Producing such a plot in r
Hello
I have proportion of samples altered for a list of genes and related p-value like
CNV - log10_pvalue Percentage_altered
CDKN2B Deletion 3 69
CDKN2A Deletion 3 69
RPL22 Deletion 0.087568 33
GATA6 Amplifiction 2.974694135 44
EGFR Amplifiction 1.958607315 42
CCND1 Amplifiction 2.999132278 36
CDK6 Amplifiction 2.795880017 30
GATAD1 Amplifiction 2.795880017 30
KRAS Amplifiction 2.999132278 22
MYB Amplifiction 1.677780705 16
GATA4 Amplifiction 1.091514981 13
MYC Amplifiction 2.22184875 52
CCNE1 Amplifiction -0.000434077 0
TSHZ3 Amplifiction -0.000434077 0
ERBB2 Amplifiction -0.000434077 0
I want to visualise this data like below but I don't know how
Any help please?
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rpolicastro
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zizigolu
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zizigolu
1 answer
The example data.
df <- structure(list(gene = c("CDKN2B", "CDKN2A", "RPL22", "GATA6",
"EGFR", "CCND1", "CDK6", "GATAD1", "KRAS", "MYB", "GATA4", "MYC",
"CCNE1", "TSHZ3", "ERBB2"), CNV = c("Deletion", "Deletion", "Deletion",
"Amplifiction", "Amplifiction", "Amplifiction", "Amplifiction",
"Amplifiction", "Amplifiction", "Amplifiction", "Amplifiction",
"Amplifiction", "Amplifiction", "Amplifiction", "Amplifiction"
), log10_pvalue = c(3, 3, 0.087568, 2.974694135, 1.958607315,
2.999132278, 2.795880017, 2.795880017, 2.999132278, 1.677780705,
1.091514981, 2.22184875, -0.000434077, -0.000434077, -0.000434077
), Percentage_altered = c(69L, 69L, 33L, 44L, 42L, 36L, 30L,
30L, 22L, 16L, 13L, 52L, 0L, 0L, 0L)), class = "data.frame", row.names = c(NA,
-15L))
ggplot2 answer
library("tidyverse")
library("ggrepel")
df %>%
mutate(net_frequency=ifelse(CNV == "Deletion", -Percentage_altered/100, Percentage_altered/100)) %>%
ggplot(aes(x=log10_pvalue, y=net_frequency)) +
geom_point(aes(size=Percentage_altered, color=log10_pvalue)) +
geom_text_repel(aes(label=ifelse(log10_pvalue > -log10(0.05), gene, "")), force=10) +
geom_hline(yintercept=0, lty=2) +
theme_classic()
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rpolicastro
I edited the post to include the gene names for genes with a p-value < 0.05.
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rpolicastro
Sorry this is my full data
gene CNV -log10_pvalue Percentage_altered
CDKN2B Deletion 2.72E+01 69
CDKN2A Deletion 2.72E+01 69
RPL22 Deletion 1.057654569 36
GATA6 Amplification 4.22184875 42
EGFR Amplification 2 34
CCND1 Amplification 5.698970004 32
CDK6 Amplification 3.22184875 24
GATAD1 Amplification 3.22184875 24
KRAS Amplification 5.698970004 24
MYB Amplification 1.698970004 16
GATA4 Amplification 1.096910013 16
MYC Amplification 2.22184875 52
CCNE1 Amplification 0 0
TSHZ3 Amplification 0 0
ERBB2 Amplification 0 0
CCNE1, TSHZ3 and ERBB2 are all zero percent therefore I don't have any p-value for them so I put log10(1)=0 so on the plot I must see three bubbles on the 0 axis but I see only one bubble, please correct me if I am wrong here
I want to show gene cable for all if possible
If their p-value and percentage are the same the points will be exactly on top of each other.
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It seems to me that is a mix of inverted volcano plot and bubble plot. Two links that can help you to achieve the below as per my experience are below:
1.https://www.r-graph-gallery.com/320-the-basis-of-bubble-plot.html
2.https://www.bioconductor.org/packages/release/bioc/vignettes/EnhancedVolcano/inst/doc/EnhancedVolcano.html
You would definitely need to tweak the code. Is there a GitHub link present from the paper you are referring to? Maybe also digging into that might give some leads.
You are currently missing the variable they used in their y-axis.
Does not seem like so. The Y-axis here refers to the frequency of gain and deletion %, which in the OP query is the last column (Percentage_altered) if I understand correctly.
edit: I think the y axis and the point size are the same variable, but on the y-axis they functionally make the percentage negative for deletion and positive for gain.