bubble_plot_v2.R

library(ggplot2)
library(plyr)
library(dplyr)

#v2 to work on input format for 124SNPs old data

fishing <- fishing_counts_2016_v2

#choose snp to plot and get its name
d <- gts[c(1,81:83)]
d
id <- colnames(d)[2]
marker <- strsplit(id, "_")[[1]][1] 
marker

d <- rename(d, c("River_short" = "River"))
data <- merge(fishing, d, by = c("River_short"))
data$River_short <- gsub("LaD", "La_D", data$River_short)

tbl_df = data.frame()
#for global plot
#tbl_list = list()
#csvname = paste(marker, "_bubble.csv", sep="")
#write.table(tbl_list, file = csvname, 
            #col.names = NA, row.names = TRUE, sep = ",")
#to have empty column for row name
#plot_list = list() 
#empty

for (i in 1:nrow(data)) {
  row <- data[i,] #row by row
  row.names(row) <- as.character(row$River_short) 
  #remove levels attribute
  
  river <- as.character(row$River_short) 
  SW <- row$freq_2SW
  nd_1 <- colnames(row)[6]
  nd_2 <- colnames(row)[7]
  nd_3 <- colnames(row)[8]
  gt_1 <- pull(row[6])
  gt_2 <- pull(row[7])
  gt_3 <- pull(row[8])
  nd <- c(nd_1, nd_2, nd_3)
  genotype_frequency <- c(gt_1, gt_2, gt_3)
  frequency_2SW <- c(SW, SW, SW)
  
  #create output table
  #tbl <- select(.data = row, freq_2SW, 
  #                     nd_1, nd_2, nd_3)
  #tbl_list[[i]] = tbl
  #write.table(tbl, file = csvname, 
  #            append = TRUE,col.names = NA, row.names = TRUE,
  #            sep = ",")
  
  #create table for the plot
  input <- data.frame(nd, frequency_2SW, genotype_frequency)
  
  #global table for global plot
  tbl_df <- rbind(input, tbl_df)
  
  #bubble plot
  #plot <- ggplot(input, 
  #  aes(x = nd, y = freq_2SW, size = gt))+    
  #  geom_point()+
  #  ylim(0, 0.70)+
  #  scale_size_continuous(limits=c(0,1),
  #        breaks=c(0.05,0.25,0.5,0.75,1))+
  #  theme_minimal()+
  #  ggtitle(river)
  #plot_list[[i]] = plot
  
  #file_name = paste("bubble_plot_", river, ".png", sep="")
  #png(file_name)
  #print(plot_list[[i]])
  #dev.off()
}


glob_plot <- ggplot(tbl_df, aes(x = nd, 
                               y = frequency_2SW, 
                               size = genotype_frequency))+    
  geom_point(alpha = 0.3)+
  ylim(0, 0.70)+
  scale_size_continuous(limits=c(0,1),
                        breaks=c(0.05,0.25,0.5,0.75,1))+
  theme_minimal()

fname <- paste("bubble_plot_global_", marker, ".png", sep = "")
png(fname)
print(glob_plot)
dev.off()