R/0d_Final Dataset Creation.R
In gfalbery/ViralSharingPhylogeography: What the Package Does (One Line, Title Case)
# 0d_Final Dataset Creation ####
library(tidyverse);library(Matrix); library(parallel); library(mgcv); library(ggregplot)
# Removing non-eutherian mammals ####
NonEutherians <- c("Diprotodontia",
"Dasyuromorphia",
"Paucituberculata",
"Didelphimorphia",
"Microbiotheria",
"Peramelemorphia",
"Notoryctemorphia",
"Monotremata")
Panth1 <- read.delim("data/PanTHERIA_1-0_WR05_Aug2008.txt") %>%
dplyr::rename(Sp = MSW05_Binomial, hOrder = MSW05_Order)
Panth1$Sp <- Panth1$Sp %>% str_replace(" ", "_")
NonEutherianSp <- Panth1[Panth1$hOrder%in%NonEutherians,"Sp"]
FinalHostNames <- reduce(list(
rownames(FullRangeAdj),
colnames(FullSTMatrix),
rownames(HostAdj)), intersect)
FHN <- FinalHostNames %>% setdiff(NonEutherianSp); length(FHN)
AllMammals <- intersect(colnames(FullSTMatrix),colnames(FullRangeAdj))
AllMammals <- AllMammals[order(AllMammals)]
AbsentHosts <- FHN[which(!FHN%in%AllMammals)]
# Replacing absent names in the full ST matrix ####
NameReplace <- c(
"Micaelamys_namaquensis",
"Akodon_paranaensis",
"Bos_frontalis",
"Bos_grunniens",
"Bubalus_arnee", # Absent
"Capra_hircus",
"Hexaprotodon_liberiensis",
"Equus_burchellii",
"Oryzomys_alfaroi" ,
"Oryzomys_laticeps",
"Oryzomys_megacephalus",
"Callithrix_argentata",
"Miniopterus_schreibersii",
"Myotis_ricketti",
"Oryzomys_albigularis",
"Ovis_aries",
"Piliocolobus_badius",
"Piliocolobus_rufomitratus" ,
"Lycalopex_gymnocercus" ,
"Rhinolophus_hildebrandtii",
"Oryzomys_angouya",
"Mops_condylurus",
"Chaerephon_plicatus",
"Chaerephon_pumilus",
"Taurotragus_oryx")
names(NameReplace) <- AbsentHosts
rownames(FullSTMatrix) <- colnames(FullSTMatrix) <- sapply(rownames(FullSTMatrix), function(a) ifelse(a%in%AbsentHosts, NameReplace[a], a))
NonEutherians <- c("Diprotodontia",
"Dasyuromorphia",
"Paucituberculata",
"Didelphimorphia",
"Microbiotheria",
"Peramelemorphia",
"Notoryctemorphia",
"Monotremata")
Panth1 <- read.delim("data/PanTHERIA_1-0_WR05_Aug2008.txt") %>%
dplyr::rename(Sp = MSW05_Binomial, hOrder = MSW05_Order, hFamily = MSW05_Family)
Panth1$Sp <- Panth1$Sp %>% str_replace(" ", "_")
NonEutherianSp <- Panth1[Panth1$hOrder%in%NonEutherians,"Sp"]
tFullSTMatrix <- 1 - (FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp] -
min(FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp]))/
max(FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp])
tSTMatrix <- tFullSTMatrix
# Going Ahead ####
rownames(Hosts) = Hosts$Sp
FinalHostNames <- reduce(list(
rownames(FullRangeAdj),
colnames(tFullSTMatrix),
rownames(HostAdj)), intersect)
FinalHostNames %>% setdiff(NonEutherianSp)
FHN <- FinalHostNames; length(FHN)
UpperHosts <- # Removing diagonals, as they're uninformative
which(upper.tri(HostAdj[FHN,FHN], diag = T))
HostMatrixdf <- data.frame(Virus = c(HostAdj[FHN, FHN]),
Space = c(FullRangeAdj[FHN, FHN]),
#SpaceA = c(RangeAdjA[FHN, FHN]),
#SpaceB = c(RangeAdjB[FHN, FHN]),
Phylo = c(tFullSTMatrix[FHN, FHN]),
Sp = as.character(rep(FHN, each = length(FHN))),
Sp2 = as.character(rep(FHN, length(FHN)))
)
HostMatrixdf$Sp <- as.character(HostMatrixdf$Sp)
HostMatrixdf$Sp2 <- as.character(HostMatrixdf$Sp2)
HostMatrixVar <- c("hOrder", "hFamily", "hDom", "hAllZACites", "hDiseaseZACites"
#"LongMean", "LatMean")
)
HostMatrixdf[,HostMatrixVar] <- Hosts[HostMatrixdf$Sp, HostMatrixVar]
HostMatrixdf[,paste0(HostMatrixVar,".Sp2")] <- Hosts[HostMatrixdf$Sp2, HostMatrixVar]
HostMatrixdf[HostMatrixdf$Sp == "Lynx_lynx",] <- HostMatrixdf[HostMatrixdf$Sp == "Lynx_lynx",] %>% mutate(hAllZACites = 1167, hDiseaseZACites = 115)
HostMatrixdf <- HostMatrixdf %>% mutate(
hOrder = Hosts[HostMatrixdf$Sp,"hOrder"],
hFamily = Hosts[HostMatrixdf$Sp,"hFamily"],
hDom = Hosts[HostMatrixdf$Sp,"hDom"]
)
HostMatrixdf$Space0 <- ifelse(HostMatrixdf$Space == 0, "No Overlap", "Overlap")
HostMatrixdf$Cites <- log(HostMatrixdf$hAllZACites + 1)
HostMatrixdf$TotalCites <- log(HostMatrixdf$hAllZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$MinCites <- apply(HostMatrixdf[,c("hAllZACites", "hAllZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$DCites <- log(HostMatrixdf$hDiseaseZACites + 1)
HostMatrixdf$MinDCites <- apply(HostMatrixdf[,c("hDiseaseZACites", "hDiseaseZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$TotalDCites <- log(HostMatrixdf$hDiseaseZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$DomDom <- paste(HostMatrixdf$hDom, HostMatrixdf$hDom.Sp2)
HostMatrixdf$DomDom <- ifelse(HostMatrixdf$DomDom == "domestic wild", "wild domestic", HostMatrixdf$DomDom) %>%
factor(levels = c("wild wild", "domestic domestic", "wild domestic"))
UpperHosts <- # Removing diagonals and
which(upper.tri(HostAdj[FHN,FHN], diag = T))
FinalHostMatrix <- HostMatrixdf[-UpperHosts,]
FinalHostMatrix$Phylo <- FinalHostMatrix$Phylo
FinalHostMatrix$MinDCites <- log(FinalHostMatrix$MinDCites + 1)
FinalHostMatrix$VirusBinary <- ifelse(FinalHostMatrix$Virus>0, 1, 0)
Remove1 <- FinalHostMatrix %>% group_by(Sp) %>% dplyr::summarise(Mean = mean(VirusBinary)) %>% slice(order(Mean)) %>% filter(Mean==0) %>% dplyr::select(Sp)
Remove2 <- FinalHostMatrix %>% group_by(Sp2) %>% dplyr::summarise(Mean = mean(VirusBinary)) %>% slice(order(Mean)) %>% filter(Mean==0) %>% dplyr::select(Sp2)
Remove3 <- which(table(c((FinalHostMatrix %>% filter(Phylo < 0.25) %>% dplyr::select(Sp, Sp2))$Sp %>% as.character(),
(FinalHostMatrix %>% filter(Phylo < 0.25) %>% dplyr::select(Sp, Sp2))$Sp2 %>% as.character()))>20) %>%
names
RemoveSp <- intersect(Remove1$Sp, Remove2$Sp2)
FinalHostMatrix <- FinalHostMatrix %>% filter(!Sp%in%RemoveSp&!Sp2%in%RemoveSp)
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix <- FinalHostMatrix %>% slice(order(Sp,Sp2))
# Let's try this a second time ####
FHN <- levels(FinalHostMatrix$Sp)
HostMatrixdf <- data.frame(Virus = c(HostAdj[FHN, FHN]),
Space = c(FullRangeAdj[FHN, FHN]),
Phylo = c(tFullSTMatrix[FHN, FHN]),
Sp = as.character(rep(FHN, each = length(FHN))),
Sp2 = as.character(rep(FHN, length(FHN)))
)
HostMatrixdf$Sp <- as.character(HostMatrixdf$Sp)
HostMatrixdf$Sp2 <- as.character(HostMatrixdf$Sp2)
HostMatrixVar <- c("hOrder", "hFamily", "hDom", "hAllZACites", "hDiseaseZACites")
HostMatrixdf[,HostMatrixVar] <- Hosts[HostMatrixdf$Sp, HostMatrixVar]
HostMatrixdf[,paste0(HostMatrixVar,".Sp2")] <- Hosts[HostMatrixdf$Sp2, HostMatrixVar]
HostMatrixdf$Cites <- log(HostMatrixdf$hAllZACites + 1)
HostMatrixdf$TotalCites <- log(HostMatrixdf$hAllZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$MinCites <- apply(HostMatrixdf[,c("hAllZACites", "hAllZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$DCites <- log(HostMatrixdf$hDiseaseZACites + 1)
HostMatrixdf$MinDCites <- apply(HostMatrixdf[,c("hDiseaseZACites", "hDiseaseZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$TotalDCites <- log(HostMatrixdf$hDiseaseZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$DomDom <- paste(HostMatrixdf$hDom, HostMatrixdf$hDom.Sp2)
HostMatrixdf$DomDom <- ifelse(HostMatrixdf$DomDom == "domestic wild", "wild domestic", HostMatrixdf$DomDom) %>%
factor(levels = c("wild wild", "domestic domestic", "wild domestic"))
UpperHosts <- which(upper.tri(HostAdj[FHN,FHN], diag = T))
FinalHostMatrix <- HostMatrixdf[-UpperHosts,]
FinalHostMatrix$MinDCites <- log(FinalHostMatrix$MinDCites + 1)
FinalHostMatrix$VirusBinary <- ifelse(FinalHostMatrix$Virus>0, 1, 0)
FinalHostMatrix$Gz <- as.numeric(FinalHostMatrix$Space==0)
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix <- FinalHostMatrix %>% slice(order(Sp,Sp2))
# Creating viral subsets ####
# DNA and RNA viruses ####
SubResps <- c("RNA", "DNA", "Vector","NVector")
RNAViruses <- VirusTraits[VirusTraits$vDNAoRNA == "RNA","vVirusNameCorrected"] %>% intersect(rownames(M))
DNAViruses <- VirusTraits[VirusTraits$vDNAoRNA == "DNA","vVirusNameCorrected"] %>% intersect(rownames(M))
MRNA <- M[RNAViruses,]
MDNA <- M[DNAViruses,]
MRNA <- MRNA[,which(colSums(MRNA)>0)]
MDNA <- MDNA[,which(colSums(MDNA)>0)]
RNABipGraph <- graph.incidence(MRNA, weighted = T)
DNABipGraph <- graph.incidence(MDNA, weighted = T)
RNAHostGraph <- bipartite.projection(RNABipGraph)$proj2
DNAHostGraph <- bipartite.projection(DNABipGraph)$proj2
RNAHostAdj <- get.adjacency(RNAHostGraph) %>% as.matrix
DNAHostAdj <- get.adjacency(DNAHostGraph) %>% as.matrix
RNAHostdf <- RNAHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, RNA = value)
DNAHostdf <- DNAHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, DNA = value)
rownames(RNAHostdf) <- with(RNAHostdf, paste(Sp, Sp2))
rownames(DNAHostdf) <- with(DNAHostdf, paste(Sp, Sp2))
FinalHostMatrix <- FinalHostMatrix %>% left_join(RNAHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix <- FinalHostMatrix %>% left_join(DNAHostdf,
by = c("Sp","Sp2"))
# Vector-Borne ####
VectorViruses <- VirusTraits %>% filter(vDNAoRNA == "RNA"&vVectorYNna == "Y") %>%
dplyr::select(vVirusNameCorrected) %>%
unlist %>% intersect(rownames(M))
MVector <- M[VectorViruses,]
MVector <- MVector[,which(colSums(MVector)>0)]
VectorBipGraph <- graph.incidence(MVector, weighted = T)
VectorHostGraph <- bipartite.projection(VectorBipGraph)$proj2
VectorHostAdj <- get.adjacency(VectorHostGraph) %>% as.matrix
VectorHostdf <- VectorHostAdj %>% reshape2::melt() %>%
#dplyr::rename(Sp = Var2, Sp2 = Var1, Vector = value) %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, Vector = value)
rownames(VectorHostdf) <- with(VectorHostdf, paste(Sp, Sp2))
# Non-Vector-Borne ####
NVectorViruses <- VirusTraits %>% filter(vDNAoRNA == "RNA"&vVectorYNna == "N") %>% dplyr::select(vVirusNameCorrected) %>% unlist %>% intersect(rownames(M))
MNVector <- M[NVectorViruses,]
MNVector <- MNVector[,which(colSums(MNVector)>0)]
NVectorBipGraph <- graph.incidence(MNVector, weighted = T)
NVectorHostGraph <- bipartite.projection(NVectorBipGraph)$proj2
NVectorHostAdj <- get.adjacency(NVectorHostGraph) %>% as.matrix
NVectorHostdf <- NVectorHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, NVector = value)
rownames(NVectorHostdf) <- with(NVectorHostdf, paste(Sp, Sp2))
FinalHostMatrix <- FinalHostMatrix %>% left_join(VectorHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix <- FinalHostMatrix %>% left_join(NVectorHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
# Creating full mammal dataset ####
AllMammals <- intersect(rownames(FullSTMatrix), rownames(FullRangeAdj)) %>% setdiff(NonEutherianSp)
AllMammals <- sort(AllMammals)
AllMammalMatrix <- data.frame(
Sp = as.character(rep(AllMammals,each = length(AllMammals))),
Sp2 = as.character(rep(AllMammals,length(AllMammals))),
Space = c(FullRangeAdj[AllMammals,AllMammals]),
Phylo = c(tFullSTMatrix[AllMammals,AllMammals])
) %>%
mutate(Gz = as.numeric(Space==0)) %>%
droplevels
UpperMammals <- which(upper.tri(FullSTMatrix[AllMammals, AllMammals], diag = T))
AllMammaldf <- AllMammalMatrix[-UpperMammals,]
N = nrow(AllMammaldf)
save(FinalHostMatrix, file = "Output Files/Finaldf.Rdata")
gfalbery/ViralSharingPhylogeography documentation built on April 24, 2020, 12:41 p.m.
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# 0d_Final Dataset Creation ####
library(tidyverse);library(Matrix); library(parallel); library(mgcv); library(ggregplot)
# Removing non-eutherian mammals ####
NonEutherians <- c("Diprotodontia",
"Dasyuromorphia",
"Paucituberculata",
"Didelphimorphia",
"Microbiotheria",
"Peramelemorphia",
"Notoryctemorphia",
"Monotremata")
Panth1 <- read.delim("data/PanTHERIA_1-0_WR05_Aug2008.txt") %>%
dplyr::rename(Sp = MSW05_Binomial, hOrder = MSW05_Order)
Panth1$Sp <- Panth1$Sp %>% str_replace(" ", "_")
NonEutherianSp <- Panth1[Panth1$hOrder%in%NonEutherians,"Sp"]
FinalHostNames <- reduce(list(
rownames(FullRangeAdj),
colnames(FullSTMatrix),
rownames(HostAdj)), intersect)
FHN <- FinalHostNames %>% setdiff(NonEutherianSp); length(FHN)
AllMammals <- intersect(colnames(FullSTMatrix),colnames(FullRangeAdj))
AllMammals <- AllMammals[order(AllMammals)]
AbsentHosts <- FHN[which(!FHN%in%AllMammals)]
# Replacing absent names in the full ST matrix ####
NameReplace <- c(
"Micaelamys_namaquensis",
"Akodon_paranaensis",
"Bos_frontalis",
"Bos_grunniens",
"Bubalus_arnee", # Absent
"Capra_hircus",
"Hexaprotodon_liberiensis",
"Equus_burchellii",
"Oryzomys_alfaroi" ,
"Oryzomys_laticeps",
"Oryzomys_megacephalus",
"Callithrix_argentata",
"Miniopterus_schreibersii",
"Myotis_ricketti",
"Oryzomys_albigularis",
"Ovis_aries",
"Piliocolobus_badius",
"Piliocolobus_rufomitratus" ,
"Lycalopex_gymnocercus" ,
"Rhinolophus_hildebrandtii",
"Oryzomys_angouya",
"Mops_condylurus",
"Chaerephon_plicatus",
"Chaerephon_pumilus",
"Taurotragus_oryx")
names(NameReplace) <- AbsentHosts
rownames(FullSTMatrix) <- colnames(FullSTMatrix) <- sapply(rownames(FullSTMatrix), function(a) ifelse(a%in%AbsentHosts, NameReplace[a], a))
NonEutherians <- c("Diprotodontia",
"Dasyuromorphia",
"Paucituberculata",
"Didelphimorphia",
"Microbiotheria",
"Peramelemorphia",
"Notoryctemorphia",
"Monotremata")
Panth1 <- read.delim("data/PanTHERIA_1-0_WR05_Aug2008.txt") %>%
dplyr::rename(Sp = MSW05_Binomial, hOrder = MSW05_Order, hFamily = MSW05_Family)
Panth1$Sp <- Panth1$Sp %>% str_replace(" ", "_")
NonEutherianSp <- Panth1[Panth1$hOrder%in%NonEutherians,"Sp"]
tFullSTMatrix <- 1 - (FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp] -
min(FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp]))/
max(FullSTMatrix[!rownames(FullSTMatrix)%in%NonEutherianSp,!rownames(FullSTMatrix)%in%NonEutherianSp])
tSTMatrix <- tFullSTMatrix
# Going Ahead ####
rownames(Hosts) = Hosts$Sp
FinalHostNames <- reduce(list(
rownames(FullRangeAdj),
colnames(tFullSTMatrix),
rownames(HostAdj)), intersect)
FinalHostNames %>% setdiff(NonEutherianSp)
FHN <- FinalHostNames; length(FHN)
UpperHosts <- # Removing diagonals, as they're uninformative
which(upper.tri(HostAdj[FHN,FHN], diag = T))
HostMatrixdf <- data.frame(Virus = c(HostAdj[FHN, FHN]),
Space = c(FullRangeAdj[FHN, FHN]),
#SpaceA = c(RangeAdjA[FHN, FHN]),
#SpaceB = c(RangeAdjB[FHN, FHN]),
Phylo = c(tFullSTMatrix[FHN, FHN]),
Sp = as.character(rep(FHN, each = length(FHN))),
Sp2 = as.character(rep(FHN, length(FHN)))
)
HostMatrixdf$Sp <- as.character(HostMatrixdf$Sp)
HostMatrixdf$Sp2 <- as.character(HostMatrixdf$Sp2)
HostMatrixVar <- c("hOrder", "hFamily", "hDom", "hAllZACites", "hDiseaseZACites"
#"LongMean", "LatMean")
)
HostMatrixdf[,HostMatrixVar] <- Hosts[HostMatrixdf$Sp, HostMatrixVar]
HostMatrixdf[,paste0(HostMatrixVar,".Sp2")] <- Hosts[HostMatrixdf$Sp2, HostMatrixVar]
HostMatrixdf[HostMatrixdf$Sp == "Lynx_lynx",] <- HostMatrixdf[HostMatrixdf$Sp == "Lynx_lynx",] %>% mutate(hAllZACites = 1167, hDiseaseZACites = 115)
HostMatrixdf <- HostMatrixdf %>% mutate(
hOrder = Hosts[HostMatrixdf$Sp,"hOrder"],
hFamily = Hosts[HostMatrixdf$Sp,"hFamily"],
hDom = Hosts[HostMatrixdf$Sp,"hDom"]
)
HostMatrixdf$Space0 <- ifelse(HostMatrixdf$Space == 0, "No Overlap", "Overlap")
HostMatrixdf$Cites <- log(HostMatrixdf$hAllZACites + 1)
HostMatrixdf$TotalCites <- log(HostMatrixdf$hAllZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$MinCites <- apply(HostMatrixdf[,c("hAllZACites", "hAllZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$DCites <- log(HostMatrixdf$hDiseaseZACites + 1)
HostMatrixdf$MinDCites <- apply(HostMatrixdf[,c("hDiseaseZACites", "hDiseaseZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$TotalDCites <- log(HostMatrixdf$hDiseaseZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$DomDom <- paste(HostMatrixdf$hDom, HostMatrixdf$hDom.Sp2)
HostMatrixdf$DomDom <- ifelse(HostMatrixdf$DomDom == "domestic wild", "wild domestic", HostMatrixdf$DomDom) %>%
factor(levels = c("wild wild", "domestic domestic", "wild domestic"))
UpperHosts <- # Removing diagonals and
which(upper.tri(HostAdj[FHN,FHN], diag = T))
FinalHostMatrix <- HostMatrixdf[-UpperHosts,]
FinalHostMatrix$Phylo <- FinalHostMatrix$Phylo
FinalHostMatrix$MinDCites <- log(FinalHostMatrix$MinDCites + 1)
FinalHostMatrix$VirusBinary <- ifelse(FinalHostMatrix$Virus>0, 1, 0)
Remove1 <- FinalHostMatrix %>% group_by(Sp) %>% dplyr::summarise(Mean = mean(VirusBinary)) %>% slice(order(Mean)) %>% filter(Mean==0) %>% dplyr::select(Sp)
Remove2 <- FinalHostMatrix %>% group_by(Sp2) %>% dplyr::summarise(Mean = mean(VirusBinary)) %>% slice(order(Mean)) %>% filter(Mean==0) %>% dplyr::select(Sp2)
Remove3 <- which(table(c((FinalHostMatrix %>% filter(Phylo < 0.25) %>% dplyr::select(Sp, Sp2))$Sp %>% as.character(),
(FinalHostMatrix %>% filter(Phylo < 0.25) %>% dplyr::select(Sp, Sp2))$Sp2 %>% as.character()))>20) %>%
names
RemoveSp <- intersect(Remove1$Sp, Remove2$Sp2)
FinalHostMatrix <- FinalHostMatrix %>% filter(!Sp%in%RemoveSp&!Sp2%in%RemoveSp)
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix <- FinalHostMatrix %>% slice(order(Sp,Sp2))
# Let's try this a second time ####
FHN <- levels(FinalHostMatrix$Sp)
HostMatrixdf <- data.frame(Virus = c(HostAdj[FHN, FHN]),
Space = c(FullRangeAdj[FHN, FHN]),
Phylo = c(tFullSTMatrix[FHN, FHN]),
Sp = as.character(rep(FHN, each = length(FHN))),
Sp2 = as.character(rep(FHN, length(FHN)))
)
HostMatrixdf$Sp <- as.character(HostMatrixdf$Sp)
HostMatrixdf$Sp2 <- as.character(HostMatrixdf$Sp2)
HostMatrixVar <- c("hOrder", "hFamily", "hDom", "hAllZACites", "hDiseaseZACites")
HostMatrixdf[,HostMatrixVar] <- Hosts[HostMatrixdf$Sp, HostMatrixVar]
HostMatrixdf[,paste0(HostMatrixVar,".Sp2")] <- Hosts[HostMatrixdf$Sp2, HostMatrixVar]
HostMatrixdf$Cites <- log(HostMatrixdf$hAllZACites + 1)
HostMatrixdf$TotalCites <- log(HostMatrixdf$hAllZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$MinCites <- apply(HostMatrixdf[,c("hAllZACites", "hAllZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$DCites <- log(HostMatrixdf$hDiseaseZACites + 1)
HostMatrixdf$MinDCites <- apply(HostMatrixdf[,c("hDiseaseZACites", "hDiseaseZACites.Sp2")],1, function(a) min(a, na.rm = T))
HostMatrixdf$TotalDCites <- log(HostMatrixdf$hDiseaseZACites + HostMatrixdf$hAllZACites.Sp2 + 1)
HostMatrixdf$DomDom <- paste(HostMatrixdf$hDom, HostMatrixdf$hDom.Sp2)
HostMatrixdf$DomDom <- ifelse(HostMatrixdf$DomDom == "domestic wild", "wild domestic", HostMatrixdf$DomDom) %>%
factor(levels = c("wild wild", "domestic domestic", "wild domestic"))
UpperHosts <- which(upper.tri(HostAdj[FHN,FHN], diag = T))
FinalHostMatrix <- HostMatrixdf[-UpperHosts,]
FinalHostMatrix$MinDCites <- log(FinalHostMatrix$MinDCites + 1)
FinalHostMatrix$VirusBinary <- ifelse(FinalHostMatrix$Virus>0, 1, 0)
FinalHostMatrix$Gz <- as.numeric(FinalHostMatrix$Space==0)
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix <- FinalHostMatrix %>% slice(order(Sp,Sp2))
# Creating viral subsets ####
# DNA and RNA viruses ####
SubResps <- c("RNA", "DNA", "Vector","NVector")
RNAViruses <- VirusTraits[VirusTraits$vDNAoRNA == "RNA","vVirusNameCorrected"] %>% intersect(rownames(M))
DNAViruses <- VirusTraits[VirusTraits$vDNAoRNA == "DNA","vVirusNameCorrected"] %>% intersect(rownames(M))
MRNA <- M[RNAViruses,]
MDNA <- M[DNAViruses,]
MRNA <- MRNA[,which(colSums(MRNA)>0)]
MDNA <- MDNA[,which(colSums(MDNA)>0)]
RNABipGraph <- graph.incidence(MRNA, weighted = T)
DNABipGraph <- graph.incidence(MDNA, weighted = T)
RNAHostGraph <- bipartite.projection(RNABipGraph)$proj2
DNAHostGraph <- bipartite.projection(DNABipGraph)$proj2
RNAHostAdj <- get.adjacency(RNAHostGraph) %>% as.matrix
DNAHostAdj <- get.adjacency(DNAHostGraph) %>% as.matrix
RNAHostdf <- RNAHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, RNA = value)
DNAHostdf <- DNAHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, DNA = value)
rownames(RNAHostdf) <- with(RNAHostdf, paste(Sp, Sp2))
rownames(DNAHostdf) <- with(DNAHostdf, paste(Sp, Sp2))
FinalHostMatrix <- FinalHostMatrix %>% left_join(RNAHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix <- FinalHostMatrix %>% left_join(DNAHostdf,
by = c("Sp","Sp2"))
# Vector-Borne ####
VectorViruses <- VirusTraits %>% filter(vDNAoRNA == "RNA"&vVectorYNna == "Y") %>%
dplyr::select(vVirusNameCorrected) %>%
unlist %>% intersect(rownames(M))
MVector <- M[VectorViruses,]
MVector <- MVector[,which(colSums(MVector)>0)]
VectorBipGraph <- graph.incidence(MVector, weighted = T)
VectorHostGraph <- bipartite.projection(VectorBipGraph)$proj2
VectorHostAdj <- get.adjacency(VectorHostGraph) %>% as.matrix
VectorHostdf <- VectorHostAdj %>% reshape2::melt() %>%
#dplyr::rename(Sp = Var2, Sp2 = Var1, Vector = value) %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, Vector = value)
rownames(VectorHostdf) <- with(VectorHostdf, paste(Sp, Sp2))
# Non-Vector-Borne ####
NVectorViruses <- VirusTraits %>% filter(vDNAoRNA == "RNA"&vVectorYNna == "N") %>% dplyr::select(vVirusNameCorrected) %>% unlist %>% intersect(rownames(M))
MNVector <- M[NVectorViruses,]
MNVector <- MNVector[,which(colSums(MNVector)>0)]
NVectorBipGraph <- graph.incidence(MNVector, weighted = T)
NVectorHostGraph <- bipartite.projection(NVectorBipGraph)$proj2
NVectorHostAdj <- get.adjacency(NVectorHostGraph) %>% as.matrix
NVectorHostdf <- NVectorHostAdj %>% reshape2::melt() %>%
dplyr::select(Var2, Var1, value) %>%
dplyr::rename(Sp = Var2, Sp2 = Var1, NVector = value)
rownames(NVectorHostdf) <- with(NVectorHostdf, paste(Sp, Sp2))
FinalHostMatrix <- FinalHostMatrix %>% left_join(VectorHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix <- FinalHostMatrix %>% left_join(NVectorHostdf,
by = c("Sp","Sp2"))
FinalHostMatrix$Sp <- factor(FinalHostMatrix$Sp, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
FinalHostMatrix$Sp2 <- factor(FinalHostMatrix$Sp2, levels = sort(union(FinalHostMatrix$Sp,FinalHostMatrix$Sp2)))
# Creating full mammal dataset ####
AllMammals <- intersect(rownames(FullSTMatrix), rownames(FullRangeAdj)) %>% setdiff(NonEutherianSp)
AllMammals <- sort(AllMammals)
AllMammalMatrix <- data.frame(
Sp = as.character(rep(AllMammals,each = length(AllMammals))),
Sp2 = as.character(rep(AllMammals,length(AllMammals))),
Space = c(FullRangeAdj[AllMammals,AllMammals]),
Phylo = c(tFullSTMatrix[AllMammals,AllMammals])
) %>%
mutate(Gz = as.numeric(Space==0)) %>%
droplevels
UpperMammals <- which(upper.tri(FullSTMatrix[AllMammals, AllMammals], diag = T))
AllMammaldf <- AllMammalMatrix[-UpperMammals,]
N = nrow(AllMammaldf)
save(FinalHostMatrix, file = "Output Files/Finaldf.Rdata")
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