Hello All, How can I cluster different GO_categories so that it does not look scattered as in my case?
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7 weeks ago

The data frame is provided as an image:DataFrame

My R code is:

Bubble_plot_5 <- read_excel("GO_Bubble_plot.xlsx", sheet = "GO_5")
 view(Bubble_plot_5)

 ggplot(Bubble_plot_5, aes(y = reorder(GO_Term, as.numeric(GO_Category)), x = Gene_Count,
                              size = Gene_Count))+
      geom_point(aes(color = GO_Category), alpha = 3.0)+
      geom_tile(aes(width = Inf, fill = GO_Category), alpha = 0.4)+
      scale_fill_manual(values = c("green", "red", "blue"))

Bubbleplot

R Gene ggplot2 ontology. • 896 views
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Pro-tip: Rather than providing images of data just use dput() on the data.frame and copy/paste the output. Also, please remove "hello" from the title, this does not belong there.

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Thank you for the suggestion. I will see to it next time. The dput() output is as follows:

structure(list(GO_Term = c("Translation", "Signal transduction", "Regulation of transcription, DNA-templated", "Regulation of cell shape", "Phosphorelay signal transduction system", "Peptidoglycan biosynthetic process", "Mo-molybdopterin cofactor biosynthetic process", "Methylation", "Intracellular protein transmembrane transport", "Fatty acid biosynthetic process", "Electron transport chain", "Chemotaxis", "Cell wall organization", "Cell division", "Carbohydrate metabolic process", "Bacterial-type flagellum dependent cell motility", "Plasma membrane", "Integral component of membrane", "Extracellular region", "Cytoplasm", "Bacterial-type flagellum basal body", "ATP-binding cassette (ABC) transporter complex", "Zinc ion binding", "Transmembrane transporter activity", "rRNA binding", "Phosphorelay sensor kinase activity", "Oxidoreductase activity", "Methyltransferase activity", "Metalloendopeptidase activity", "Metal ion Binding", "Iron-sulfur cluster binding", "Hydrolase activity ", "Heme binding", "Electron transfer activity", "ATPase-coupled transmembrane transporter activity", "ATPase-coupled cation transmembrane transporter activity", "ATP binding", "4 iron, 4 sulfur cluster binding"), Gene Count = c(27, 18, 34, 4, 29, 5, 3, 10, 1, 5, 2, 19, 8, 5, 12, 16, 107, 212, 5, 77, 16, 15, 18, 22, 18, 16, 18, 6, 5, 97, 18, 54, 12, 14, 25, 2, 114, 28), GO Category = c("BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "CC", "CC", "CC", "CC", "CC", "CC", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF" )), row.names = c(NA, -38L), class = c("tbl_df", "tbl", "data.frame" ))

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Just rearrange the terms in the excel file in descending or ascending order and then read the file.

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Could you show us the rest of your code please? (Including libraries.) There isn't anything inherently wrong with the code snippet here, and executing it on some dummy data produces a properly "grouped" plot.

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I have provided the full table as dput() in a reply above. The complete code (including libraries) is as follows:

library(ggplot2)
library(forcats)
library(magrittr)
library(tidyverse)
library(readxl)
library("gplots")
library(writexl)
library(dplyr)
library(tidyr)
library(ggplot2)


Bubble_plot_5 <- read_excel("GO_Bubble_plot.xlsx", sheet = "GO_5")
view(Bubble_plot_5)

ggplot(Bubble_plot_5, aes(y = reorder(GO_Term, as.numeric(`GO Category`)), x = `Gene Count`,
                          size = `Gene Count`))+
  geom_point(aes(color = `GO Category`), alpha = 3.0)+
  geom_tile(aes(width = Inf, fill = `GO Category`), alpha = 0.4)+
  scale_fill_manual(values = c("darkcyan", "darkseagreen1", "lightgoldenrod"))+
  theme(panel.background = element_blank())+
  xlab("Gene Count")+
  ylab("GO Term")+
  theme(axis.line.x = element_line(color="black", size = 0.5),
        axis.line.y = element_line(color="black", size = 0.5),
        axis.text.y = element_text(angle = 0, size = 15),
        axis.text.x = element_text(angle = 0, size = 15),
        axis.title=element_text(size=14,face="bold"),
        legend.text=element_text(size=12),
        legend.title = element_text(size=14))

ggsave("GO5Bubbleplot.png", width = 10, height = 8, dpi = 400, limitsize = FALSE)
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Thank you, really appreciate it. So the problem was with the GO_Term column not getting re-leveled. That old code of mine here is clunky. Sorry about that.

Here's how you could do this now (see code snippet below). Please note that I renamed the input data in your columns to avoid having to use backticks while referencing them (so I replaced the whitespaces with underscores).

I tested it on my R installation (version 4.1.1) and it worked properly. Let me know if this works for you also.

#OP's data.
Bubble_plot_5 <- structure(list(GO_Term = c("Translation", "Signal transduction", "Regulation of transcription, DNA-templated", "Regulation of cell shape", 
                                            "Phosphorelay signal transduction system", "Peptidoglycan biosynthetic process", 
                                            "Mo-molybdopterin cofactor biosynthetic process", "Methylation", "Intracellular protein transmembrane transport", 
                                            "Fatty acid biosynthetic process", "Electron transport chain", "Chemotaxis", "Cell wall organization", 
                                            "Cell division", "Carbohydrate metabolic process", "Bacterial-type flagellum dependent cell motility", 
                                            "Plasma membrane", "Integral component of membrane", "Extracellular region", "Cytoplasm", 
                                            "Bacterial-type flagellum basal body", "ATP-binding cassette (ABC) transporter complex", "Zinc ion binding", 
                                            "Transmembrane transporter activity", "rRNA binding", "Phosphorelay sensor kinase activity", 
                                            "Oxidoreductase activity", "Methyltransferase activity", "Metalloendopeptidase activity", "Metal ion Binding", 
                                            "Iron-sulfur cluster binding", "Hydrolase activity ", "Heme binding", "Electron transfer activity", 
                                            "ATPase-coupled transmembrane transporter activity", "ATPase-coupled cation transmembrane transporter activity", 
                                            "ATP binding", "4 iron, 4 sulfur cluster binding"), 
                                Gene_Count = c(27, 18, 34, 4, 29, 5, 3, 10, 1, 5, 2, 19, 8, 5, 12, 16, 107, 212, 5, 77, 16, 15, 18, 22, 18, 16, 18, 6, 5, 97, 18, 54, 12, 14, 25, 2, 114, 28), 
                                GO_Category = c("BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "BP", "CC", "CC", "CC", "CC", "CC", "CC", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF", "MF" )),
                           row.names = c(NA, -38L), class = c("tbl_df", "tbl", "data.frame" ))



#Libraries.

#Data translocation.
library(readxl)
library(writexl)

#Plotting
library(ggplot2)
library(gplots)

#Data munging.
library(forcats)
library(magrittr)
library(tidyr)
library(dplyr)


#Bubble_plot_5 <- read_excel("GO_Bubble_plot.xlsx", sheet = "GO_5")
#view(Bubble_plot_5)


#Grouping by GO_Category, 
#arranging GO_Term column in ascending order alphabetically
#and reordering that column as is.
Bubble_plot_5 %<>%
  group_by(GO_Category) %>%
  arrange(GO_Term, .by_group = TRUE) %>%
  ungroup() %>%
  mutate(GO_Term = forcats::fct_reorder(GO_Term, GO_Category))

#Plotting.
ggplot(Bubble_plot_5, mapping = aes(x = Gene_Count, 
                                    y = GO_Term, 
                                    size = Gene_Count)) + 
  geom_tile(mapping = aes(width = Inf, y = GO_Term, fill = GO_Category), alpha = 0.2) + 
  geom_point(mapping = aes(color = GO_Category), alpha = 4.0) + 
  scale_fill_manual(values = c("darkcyan", "darkseagreen1", "lightgoldenrod")) +
  scale_color_manual(values = c("darkcyan", "darkseagreen1", "lightgoldenrod")) +
  theme(panel.background = element_blank()) +
  xlab("Gene Count") +
  ylab("GO Term") +
  theme(axis.line.x = element_line(color = "black", size = 0.5),
        axis.line.y = element_line(color = "black", size = 0.5),
        axis.text.y = element_text(angle = 0, size = 15),
        axis.text.x = element_text(angle = 0, size = 15),
        axis.title = element_text(size = 14, face = "bold"),
        legend.text = element_text(size = 12),
        legend.title = element_text(size = 14))
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Thank you so much Dunois . It works completely fine now.

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