R/amp_venn.R
In MadsAlbertsen/ampvis: Tools for visualising amplicon data
Defines functions
amp_venn
Documented in
amp_venn
#' Generates a ggplot2 style venn diagram
#'
#' Calculates the number of "core" OTUs shared by groups given tresholds for how frequent the OTUs should be above a certain abundance. Also returns the average abundance of the OTUs in a particular group.
#'
#' @usage amp_venn(data)
#'
#' @param data (required) A phyloseq object.
#' @param group Group the data based on a sample variable.
#' @param cut_a Abundance cutoff in percent (default: 0.1).
#' @param cut_f Frequency cutoff in percent (default: 80).
#' @param text.size Size of the plotted text.
#' @param output Either "plot" or "complete" (default: "plot").
#'
#' @return A ggplot2 object
#'
#' @export
#' @import ggplot2
#' @import dplyr
#' @import reshape2
#' @import phyloseq
#'
#' @author Mads Albertsen \email{MadsAlbertsen85@@gmail.com}
amp_venn <- function(data, group = NULL,cut_a = 0.1, cut_f = 80, text.size = 5, output = "plot"){
## Retrieve data
abund <- as.data.frame(otu_table(data)@.Data)
tax <- data.frame(tax_table(data)@.Data)
OTU <- rownames(tax_table(data))
sample <- suppressWarnings(as.data.frame(as.matrix(sample_data(data))))
## Test for number of groups
if (length(levels(sample[,group])) > 3){
stop(paste("A maximum of 3 levels are supported. The grouping viable contains:",
paste(levels(sample[,group]), collapse = ", ")))
}
## Select grouping variable
colnames(sample)[1] <- "SeqID"
if (!is.null(group)){
sample <- sample[,c("SeqID", group)]
colnames(sample)[2] <- "GRP"
} else {
sample <- data.frame(SeqID = sample[,1], GRP = "Core")
}
## Add OTU names to the abundance information
abund1 <- cbind.data.frame(abund, OTU)
## Melt the dataframe for subsequent processing
abund2 <- melt(abund1, id.var = "OTU", value.name= "Abundance", variable.name = "SeqID")
## Merge sample information with the abundance data
abund3 <- merge(abund2, sample, by = "SeqID")
## Add frequent abundant column
abund4 <- mutate(abund3,
Freq = ifelse(Abundance > cut_a, 1, 0))
## Evaluate if OTUs are part of the core
abund5 <- group_by(abund4, OTU, GRP) %>%
summarise(Abundance = mean(Abundance),
cFreq = sum(Freq)/n()*100,
Core = ifelse(sum(Freq)/n()*100 >= cut_f, 1, 0))
## Convert back into matrix format
a <- dcast(abund5, OTU~GRP, value.var = "Core")
################### PLOT #############################
## 1 group
if(ncol(a) == 2){
c_A <- subset(a, a[,2] == 1)
c_n <- subset(a, a[,2] == 0)
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(A = nrow(c_A), N = nrow(c_n)),
abund = round(c(A = a_A$Sum, N = a_n$Sum), 1))
## Plot
p <- ggplot(data.frame(), aes(x=0, y=0)) +
annotate("text", x=c(0, 0), y = c(0,-0.5),
label = c(paste(AD[1,1], "\n(", AD[1,2],")", sep = ""),
paste("Non-core: ", AD[2,1]," (", AD[2,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(0), y = 0.45, label = colnames(a)[2], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=00.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
## Generate lists of species in each group
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared))
res <- list(plot = p,
A = as.character(unique(c_A$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2] <- colnames(a)[2]
}
## 2 groups
if(ncol(a) == 3){
c_AB <- subset(a, a[,2] == 1 & a[,3] == 1)
c_A <- subset(a, a[,2] == 1 & a[,3] == 0)
c_B <- subset(a, a[,2] == 0 & a[,3] == 1)
c_n <- subset(a, a[,2] == 0 & a[,3] == 0)
a_AB <- subset(abund5, OTU %in% c_AB$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_B <- subset(abund5, OTU %in% c_B$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(A = nrow(c_A), AB = nrow(c_AB), B = nrow(c_B), N = nrow(c_n)),
abund = round(c(A = a_A$Sum, AB = a_AB$Sum, B = a_B$Sum, N = a_n$Sum), 1))
p <- ggplot(data.frame(), aes(x=c(-0.2,0.2), y=0)) +
annotate("text", x=c(-0.4, 0, 0.4, 0), y = c(0,0,0,-0.5),
label = c(paste(AD[1:3,1], "\n(", AD[1:3,2],")", sep = ""),
paste("Non-core: ", AD[4,1]," (", AD[4,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(-0.2, 0.2), y = 0.45, label = colnames(a)[2:3], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=-0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_B$OTU)), colnames(a)[3], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AB$OTU)), "Core", Shared))
res <- list(plot = p,
A = as.character(unique(c_A$OTU)),
B = as.character(unique(c_B$OTU)),
Core = as.character(unique(c_AB$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2:4] <- c(colnames(a)[2],
colnames(a)[3],
"Core")
}
## 3 groups
if(ncol(a) == 4){
c_ABC <- subset(a, a[,2] == 1 & a[,3] == 1 & a[,4] == 1)
c_AB <- subset(a, a[,2] == 1 & a[,3] == 1 & a[,4] == 0)
c_AC <- subset(a, a[,2] == 1 & a[,3] == 0 & a[,4] == 1)
c_BC <- subset(a, a[,2] == 0 & a[,3] == 1 & a[,4] == 1)
c_A <- subset(a, a[,2] == 1 & a[,3] == 0 & a[,4] == 0)
c_B <- subset(a, a[,2] == 0 & a[,3] == 1 & a[,4] == 0)
c_C <- subset(a, a[,2] == 0 & a[,3] == 0 & a[,4] == 1)
c_n <- subset(a, a[,2] == 0 & a[,3] == 0 & a[,4] == 0)
a_ABC <- subset(abund5, OTU %in% c_ABC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_AB <- subset(abund5, OTU %in% c_AB$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_AC <- subset(abund5, OTU %in% c_AC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_BC <- subset(abund5, OTU %in% c_BC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_B <- subset(abund5, OTU %in% c_B$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_C <- subset(abund5, OTU %in% c_C$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(ABC = nrow(c_ABC), AB = nrow(c_AB),AC = nrow(c_AC), BC = nrow(c_BC),
A = nrow(c_A), B = nrow(c_B), C = nrow(c_C), N = nrow(c_n)),
abund = round(c(ABC = a_ABC$Sum, AB = a_AB$Sum, AC = a_AC$Sum, BC = a_BC$Sum,
A = a_A$Sum, B = a_B$Sum, C = a_C$Sum, N = a_n$Sum), 1))
p <- ggplot(data.frame(), aes(x=c(-0.2,0.2), y=0)) +
annotate("text", x=c(0, 0, -0.25, 0.25, -0.4, 0.4, 0, 0.5), y = c(0.05, 0.4, -0.05, -0.05, 0.3, 0.3, -0.3, -0.6),
label = c(paste(AD[1:7,1], "\n(", AD[1:7,2],")", sep = ""),
paste("Non-core:\n", AD[8,1]," (", AD[8,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(-0.2, 0.2, 0), y = c(0.65, 0.65, -0.65), label = colnames(a)[2:4], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=-0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=0+0.4*cos(seq(0,2*pi,length.out=100)),
y=-0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_ABC$OTU)), "Core", Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AB$OTU)), paste(colnames(a)[2], colnames(a)[3], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AC$OTU)), paste(colnames(a)[2], colnames(a)[4], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_BC$OTU)), paste(colnames(a)[3], colnames(a)[4], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_B$OTU)), colnames(a)[3], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_C$OTU)), colnames(a)[4], Shared))
res <- list(plot = p,
Core = as.character(unique(c_ABC$OTU)),
AB = as.character(unique(c_AB$OTU)),
AC = as.character(unique(c_AC$OTU)),
BC = as.character(unique(c_BC$OTU)),
A = as.character(unique(c_A$OTU)),
B = as.character(unique(c_B$OTU)),
C = as.character(unique(c_C$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2:8] <- c("Core",
paste(colnames(a)[2], colnames(a)[3], sep = "_"),
paste(colnames(a)[2], colnames(a)[4], sep = "_"),
paste(colnames(a)[3], colnames(a)[4], sep = "_"),
colnames(a)[2],
colnames(a)[3],
colnames(a)[4]
)
}
## Export data
if(output == "complete"){ return(res) }
if(output == "plot"){ return(p) }
}
MadsAlbertsen/ampvis documentation built on May 7, 2019, 2:08 p.m.
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Defines functions amp_venn
Documented in amp_venn
#' Generates a ggplot2 style venn diagram
#'
#' Calculates the number of "core" OTUs shared by groups given tresholds for how frequent the OTUs should be above a certain abundance. Also returns the average abundance of the OTUs in a particular group.
#'
#' @usage amp_venn(data)
#'
#' @param data (required) A phyloseq object.
#' @param group Group the data based on a sample variable.
#' @param cut_a Abundance cutoff in percent (default: 0.1).
#' @param cut_f Frequency cutoff in percent (default: 80).
#' @param text.size Size of the plotted text.
#' @param output Either "plot" or "complete" (default: "plot").
#'
#' @return A ggplot2 object
#'
#' @export
#' @import ggplot2
#' @import dplyr
#' @import reshape2
#' @import phyloseq
#'
#' @author Mads Albertsen \email{MadsAlbertsen85@@gmail.com}
amp_venn <- function(data, group = NULL,cut_a = 0.1, cut_f = 80, text.size = 5, output = "plot"){
## Retrieve data
abund <- as.data.frame(otu_table(data)@.Data)
tax <- data.frame(tax_table(data)@.Data)
OTU <- rownames(tax_table(data))
sample <- suppressWarnings(as.data.frame(as.matrix(sample_data(data))))
## Test for number of groups
if (length(levels(sample[,group])) > 3){
stop(paste("A maximum of 3 levels are supported. The grouping viable contains:",
paste(levels(sample[,group]), collapse = ", ")))
}
## Select grouping variable
colnames(sample)[1] <- "SeqID"
if (!is.null(group)){
sample <- sample[,c("SeqID", group)]
colnames(sample)[2] <- "GRP"
} else {
sample <- data.frame(SeqID = sample[,1], GRP = "Core")
}
## Add OTU names to the abundance information
abund1 <- cbind.data.frame(abund, OTU)
## Melt the dataframe for subsequent processing
abund2 <- melt(abund1, id.var = "OTU", value.name= "Abundance", variable.name = "SeqID")
## Merge sample information with the abundance data
abund3 <- merge(abund2, sample, by = "SeqID")
## Add frequent abundant column
abund4 <- mutate(abund3,
Freq = ifelse(Abundance > cut_a, 1, 0))
## Evaluate if OTUs are part of the core
abund5 <- group_by(abund4, OTU, GRP) %>%
summarise(Abundance = mean(Abundance),
cFreq = sum(Freq)/n()*100,
Core = ifelse(sum(Freq)/n()*100 >= cut_f, 1, 0))
## Convert back into matrix format
a <- dcast(abund5, OTU~GRP, value.var = "Core")
################### PLOT #############################
## 1 group
if(ncol(a) == 2){
c_A <- subset(a, a[,2] == 1)
c_n <- subset(a, a[,2] == 0)
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(A = nrow(c_A), N = nrow(c_n)),
abund = round(c(A = a_A$Sum, N = a_n$Sum), 1))
## Plot
p <- ggplot(data.frame(), aes(x=0, y=0)) +
annotate("text", x=c(0, 0), y = c(0,-0.5),
label = c(paste(AD[1,1], "\n(", AD[1,2],")", sep = ""),
paste("Non-core: ", AD[2,1]," (", AD[2,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(0), y = 0.45, label = colnames(a)[2], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=00.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
## Generate lists of species in each group
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared))
res <- list(plot = p,
A = as.character(unique(c_A$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2] <- colnames(a)[2]
}
## 2 groups
if(ncol(a) == 3){
c_AB <- subset(a, a[,2] == 1 & a[,3] == 1)
c_A <- subset(a, a[,2] == 1 & a[,3] == 0)
c_B <- subset(a, a[,2] == 0 & a[,3] == 1)
c_n <- subset(a, a[,2] == 0 & a[,3] == 0)
a_AB <- subset(abund5, OTU %in% c_AB$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_B <- subset(abund5, OTU %in% c_B$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(A = nrow(c_A), AB = nrow(c_AB), B = nrow(c_B), N = nrow(c_n)),
abund = round(c(A = a_A$Sum, AB = a_AB$Sum, B = a_B$Sum, N = a_n$Sum), 1))
p <- ggplot(data.frame(), aes(x=c(-0.2,0.2), y=0)) +
annotate("text", x=c(-0.4, 0, 0.4, 0), y = c(0,0,0,-0.5),
label = c(paste(AD[1:3,1], "\n(", AD[1:3,2],")", sep = ""),
paste("Non-core: ", AD[4,1]," (", AD[4,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(-0.2, 0.2), y = 0.45, label = colnames(a)[2:3], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=-0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_B$OTU)), colnames(a)[3], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AB$OTU)), "Core", Shared))
res <- list(plot = p,
A = as.character(unique(c_A$OTU)),
B = as.character(unique(c_B$OTU)),
Core = as.character(unique(c_AB$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2:4] <- c(colnames(a)[2],
colnames(a)[3],
"Core")
}
## 3 groups
if(ncol(a) == 4){
c_ABC <- subset(a, a[,2] == 1 & a[,3] == 1 & a[,4] == 1)
c_AB <- subset(a, a[,2] == 1 & a[,3] == 1 & a[,4] == 0)
c_AC <- subset(a, a[,2] == 1 & a[,3] == 0 & a[,4] == 1)
c_BC <- subset(a, a[,2] == 0 & a[,3] == 1 & a[,4] == 1)
c_A <- subset(a, a[,2] == 1 & a[,3] == 0 & a[,4] == 0)
c_B <- subset(a, a[,2] == 0 & a[,3] == 1 & a[,4] == 0)
c_C <- subset(a, a[,2] == 0 & a[,3] == 0 & a[,4] == 1)
c_n <- subset(a, a[,2] == 0 & a[,3] == 0 & a[,4] == 0)
a_ABC <- subset(abund5, OTU %in% c_ABC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_AB <- subset(abund5, OTU %in% c_AB$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_AC <- subset(abund5, OTU %in% c_AC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_BC <- subset(abund5, OTU %in% c_BC$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_A <- subset(abund5, OTU %in% c_A$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_B <- subset(abund5, OTU %in% c_B$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_C <- subset(abund5, OTU %in% c_C$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
a_n <- subset(abund5, OTU %in% c_n$OTU) %>% group_by(OTU) %>%
summarise(Mean = mean(Abundance)) %>% as.data.frame() %>% summarise(Sum = sum(Mean))
AD <- data.frame(counts = c(ABC = nrow(c_ABC), AB = nrow(c_AB),AC = nrow(c_AC), BC = nrow(c_BC),
A = nrow(c_A), B = nrow(c_B), C = nrow(c_C), N = nrow(c_n)),
abund = round(c(ABC = a_ABC$Sum, AB = a_AB$Sum, AC = a_AC$Sum, BC = a_BC$Sum,
A = a_A$Sum, B = a_B$Sum, C = a_C$Sum, N = a_n$Sum), 1))
p <- ggplot(data.frame(), aes(x=c(-0.2,0.2), y=0)) +
annotate("text", x=c(0, 0, -0.25, 0.25, -0.4, 0.4, 0, 0.5), y = c(0.05, 0.4, -0.05, -0.05, 0.3, 0.3, -0.3, -0.6),
label = c(paste(AD[1:7,1], "\n(", AD[1:7,2],")", sep = ""),
paste("Non-core:\n", AD[8,1]," (", AD[8,2],")", sep = "")),
size = text.size) +
annotate("text", x=c(-0.2, 0.2, 0), y = c(0.65, 0.65, -0.65), label = colnames(a)[2:4], size = text.size) +
xlim(-0.65,0.65) +
ylim(-0.65,0.65) +
annotate("path",
x=0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=-0.2+0.4*cos(seq(0,2*pi,length.out=100)),
y=0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
annotate("path",
x=0+0.4*cos(seq(0,2*pi,length.out=100)),
y=-0.2+0.4*sin(seq(0,2*pi,length.out=100))) +
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
axis.text=element_blank(),
axis.title=element_blank(),
axis.ticks=element_blank(),
panel.border=element_blank(),
panel.background = element_blank(),
legend.key = element_blank(),
plot.margin = unit(c(0,0,0,0), "mm"))
ot <- cbind.data.frame(OTU = rownames(tax),tax, abund) %>%
mutate(Shared = "Non-core") %>%
mutate(Shared = ifelse(OTU %in% as.character(unique(c_ABC$OTU)), "Core", Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AB$OTU)), paste(colnames(a)[2], colnames(a)[3], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_AC$OTU)), paste(colnames(a)[2], colnames(a)[4], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_BC$OTU)), paste(colnames(a)[3], colnames(a)[4], sep = "_"), Shared),
Shared = ifelse(OTU %in% as.character(unique(c_A$OTU)), colnames(a)[2], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_B$OTU)), colnames(a)[3], Shared),
Shared = ifelse(OTU %in% as.character(unique(c_C$OTU)), colnames(a)[4], Shared))
res <- list(plot = p,
Core = as.character(unique(c_ABC$OTU)),
AB = as.character(unique(c_AB$OTU)),
AC = as.character(unique(c_AC$OTU)),
BC = as.character(unique(c_BC$OTU)),
A = as.character(unique(c_A$OTU)),
B = as.character(unique(c_B$OTU)),
C = as.character(unique(c_C$OTU)),
Noncore = as.character(unique(c_n$OTU)),
Otutable = ot)
names(res)[2:8] <- c("Core",
paste(colnames(a)[2], colnames(a)[3], sep = "_"),
paste(colnames(a)[2], colnames(a)[4], sep = "_"),
paste(colnames(a)[3], colnames(a)[4], sep = "_"),
colnames(a)[2],
colnames(a)[3],
colnames(a)[4]
)
}
## Export data
if(output == "complete"){ return(res) }
if(output == "plot"){ return(p) }
}
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