Mercurial > repos > iuc > volcanoplot

comparison test-data/out.rscript @ 11:5e08a1e22dbc draft default tip

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/volcanoplot commit 8031afb306afd728f682d754e9270dc22c64c61c
author iuc
date Wed, 29 Jan 2025 10:37:54 +0000
parents 99ace6c1ff57
children
comparison
equal deleted inserted replaced
10:99ace6c1ff57 11:5e08a1e22dbc
18 }) 18 })
19 19
20 20
21 # Import data ------------------------------------------------------------ 21 # Import data ------------------------------------------------------------
22 22
23 results <- read.delim('/private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmprh4qip75/files/d/2/2/dataset_d2255b46-f0f6-4900-8b9e-bd352e34f303.dat', header = TRUE) 23 results <- read.delim('/tmp/tmpl4o1f_bf/files/5/2/5/dataset_52538741-d085-42da-817b-263bd4f7cf98.dat', header = TRUE)
24 24
25 25
26 # Format data ------------------------------------------------------------ 26 # Format data ------------------------------------------------------------
27 27
28 # Create columns from the column numbers specified 28 # Create columns from the column numbers specified and use the existing category_symbol column for shapes
29 results <- results %>% mutate(fdr = .[[4]], 29 results <- results %>% mutate(
30 pvalue = .[[3]], 30 fdr = .[[4]],
31 logfc = .[[2]], 31 pvalue = .[[3]],
32 labels = .[[1]]) 32 logfc = .[[2]],
33 labels = .[[1]],
34 )
35
36 # Check if shape_col is provided
33 37
34 # Get names for legend 38 # Get names for legend
35 down <- unlist(strsplit('Down,Not Sig,Up', split = ","))[1] 39 down <- unlist(strsplit('Down,Not Sig,Up', split = ","))[1]
36 notsig <- unlist(strsplit('Down,Not Sig,Up', split = ","))[2] 40 notsig <- unlist(strsplit('Down,Not Sig,Up', split = ","))[2]
37 up <- unlist(strsplit('Down,Not Sig,Up', split = ","))[3] 41 up <- unlist(strsplit('Down,Not Sig,Up', split = ","))[3]
47 51
48 52
49 # Specify genes to label -------------------------------------------------- 53 # Specify genes to label --------------------------------------------------
50 54
51 # Import file with genes of interest 55 # Import file with genes of interest
52 labelfile <- read.delim('/private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmprh4qip75/files/5/e/5/dataset_5e5b8fb0-bf65-438e-9b5b-03a540d9aa5d.dat', header = TRUE) 56 labelfile <- read.delim('/tmp/tmpl4o1f_bf/files/5/d/4/dataset_5d401b02-f6af-4ed9-b853-992fd4a4d044.dat', header = TRUE)
53 57
54 # Label the genes of interest in results table 58 # Label the genes of interest in results table
55 results <- mutate(results, labels = ifelse(labels %in% labelfile[, 1], labels, "")) 59 results <- mutate(results, labels = ifelse(labels %in% labelfile[, 1], labels, ""))
56 60
57 61
59 # Create plot ------------------------------------------------------------- 63 # Create plot -------------------------------------------------------------
60 64
61 # Open file to save plot as PDF 65 # Open file to save plot as PDF
62 pdf("volcano_plot.pdf") 66 pdf("volcano_plot.pdf")
63 67
64 # Set up base plot 68 # Set up base plot with faceting by category_symbol instead of shapes
65 p <- ggplot(data = results, aes(x = logfc, y = -log10(pvalue))) + 69 p <- ggplot(data = results, aes(x = logfc, y = -log10(pvalue))) +
66 geom_point(aes(colour = sig)) +
67 scale_color_manual(values = colours) + 70 scale_color_manual(values = colours) +
68 theme(panel.grid.major = element_blank(), 71 theme(panel.grid.major = element_blank(),
69 panel.grid.minor = element_blank(), 72 panel.grid.minor = element_blank(),
70 panel.background = element_blank(), 73 panel.background = element_blank(),
71 axis.line = element_line(colour = "black"), 74 axis.line = element_line(colour = "black"),
72 legend.key = element_blank()) 75 legend.key = element_blank())
76
77 # Conditional logic to use either shape or facet based on user selection
78 p <- p + geom_point(aes(colour = sig)) #only add color
73 79
74 # Add gene labels 80 # Add gene labels
75 p <- p + geom_text_repel(data = filter(results, labels != ""), aes(label = labels), 81 p <- p + geom_text_repel(data = filter(results, labels != ""), aes(label = labels),
76 min.segment.length = 0, 82 min.segment.length = 0,
77 max.overlaps = Inf, 83 max.overlaps = Inf,