/
habitat.Rmd
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habitat.Rmd
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---
title: "Structure by habitat type"
output:
html_document:
df_print: paged
---
Load libraries:
```{r, echo=FALSE}
library(ape)
library(paran)
library(splits)
library(ggplot2)
library(dplyr)
```
Bar plots of all OTU abundance by habitat type
```{r}
# read data
samples_otus<-read.delim("samples_OTUs.txt") %>%
dplyr::arrange(., OTU) %>% # order by otu
mutate(., OTU=as.factor(OTU)) # otu as character not number
levels(samples_otus$OTU)<-unique(samples_otus$OTU) # add levels so that it plots nice (cant use integer because there is not otu 9)
# plot
ggplot(samples_otus, aes(x=OTU, fill=vegetation_type)) +
geom_bar() + theme_bw() +
scale_fill_manual(values=c("green4", "orange"),
name="Vegetation type") +
theme(legend.title=element_text(size=13),
legend.text=element_text(size=12),
axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.x = element_text(size=12),
axis.text.y = element_text(size=12)) +
scale_x_discrete(breaks=seq(0,40,5))
```
Bar plot by family:
```{r}
ggplot(samples_otus, aes(x=OTU, fill=vegetation_type)) +
geom_bar() + theme_bw() +
facet_wrap(. ~ family, scales="free_x") +
scale_fill_manual(values=c("green4", "orange"),
name="Habitat") +
theme(legend.title=element_text(size=13),
legend.text=element_text(size=12),
axis.title.x = element_text(size=13),
axis.title.y = element_text(size=13),
axis.text.x = element_text(size=10),
axis.text.y = element_text(size=12),
strip.text = element_text(size=12)) +
scale_x_discrete(breaks=c(1:11, seq(12,37,3), 39:45))
```
Now plot nice trees.
Modify the plot function from splits (add a 2 so R don't get confused) | Se modifica la función de graficar del paquete splits (se agrega un 2 para que R no se confunda)
```{r}
plotCluster2 <- function(tr, lthresh, show.tip.label = FALSE, # tip labels to FALSE
show.node.label = FALSE, cex = 0.5, edge.width) {
numnod <- tr$Nnode
numtip <- length(tr$tip.label)
cdat <- array(1, 2 * numnod)
ndat <- array("", numnod)
bt <- -branching.times(tr)
nest.nodes <- function(tr, x, p = 0) {
numtip <- length(tr$tip.label)
nods <- array(NA, 0)
desc <- as.integer(tr$edge[, 2][tr$edge[, 1] == x])
if (desc[1] > numtip) {
nods <- c(nods, desc[1], nest.nodes(tr, desc[1]))
}
if (desc[2] > numtip) {
nods <- c(nods, desc[2], nest.nodes(tr, desc[2]))
}
if (length(nods) > 0) {
return(nods)
}
else {
return(NULL)
}
}
threshold.group <- function(mrcas) {
parent <- tr$edge[, 1]
child <- tr$edge[, 2]
thresh.group <- list()
thresh.time <- c()
mrcas <- mrcas + numtip
k <- 1
while (TRUE) {
times <- bt[mrcas - numtip]
thresh1.time <- min(times)
thresh1.node <- mrcas[which.min(times)]
mrcas <- mrcas[-which.min(times)]
if (length(mrcas) == 0) {
thresh.time <- c(thresh.time, thresh1.time)
thresh.group[[k]] <- thresh1.node
break
}
member <- thresh1.node
del <- c()
for (i in 1:length(mrcas)) {
par.nod <- parent[child == mrcas[i]]
t.par <- bt[par.nod - numtip]
if (t.par < thresh1.time) {
member <- c(member, mrcas[i])
del <- c(del, i)
}
}
thresh.time <- c(thresh.time, thresh1.time)
thresh.group[[k]] <- member
k <- k + 1
if (length(del) != 0) {
mrcas <- mrcas[-del]
}
if (length(mrcas) == 0) {
break
}
}
return(thresh.group)
}
group <- threshold.group(lthresh)
colors <- rainbow(length(group))
k <- 1
for (g in group) {
n.col.type <- rep(0, numnod)
for (j in 1:length(g)) {
n.col.type[g[j] - numtip] <- 2
n.col.type[nest.nodes(tr, g[j]) - numtip] <- 1
}
cdat[match(tr$edge[, 1], which((n.col.type == 1) |
(n.col.type == 2)) + numtip) > 0] <-
colors[k]
k <- k + 1
}
plot(tr, edge.color = cdat, use.edge.length = 1, show.node.label =
show.node.label,
show.tip.label = show.tip.label, no.margin = FALSE,
cex = cex, edge.width=edge.width)
}
```
Use the trees resulted from the GMYC analysis (see "otus_delimitation.Rmd"). First, get population names and habitat from sequences names. B corresponds to forest and Z to alpine grasslands. | Se usan los árboles que resultaron del análisis GMYC (explicado en "otus_delimitation.Rmd"). Primero, se obtienen los nombres de las poblaciones y el tipo de vegetación de los nombres de las secuencias. B corresponde a bosques, y Z a pastizal alpino.
```{r, fig.width=12, fig.height=7}
Ttree<-read.nexus("trees/CurculionidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
# change tips
x<-Tgmyc
nomtips<-substr((x$tr)$tip.label, 1,2)
nomtips #Population
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
# plot tree according to habitat type
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=nomtips, frame="none", col="black", cex=1, adj=0, offset = 0.018)
# add OTU names
edgelabels(text=c("OTU 5", "OTU 4", "OTU 3", "OTU 2", "OTU 7", "OTU 6", "OTU 1"), edge=c(54, 51, 24, 15, 14, 13, 4), frame="none", adj = c(0.5, -0.25), cex=.7, date= .09)
# plot Time vs likelihood
plot(x$threshold.time, x$likelihood,type = "l", xlab = "Time", ylab = "Likelihood", cex.lab=1.5, cex.axis=1.5)
# plot time vs number of entityes and threshold time: -0.03913536
plot(x$threshold.time, x$entity, type="s" , xlab = "Time", ylab = "N", cex.lab=1.5, cex.axis=1.5)
abline(v=-0.03913536, col="red")
```
### Full figures for all Families:
Curculionidae
```{r, echo= FALSE, fig.width=12, fig.height=11}
Ttree<-read.nexus("trees/CurculionidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
# change tips
x<-Tgmyc
nomtips<-substr((x$tr)$tip.label, 1,2)
nomtips #Population
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
## PLOT
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE),
heights=c(2,1))
# plot tree according to habitat type
par(mar=c(0, 4, 2.5, 4))
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=nomtips, frame="none", col="black", cex=1, adj=0, offset = 0.018)
title(main="Curculionidae (Coleoptera) \na)",adj=0, cex.main=1.5)
# add OTU names
edgelabels(text=c("OTU 5", "OTU 4", "OTU 3", "OTU 2", "OTU 7", "OTU 6", "OTU 1"), edge=c(54, 51, 24, 15, 14, 13, 4), frame="none", adj = c(0.5, -0.25), cex=.7, date= .09)
# plot Time vs likelihood
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$likelihood,type = "l", xlab = "Time", ylab = "Likelihood", cex.lab=1.5, cex.axis=1.5, lwd=2)
title(main="b)",adj=0, cex.main=1.5)
# plot time vs number of entityes and threshold time
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$entity, type="s" , xlab = "Time", ylab = "N", cex.lab=1.5, cex.axis=1.5, lwd=2)
abline(v=-0.03913536, col="red", lwd=2)
title(main="c)",adj=0, cex.main=1.5)
```
Carabideae
```{r, echo=FALSE, results= "hide", fig.width=12, fig.height=12}
Ttree<-read.nexus("trees/CarabidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
# change tips
x<-Tgmyc
nomtips<-substr((x$tr)$tip.label, 1,2)
nomtips #Population
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
## PLOT
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE),
heights=c(3,1.2))
# plot tree according to habitat type
par(mar=c(0, 4, 2.5, 4))
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=nomtips, frame="none", col="black", cex=1, adj=0, offset = 0.018)
title("Carabidae (Coleoptera) \na)",adj=0, cex.main=1.5)
# add OTU names
edgelabels(text=c("OTU 11", "OTU 10"), edge=c(38,1), frame="none", adj = c(0.5, -0.25), cex=.8, date= .2)
# plot Time vs likelihood
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$likelihood,type = "l", xlab = "Time", ylab = "Likelihood", cex.lab=1.5, cex.axis=1.5, lwd=2)
title(main="b)",adj=0, cex.main=1.5)
# plot time vs number of entityes and threshold time
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$entity, type="s" , xlab = "Time", ylab = "N", cex.lab=1.5, cex.axis=1.5, lwd=2, ylim=c(1,20))
abline(v=-0.05120494, col="red", lwd=2)
title(main="c)",adj=0, cex.main=1.5)
```
Linyphiidae.
This family has many OTUs, check OTU names were assigned correctly
```{r, results= "hide", fig.width=13, fig.height=32}
Ttree<-read.nexus("trees/LinyphiidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
x<-Tgmyc
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
# get which CROP OTU is each tip
nomtips<-(x$tr)$tip.label
nomtips<-as.data.frame(nomtips)
otu_tips<-inner_join(nomtips, samples_otus, by=c("nomtips"="sample_id"))
####
# plot tree according to habitat type and otus name
par(mar=c(0, 4, 2.5, 4))
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=otu_tips$OTU, frame="none", col="black", cex=.50, adj=0, offset = 0.006)
tiplabels(text=(x$tr)$tip.label, frame="none", col="black", cex=.4, adj=0, offset= 0.016)
title("Linyphiidae (Aranae) \na)",adj=0, cex.main=1.5)
# add OTU names
edgelabels(text=c("OTU 31", "OTU 28", "OTU 27", "OTU 34", "OTU 26", "OTU 38", "OTU 25", "OTU 24", "OTU 23", "OTU 29", "OTU 22", "OTU 21", "OTU 20", "OTU 19", "OTU 18", "OTU 33", "OTU 18", "OTU 35", "OTU 17", "OTU 16", "OTU 32", "OTU 15", "OTU 14", "OTU 13", "OTU 36", "OTU 30", "OTU 37", "OTU 12"),
edge=c(256, 245, 236, 235, 220, 215, 203, 196, 192, 190, 187, 180, 159, 150, 130, 129, 122, 118, 103, 100, 98, 62, 37, 15, 13, 9, 8, 2),
frame="none", adj = c(0.5, -0.25), cex=.6)
```
Now nice plot:
```{r, echo=FALSE, results= "hide", fig.width=12, fig.height=32}
Ttree<-read.nexus("trees/LinyphiidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
# change tips
x<-Tgmyc
nomtips<-substr((x$tr)$tip.label, 1,2)
nomtips #Population
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
## PLOT
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE),
heights=c(6,1))
# plot tree according to habitat type
par(mar=c(0, 4, 2.5, 4))
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=nomtips, frame="none", col="black", cex=1, adj=0, offset = 0.018)
title("Linyphiidae (Aranae) \na)",adj=0, cex.main=1.5)
# add OTU names
edgelabels(text=c("OTU 31", "OTU 28", "OTU 27", "OTU 34", "OTU 26", "OTU 38", "OTU 25", "OTU 24", "OTU 23", "OTU 29", "OTU 22", "OTU 21", "OTU 20", "OTU 19", "OTU 18", "OTU 33", "OTU 18", "OTU 35", "OTU 17", "OTU 16", "OTU 32", "OTU 15", "OTU 14", "OTU 13", "OTU 36", "OTU 30", "OTU 37", "OTU 12"),
edge=c(256, 245, 236, 235, 220, 215, 203, 196, 192, 190, 187, 180, 159, 150, 130, 129, 122, 118, 103, 100, 98, 62, 37, 15, 13, 9, 8, 2),
frame="none", adj = c(0.5, -0.25), cex=.6)
# plot Time vs likelihood
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$likelihood,type = "l", xlab = "Time", ylab = "Likelihood", cex.lab=1.5, cex.axis=1.5, lwd=2)
title(main="b)",adj=0, cex.main=1.5)
# plot time vs number of entityes and threshold time
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$entity, type="s" , xlab = "Time", ylab = "N", cex.lab=1.5, cex.axis=1.5, lwd=2)
abline(v=-0.07269869, col="red", lwd=2)
title(main="c)",adj=0, cex.main=1.5)
```
Gnaphosidae
```{r, echo=FALSE, results= "hide", fig.width=12, fig.height=8}
Ttree<-read.nexus("trees/GnaphosidaeTtree")
# run gmyc
Tgmyc<-gmyc(Ttree, method="single", interval=c(0,10),quiet=F)
# change tips
x<-Tgmyc
nomtips<-substr((x$tr)$tip.label, 1,2)
nomtips #Population
samtips<-substr((x$tr)$tip.label, 3,3)
samtips #habitat
#Definir color por tipo de vegetación (samtips)
samtips<-as.factor(samtips)
levels(samtips)<-c("green4", "orange")
samtips
## PLOT
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE))
# plot tree according to habitat type
par(mar=c(0, 4, 2.5, 4))
plotCluster2(x$tree, x$MRCA[[which.max(x$likelihood)]], edge.width=2)
tiplabels(pch=15, col=as.vector(samtips), adj=0, offset=0.51, cex=1.5)
tiplabels(text=nomtips, frame="none", col="black", cex=1, adj=0, offset = 0.018)
title("Gnaphosidae (Aranae) \na)",adj=0, cex.main=1.5)
# Plot OTUs name
edgelabels(text=c("OTU 45", "OTU 44", "OTU 43", "OTU 42", "OTU 41", "OTU 40", "OTU 39"), edge=c(38, 35, 32, 26, 23, 10, 3), frame="none", adj = c(0.5, -0.25), cex=.8, date= .1)
# plot Time vs likelihood
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$likelihood,type = "l", xlab = "Time", ylab = "Likelihood", cex.lab=1.5, cex.axis=1.5, lwd=2)
title(main="b)",adj=0, cex.main=1.5)
# plot time vs number of entityes and threshold time
par(mar=c(4, 4, 2, 4))
plot(x$threshold.time, x$entity, type="s" , xlab = "Time", ylab = "N", cex.lab=1.5, cex.axis=1.5, lwd=2)
abline(v=-0.02034695, col="red", lwd=2)
title(main="c)",adj=0, cex.main=1.5)
```