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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$Description, levels = description_order) # Set the size for axis labels larger than the axis text axis_label_size <- 24 # Now, create the plot png("bubble_plot.png", width = 1000, height = 800) ggplot(mydat, aes(x = GeneRatio, y = Description)) + geom_point(aes(color = Category, size = Count, alpha = abs(log10(FDR)))) + scale_color_manual(values = c("Up-regulated" = "red", "Down-regulated" = "blue")) + scale_size_continuous(range = c(4, 10)) + labs(x = "GeneRatio", y = "Pathway name", color="Category", size="Count", alpha="-log10(FDR)") + theme( axis.text.x = element_text(angle = 20, vjust = 0.5, size = 20), axis.text.y = element_text(size = 20), axis.title.x = element_text(size = axis_label_size), axis.title.y = element_text(size = axis_label_size), legend.text = element_text(size = 20), legend.title = element_text(size = 20), plot.title = element_text(size = axis_label_size) ) + guides(color = guide_legend(override.aes = list(size = 10)), alpha = guide_legend(override.aes = list(size = 10))) dev.off()
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R code for bubbleplot2
library(readxl) library(ggplot2) library(dplyr) library(magrittr) library(tidyr) library(forcats) # Read data from an Excel file mydat <- read_excel("1457_M10_atlE_DEGs_all_pathway-2.xlsx") mydat$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()
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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
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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
Bubble plot for 1457∆atlE vs 1457-M10 vs 1457 vs mock
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