147876752 0.109743652 0.109743652 0.319126403
## [21] 0.406345620 0.284615227 0.042155772 0.090522719 0.118865952
## [26] 0.118865952 0.209388672 0.251544443 0.293249779 0.122612861
## [31] 0.217809914 0.019687199 0.200033581 0.200033581 0.219720780
## [36] 0.437530694 0.088772492 0.471371062 0.471371062 0.205198623
## [41] 0.149557576 0.352152059 0.213520271 0.213520271 0.077272447
## [46] 0.030350781 0.131293037 0.326756065 0.326756065 0.071583090
## [51] 0.386466013 0.386466013 0.093111691 0.395288192 0.395288192
## [56] 0.314402578 0.098357487 0.026727495 0.275742347 0.105244885
## [61] 0.170497462 0.170497462 0.302469841 0.400827328 0.010023460
## [66] 0.075979992 0.067203897 0.802108502 0.052409975 0.262223661
## [71] 0.219367178 0.268107688 0.268107688 0.487474866 0.161391311
## [76] 0.588307215 0.211213375 0.377093840 0.377093840 0.078671717
## [81] 0.250527521 0.091430025 0.106656009 0.342027127 0.005421884
## [86] 0.069621835 0.266983407 0.266983407 0.144047107 0.044167182
## [91] 0.148390953 0.148390953 0.192558135 0.196557801 0.252125335
## [96] 0.252125335 0.540113161 0.208968411 0.107638550 0.090953340
## [101] 0.085111020 0.203602151 0.052636755 0.041730454 0.041730454
## [106] 0.094367210 0.297969361 0.383080380 0.474033721 0.434878004
## [111] 0.146794267 0.053688425 0.093105842 0.016803480 0.076302362
## [116] 0.076302362 0.082378874 0.094353148 0.078870445 0.046441175
## [121] 0.085228625 0.037034912 0.253892089 0.092203181 0.174889942
## [126] 0.174889942 0.267093123 0.224962282 0.296022930 0.296022930
## [131] 0.183201729 0.235625627 0.024976244 0.114216523 0.114216523
## [136] 0.139192767 0.374818395 0.643248749 0.125365985 0.377365981
## [141] 0.186957958 0.186957958 0.184942132 0.379381806 0.162169110
## [146] 0.217212696 0.217212696 0.243446819 0.404251581 0.120861969
## [151] 0.120861969 0.060952236 0.009227868 0.118973642 0.335959803
## [156] 0.249896772 0.086063031 0.086063031 0.174699507 0.280233938
## [161] 0.280233938 0.464161314 0.206480322 0.656433195 0.656433195
## [166] 0.105066626 0.120748239 0.249459768 0.524725367 0.524725367
## [171] 0.039535061 0.629719450 0.017899207 0.028491642 0.058539775
## [176] 0.037133600 0.021406175 0.021406175 0.087031418 0.104930625
## [181] 0.064716929 0.032887360 0.031492017 0.605553768 0.221443700
## [186] 0.384110068 0.233182975 0.150927093 0.150927093 0.637045785
## [191] 0.140310460 0.213562660 0.137705751 0.178354275 0.178354275
## [196] 0.316060025 0.529622686 0.894933374anolisTree$edge## [,1] [,2]
## [1,] 101 102
## [2,] 102 103
## [3,] 103 104
## [4,] 104 105
## [5,] 105 106
## [6,] 106 107
## [7,] 107 108
## [8,] 108 1
## [9,] 108 2
## [10,] 107 3
## [11,] 106 4
## [12,] 105 109
## [13,] 109 110
## [14,] 110 111
## [15,] 111 112
## [16,] 112 5
## [17,] 112 113
## [18,] 113 6
## [19,] 113 7
## [20,] 111 8
## [21,] 110 9
## [22,] 109 114
## [23,] 114 115
## [24,] 115 116
## [25,] 116 10
## [26,] 116 11
## [27,] 115 12
## [28,] 114 13
## [29,] 104 117
## [30,] 117 118
## [31,] 118 119
## [32,] 119 120
## [33,] 120 14
## [34,] 120 15
## [35,] 119 16
## [36,] 118 17
## [37,] 117 121
## [38,] 121 18
## [39,] 121 19
## [40,] 103 122
## [41,] 122 123
## [42,] 123 124
## [43,] 124 20
## [44,] 124 21
## [45,] 123 125
## [46,] 125 126
## [47,] 126 127
## [48,] 127 22
## [49,] 127 23
## [50,] 126 128
## [51,] 128 24
## [52,] 128 25
## [53,] 125 129
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## [55,] 129 27
## [56,] 122 130
## [57,] 130 131
## [58,] 131 132
## [59,] 132 28
## [60,] 132 133
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## [62,] 133 30
## [63,] 131 31
## [64,] 130 32
## [65,] 102 134
## [66,] 134 135
## [67,] 135 136
## [68,] 136 33
## [69,] 136 137
## [70,] 137 138
## [71,] 138 139
## [72,] 139 34
## [73,] 139 35
## [74,] 138 36
## [75,] 137 140
## [76,] 140 37
## [77,] 140 141
## [78,] 141 38
## [79,] 141 39
## [80,] 135 142
## [81,] 142 143
## [82,] 143 144
## [83,] 144 145
## [84,] 145 40
## [85,] 145 146
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## [94,] 144 150
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## [97,] 143 48
## [98,] 142 151
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## [100,] 152 153
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## [103,] 155 156
## [104,] 156 49
## [105,] 156 50
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## [110,] 151 157
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## [116,] 159 58
## [117,] 134 160
## [118,] 160 161
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## [131,] 164 169
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## [139,] 162 172
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## [148,] 161 176
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## [162,] 178 81
## [163,] 160 183
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## [166,] 101 184
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## [168,] 185 186
## [169,] 186 84
## [170,] 186 85
## [171,] 185 187
## [172,] 187 188
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## [174,] 189 190
## [175,] 190 86
## [176,] 190 191
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## [179,] 189 89
## [180,] 188 90
## [181,] 187 192
## [182,] 192 193
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## [184,] 194 91
## [185,] 194 195
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## [187,] 195 196
## [188,] 196 93
## [189,] 196 94
## [190,] 193 95
## [191,] 192 197
## [192,] 197 198
## [193,] 198 199
## [194,] 199 96
## [195,] 199 97
## [196,] 198 98
## [197,] 197 99
## [198,] 184 100Some basic analyses with the tree:
# create cophenetic matrix
# patristic distances between all tips
anolisDistanceMatrix<-cophenetic(anolisTree)
head(anolisDistanceMatrix)## ahli allogus rubribarbus imias sagrei bremeri
## ahli 0.0000000 0.2617775 0.4799353 1.175383 1.4313392 1.4313392
## allogus 0.2617775 0.0000000 0.4799353 1.175383 1.4313392 1.4313392
## rubribarbus 0.4799353 0.4799353 0.0000000 1.175383 1.4313392 1.4313392
## imias 1.1753834 1.1753834 1.1753834 0.000000 1.4313392 1.4313392
## sagrei 1.4313392 1.4313392 1.4313392 1.431339 0.0000000 0.5152408
## bremeri 1.4313392 1.4313392 1.4313392 1.431339 0.5152408 0.0000000
## quadriocellifer ophiolepis mestrei jubar homolechis
## ahli 1.4313392 1.4313392 1.4313392 1.431339 1.431339
## allogus 1.4313392 1.4313392 1.4313392 1.431339 1.431339
## rubribarbus 1.4313392 1.4313392 1.4313392 1.431339 1.431339
## imias 1.4313392 1.4313392 1.4313392 1.431339 1.431339
## sagrei 0.5152408 0.6382528 0.8126912 1.072319 1.072319
## bremeri 0.2194873 0.6382528 0.8126912 1.072319 1.072319
## confusus guafe garmani opalinus grahami valencienni
## ahli 1.431339 1.431339 1.706787 1.706787 1.706787 1.706787
## allogus 1.431339 1.431339 1.706787 1.706787 1.706787 1.706787
## rubribarbus 1.431339 1.431339 1.706787 1.706787 1.706787 1.706787
## imias 1.431339 1.431339 1.706787 1.706787 1.706787 1.706787
## sagrei 1.072319 1.072319 1.706787 1.706787 1.706787 1.706787
## bremeri 1.072319 1.072319 1.706787 1.706787 1.706787 1.706787
## lineatopus reconditus evermanni stratulus krugi pulchellus
## ahli 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## allogus 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## rubribarbus 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## imias 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## sagrei 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## bremeri 1.706787 1.706787 1.840857 1.840857 1.840857 1.840857
## gundlachi poncensis cooki cristatellus brevirostris
## ahli 1.840857 1.840857 1.840857 1.840857 1.840857
## allogus 1.840857 1.840857 1.840857 1.840857 1.840857
## rubribarbus 1.840857 1.840857 1.840857 1.840857 1.840857
## imias 1.840857 1.840857 1.840857 1.840857 1.840857
## sagrei 1.840857 1.840857 1.840857 1.840857 1.840857
## bremeri 1.840857 1.840857 1.840857 1.840857 1.840857
## caudalis marron websteri distichus barbouri alumina
## ahli 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## allogus 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## rubribarbus 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## imias 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## sagrei 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## bremeri 1.840857 1.840857 1.840857 1.840857 1.910632 1.910632
## semilineatus olssoni etheridgei fowleri insolitus whitemani
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## haetianus breslini armouri cybotes shrevei longitibialis
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## strahmi marcanoi baleatus barahonae ricordii eugenegrahami
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## christophei cuvieri barbatus porcus chamaeleonides
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632
## guamuhaya altitudinalis oporinus isolepis allisoni porcatus
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## argillaceus centralis pumilis loysiana guazuma placidus
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sheplani alayoni angusticeps paternus alutaceus inexpectatus
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632 1.910632
## clivicola cupeyalensis cyanopleurus alfaroi macilentus
## ahli 1.910632 1.910632 1.910632 1.910632 1.910632
## allogus 1.910632 1.910632 1.910632 1.910632 1.910632
## rubribarbus 1.910632 1.910632 1.910632 1.910632 1.910632
## imias 1.910632 1.910632 1.910632 1.910632 1.910632
## sagrei 1.910632 1.910632 1.910632 1.910632 1.910632
## bremeri 1.910632 1.910632 1.910632 1.910632 1.910632
## vanidicus argenteolus lucius bartschi vermiculatus baracoae
## ahli 1.910632 1.910632 1.910632 2 2 2
## allogus 1.910632 1.910632 1.910632 2 2 2
## rubribarbus 1.910632 1.910632 1.910632 2 2 2
## imias 1.910632 1.910632 1.910632 2 2 2
## sagrei 1.910632 1.910632 1.910632 2 2 2
## bremeri 1.910632 1.910632 1.910632 2 2 2
## noblei smallwoodi luteogularis equestris monticola
## ahli 2 2 2 2 2
## allogus 2 2 2 2 2
## rubribarbus 2 2 2 2 2
## imias 2 2 2 2 2
## sagrei 2 2 2 2 2
## bremeri 2 2 2 2 2
## bahorucoensis dolichocephalus hendersoni darlingtoni aliniger
## ahli 2 2 2 2 2
## allogus 2 2 2 2 2
## rubribarbus 2 2 2 2 2
## imias 2 2 2 2 2
## sagrei 2 2 2 2 2
## bremeri 2 2 2 2 2
## singularis chlorocyanus coelestinus occultus
## ahli 2 2 2 2
## allogus 2 2 2 2
## rubribarbus 2 2 2 2
## imias 2 2 2 2
## sagrei 2 2 2 2
## bremeri 2 2 2 2# tree manipulations
# dropping tips
anolisTree2<-drop.tip(anolisTree, "allogus")
anolisTree##
## Phylogenetic tree with 100 tips and 99 internal nodes.
##
## Tip labels:
## ahli, allogus, rubribarbus, imias, sagrei, bremeri, ...
##
## Rooted; includes branch lengths.anolisTree2##
## Phylogenetic tree with 99 tips and 98 internal nodes.
##
## Tip labels:
## ahli, rubribarbus, imias, sagrei, bremeri, quadriocellifer, ...
##
## Rooted; includes branch lengths.# drop more than one species
anolisTree3<-drop.tip(anolisTree, c("allogus", "sagrei", "bremeri"))
anolisTree3##
## Phylogenetic tree with 97 tips and 96 internal nodes.
##
## Tip labels:
## ahli, rubribarbus, imias, quadriocellifer, ophiolepis, mestrei, ...
##
## Rooted; includes branch lengths.# extras: other good tree functions
# branching times from root to present day
branching.times(anolisTree)## 101 102 103 104 105 106
## 1.00000000 0.95531585 0.92042853 0.85339333 0.71566962 0.58769170
## 107 108 109 110 111 112
## 0.23996763 0.13088873 0.53615967 0.40634562 0.31912640 0.25762040
## 113 114 115 116 117 118
## 0.10974365 0.25154444 0.20938867 0.11886595 0.56014355 0.43753069
## 119 120 121 122 123 124
## 0.21972078 0.20003358 0.47137106 0.71522991 0.56567233 0.21352027
## 125 126 127 128 129 130
## 0.48839988 0.45804910 0.32675607 0.38646601 0.39528819 0.40082733
## 131 132 133 134 135 136
## 0.30246984 0.27574235 0.17049746 0.94529239 0.86931240 0.80210850
## 137 138 139 140 141 142
## 0.74969853 0.48747487 0.26810769 0.58830722 0.37709384 0.79064068
## 143 144 145 146 147 148
## 0.54011316 0.44868314 0.34202713 0.33660524 0.26698341 0.19255813
## 149 150 151 152 153 154
## 0.14839095 0.25212533 0.58167227 0.47403372 0.38308038 0.29796936
## 155 156 157 158 159 160
## 0.09436721 0.04173045 0.14679427 0.09310584 0.07630236 0.86291352
## 161 162 163 164 165 166
## 0.76856037 0.68968992 0.64324875 0.55802012 0.52098521 0.26709312
## 167 168 169 170 171 172
## 0.17488994 0.29602293 0.37481839 0.13919277 0.11421652 0.56432394
## 173 174 175 176 177 178
## 0.18695796 0.37938181 0.21721270 0.52511355 0.12086197 0.46416131
## 179 180 181 182 183 184
## 0.45493345 0.33595980 0.08606303 0.28023394 0.65643319 0.89493337
## 185 186 187 188 189 190
## 0.77418514 0.52472537 0.73465007 0.10493062 0.08703142 0.05853978
## 191 192 193 194 195 196
## 0.02140618 0.66993315 0.63704578 0.60555377 0.38411007 0.15092709
## 197 198 199
## 0.52962269 0.31606003 0.17835427# do the tips all line up?
is.ultrametric(anolisTree)## [1] TRUE# is the tree fully resolved?
is.binary.tree(anolisTree)## [1] TRUE# check monophyly of clades
putativeClade<-c("ahli", "allogus", "rubibarbus")
is.monophyletic(anolisTree, putativeClade)## [1] TRUE# reroot the tree
rer<-root(anolisTree, outgroup="allogus")
plot(rer)
Now you try! Randomly drop 5 species from the tree, then reroot using a random taxon as outgroup. How does this affect your cophenetic distance matrix?
We can also read in many trees at once
# reading in many trees
manyTrees<-read.tree("/Users/lukeharmon/Documents/teaching/r_course/data/multiple_trees.phy")
manyTrees## 100 phylogenetic treesclass(manyTrees)## [1] "multiPhylo"# access individual trees using [[ ]]
# first tree is
manyTrees[[1]]##
## Phylogenetic tree with 84 tips and 83 internal nodes.
##
## Tip labels:
## Kogia_breviceps_KBU72040__, Kogia_simus_AF304072, Physeter_catodon_X75589, Platanista_gangetica_AF304070_, Platanista_minor_X92543, Tasmacetus_shepherdi_AF334484, ...
##
## Rooted; includes branch lengths.class(manyTrees[[1]])## [1] "phylo"plot(manyTrees[[1]])
plot(manyTrees[[45]])
# create a loop to plot all trees
pdf(file="multiTree.pdf")
for(i in 1:10) {
plot(manyTrees[[i]])
}
dev.off()## quartz_off_screen
## 2Finally, we can combine tree and data
dim(aData)## [1] 100 10anolisTree##
## Phylogenetic tree with 100 tips and 99 internal nodes.
##
## Tip labels:
## ahli, allogus, rubribarbus, imias, sagrei, bremeri, ...
##
## Rooted; includes branch lengths.library(geiger)
name.check(anolisTree, aData)## [1] "OK"# EXTRA: this works - they match
# but sometimes you have to match tree and tip data
matchedData<-treedata(anolisTree, aData)What if the match is poor?
phelData<-read.csv("phelsuma_messy.csv")
rownames(phelData)<-phelData[,1]
phelData<-phelData[,-1]
phelTree<-read.tree("phel2.phy")
# nothing matches!
name.check(phelTree, phelData)## $tree_not_data
## [1] "abbotti" "astriata" "barbouri" "borbonica"
## [5] "cepedianaA" "comorensis" "dubia" "grandis"
## [9] "guentheri" "guimbeaui" "guttata" "laticauda"
## [13] "lineata" "longinsulae" "mutabilis" "ornata"
## [17] "quadriocellata" "robertmertensi" "standingi" "sunbergi"
##
## $data_not_tree
## [1] "Phelsuma_abbotti" "Phelsuma_astriata"
## [3] "Phelsuma_barbouri" "Phelsuma_borbonica"
## [5] "Phelsuma_cepedianaA" "Phelsuma_comorensis"
## [7] "Phelsuma_dubia" "Phelsuma_grandis"
## [9] "Phelsuma_guentheri" "Phelsuma_guimbeaui"
## [11] "Phelsuma_guttatus" "Phelsuma_laticauda"
## [13] "Phelsuma_lineata" "Phelsuma_longinsulae"
## [15] "Phelsuma_mutabila" "Phelsuma_ornata"
## [17] "Phelsuma_quadriocellata" "Phelsuma_robertmertensi"
## [19] "Phelsuma_standingi" "Phelsuma_sunbergi"# let's try fuzzy matching
# example with first name
dd<-adist(rownames(phelData)[5], phelTree$tip.label, ignore.case = T)
mm<-which(dd==min(dd))
phelTree$tip.label[mm]## [1] "dubia"distMatrix<-adist(rownames(phelData), phelTree$tip.label)
foo<-function(x) {
namePick<-which(x==min(x))
return(phelTree$tip.label[namePick])
}
goodNames<-apply(distMatrix, 1, foo)
goodNames<-unlist(goodNames)
cbind(rownames(phelData), goodNames)## goodNames
## [1,] "Phelsuma_abbotti" "abbotti"
## [2,] "Phelsuma_astriata" "astriata"
## [3,] "Phelsuma_borbonica" "borbonica"
## [4,] "Phelsuma_cepedianaA" "cepedianaA"
## [5,] "Phelsuma_dubia" "dubia"
## [6,] "Phelsuma_guentheri" "guentheri"
## [7,] "Phelsuma_guttatus" "guttata"
## [8,] "Phelsuma_laticauda" "laticauda"
## [9,] "Phelsuma_lineata" "lineata"
## [10,] "Phelsuma_grandis" "grandis"
## [11,] "Phelsuma_mutabila" "mutabilis"
## [12,] "Phelsuma_ornata" "ornata"
## [13,] "Phelsuma_quadriocellata" "quadriocellata"
## [14,] "Phelsuma_longinsulae" "longinsulae"
## [15,] "Phelsuma_standingi" "standingi"
## [16,] "Phelsuma_sunbergi" "sunbergi"
## [17,] "Phelsuma_barbouri" "barbouri"
## [18,] "Phelsuma_guimbeaui" "guimbeaui"
## [19,] "Phelsuma_comorensis" "comorensis"
## [20,] "Phelsuma_robertmertensi" "robertmertensi"rownames(phelData)<-goodNames
name.check(phelTree, phelData)## [1] "OK"Now try to match another dataset.