gene_x 0 like s 496 view s
Tags: plot, R, RNA-seq
R code for bubbleplot
library(ggplot2)
library(dplyr)
library(readxl)
# Assuming you have already read the data with read_excel
mydat <- read_excel("Pathway_KEGG_1457_vs_mock_Top10.xlsx")
# Custom function to convert fraction to decimal
convert_fraction_to_decimal <- function(fraction) {
parts <- strsplit(as.character(fraction), "/")[[1]]
as.numeric(parts[1]) / as.numeric(parts[2])
}
mydat$GeneRatio <- sapply(mydat$Ratio, convert_fraction_to_decimal)
mydat$Description <- factor(mydat$Description, levels = unique(mydat$Description))
mydat$Category <- factor(mydat$Category, levels=c("Up-regulated","Down-regulated"))
description_order <- rev(c("TNF signaling pathway","Legionellosis","Cytokine-cytokine receptor interaction","Protein processing in endoplasmic reticulum","Toxoplasmosis","Fluid shear stress and atherosclerosis","Pathways in cancer","JAK-STAT signaling pathway","IL-17 signaling pathway","Influenza A","Transcriptional misregulation in cancer","Glycine serine and threonine metabolism","Antifolate resistance","Base excision repair","Metabolic pathways","Acute myeloid leukemia","Homologous recombination","Fanconi anemia pathway","Primary immunodeficiency","MAPK signaling pathway"))
mydat$Description <- factor(mydat$Description, levels = description_order)
# Set the size for axis labels larger than the axis text
axis_label_size <- 24
# Now, create the plot
png("bubble_plot.png", width = 1000, height = 800)
ggplot(mydat, aes(x = GeneRatio, y = Description)) +
geom_point(aes(color = Category, size = Count, alpha = abs(log10(FDR)))) +
scale_color_manual(values = c("Up-regulated" = "red", "Down-regulated" = "blue")) +
scale_size_continuous(range = c(4, 10)) +
labs(x = "GeneRatio", y = "Pathway name", color="Category", size="Count", alpha="-log10(FDR)") +
theme(
axis.text.x = element_text(angle = 20, vjust = 0.5, size = 20),
axis.text.y = element_text(size = 20),
axis.title.x = element_text(size = axis_label_size),
axis.title.y = element_text(size = axis_label_size),
legend.text = element_text(size = 20),
legend.title = element_text(size = 20),
plot.title = element_text(size = axis_label_size)
) +
guides(color = guide_legend(override.aes = list(size = 10)), alpha = guide_legend(override.aes = list(size = 10)))
dev.off()
R code for bubbleplot2
library(readxl)
library(ggplot2)
library(dplyr)
library(magrittr)
library(tidyr)
library(forcats)
# Read data from an Excel file
mydat <- read_excel("1457_M10_atlE_DEGs_all_pathway-2.xlsx")
mydat$Comparison <- factor(mydat$Comparison, levels=c("1457","1457-M10","1457∆atlE"))
description_order <- rev(c("Protein processing in endoplasmic reticulum","TNF signaling pathway","Legionellosis","Epstein-Barr virus infection","Toxoplasmosis","Osteoclast differentiation","Proteasome","Influenza A","Herpes simplex infection","HIF-1 signaling pathway","NOD-like receptor signaling pathway","Apoptosis","C-type lectin receptor signaling pathway","MAPK signaling pathway","Endocytosis","Neurotrophin signaling pathway","Ubiquitin mediated proteolysis","Pancreatic cancer"))
mydat$Description <- factor(mydat$Description, levels = description_order)
png("bubble_plot2.png", 1000, 800)
ggplot(mydat, aes(y = Description, x = Comparison)) +
geom_point(aes(color = p.adjust), size = 10) + # Set fixed size for points
labs(x = "", y = "", alpha="-log10(p.adjust)") +
theme(axis.text.x = element_text(angle = 20, vjust = 0.5)) +
theme(axis.text = element_text(size = 20)) +
theme(legend.text = element_text(size = 20)) +
theme(legend.title = element_text(size = 20)) +
guides(size = "none") # Turn off size in legend
dev.off()
Input Excel for bubbleplot
Description Size Expect Ratio P Value FDR Category Count
TNF signaling pathway 110 93/373 42/839 2.22E-12 7.24E-10 Up-regulated 42
Legionellosis 55 46/686 55/691 2.9E-10 4.72E-08 Up-regulated 55
Cytokine-cytokine receptor interaction 294 24/956 26/046 1.95E-09 2.12E-07 Up-regulated 26
Protein processing in endoplasmic reticulum 165 14/006 30/701 1.01E-07 8.27E-06 Up-regulated 30
Toxoplasmosis 113 95/919 35/447 2.2E-07 1.43E-05 Up-regulated 35
Fluid shear stress and atherosclerosis 139 11/799 31/359 1.52E-06 8.26E-05 Up-regulated 31
Pathways in cancer 526 44/649 19/037 1.92E-05 0.000896 Up-regualted 19
JAK-STAT signaling pathway 162 13/751 27/634 4.35E-05 0.00177 Up-regulated 27
IL-17 signaling pathway 93 78/942 32/935 0.000285 1.0327E-06 Up-regulated 32
Influenza A 171 14/515 25/491 0.000687 2.241E-06 Up-regulated 25
Transcriptional misregulation in cancer 186 83/425 23/974 0.0002368 0.038559 Down-regulated 23
Glycine serine and threonine metabolism 40 17/941 44/591 0.00032864 0.038559 Down-regulated 44
Antifolate resistance 31 13/904 50/345 0.00035484 0.038559 Down-regulated 50
Base excision repair 33 14/801 47/294 0.00053358 0.043487 Down-regulated 47
Metabolic pathways 1305 58/532 12/984 0.0075183 0.40292 Down-regulated 12
Acute myeloid leukemia 66 29/602 27/025 0.008932 0.40292 Down-regulated 27
Homologous recombination 41 18/389 32/628 0.0092737 0.40292 Down-regulated 32
Fanconi anemia pathway 54 24/220 28/902 0.0098875 0.40292 Down-regulated 28
Primary immunodeficiency 37 16/595 30/129 0.023604 0.77755 Down-regulated 30
MAPK signaling pathway 295 13/231 15/871 0.023851 0.77755 Down-regulated 15
Input Excel for bubbleplot2
Comparison Description p.adjust
1457 Protein processing in endoplasmic reticulum 6.7681E-08
1457-M10 Protein processing in endoplasmic reticulum 4.6253E-06
1457∆atlE Protein processing in endoplasmic reticulum 2.0787E-05
1457 TNF signaling pathway 2.6941E-05
1457-M10 TNF signaling pathway 4.5734E-06
1457∆atlE TNF signaling pathway 3.3099E-06
1457 Legionellosis 0.0062434
1457-M10 Legionellosis 4.6253E-06
1457∆atlE Legionellosis 0.0073192
1457 Epstein-Barr virus infection 0.0062434
1457-M10 Epstein-Barr virus infection 1.6635E-06
1457∆atlE Epstein-Barr virus infection 0.00049454
1457 Toxoplasmosis 0.0064469
1457 Osteoclast differentiation 4.6509E-06
1457-M10 Osteoclast differentiation 2.6616E-05
1457 Proteasome 1.0391E-05
1457 Influenza A 1.4677E-05
1457 Herpes simplex infection 1.5915E-05
1457∆atlE Herpes simplex infection 1.857E-06
1457 HIF-1 signaling pathway 1.6873E-05
1457-M10 NOD-like receptor signaling pathway 2.22E-06
1457∆atlE NOD-like receptor signaling pathway 0.0096378
1457-M10 Apoptosis 9.54E-06
1457-M10 C-type lectin receptor signaling pathway 1.37E-05
1457-M10 MAPK signaling pathway 5.3439E-05
1457-M10 Endocytosis 5.49E-05
1457∆atlE Endocytosis 1.857E-06
1457∆atlE Neurotrophin signaling pathway 0.00049454
1457∆atlE Ubiquitin mediated proteolysis 0.0088734
1457∆atlE Pancreatic cancer 1.857E-06
点赞本文的读者
还没有人对此文章表态
没有评论
GSVA-plot for carotis RNA-seq data
RNA-seq skin organoids on GRCh38+chrHsv1 (final)
© 2023 XGenes.com Impressum