# HG changeset patch
# User iuc
# Date 1528747491 14400
# Node ID f44dc95928aadac9aac95b0d9dbb8c4de496489b
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf
diff -r 000000000000 -r f44dc95928aa ggplot2_heatmap.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/ggplot2_heatmap.xml Mon Jun 11 16:04:51 2018 -0400
@@ -0,0 +1,182 @@
+
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+ macros.xml
+
+
+ r-cowplot
+ r-egg
+ r-ggdendro
+ r-dplyr
+ r-reshape2
+ r-svglite
+
+
+
+ 0){
+ df <- read.table(input, header = header, row.names = rowname_index, sep = "\t")
+}else{
+ df <- read.table(input, header = header, sep = "\t")
+}
+
+hclust_fun = function(x) hclust(x, method="complete")
+dist_fun = function(x) dist(x, method="maximum")
+distfun=dist_fun
+hclustfun=hclust_fun
+
+plot_mat <- df
+
+## transform dataset
+if(transform == "log2"){
+ plot_mat <- log2(plot_mat)
+ cat("\n ", transform, " transformed")
+}else if(transform == "log2plus1"){
+ plot_mat <- log2(plot_mat+1)
+ cat("\n ", transform, " transformed")
+}else if(transform == "log10"){
+ plot_mat <- log10(plot_mat)
+ cat("\n ", transform, " transformed")
+}else if(transform == "log10plus1"){
+ plot_mat <- log10(plot_mat+1)
+ cat("\n ", transform, " transformed")
+}else{
+ plot_mat <- plot_mat
+}
+
+#if $adv.colorscheme == "whrd"
+ colorscale = scale_fill_gradient(low="white", high="red", guide="colorbar")
+#elif $adv.colorscheme == "whblu"
+ colorscale = scale_fill_gradient(low="white", high="blue", guide="colorbar")
+#elif $adv.colorscheme == "blwhre"
+ colorscale = scale_fill_gradient2(low="blue", mid="white", high="red", guide="colorbar")
+#end if
+
+plot_mat["rows"] <- row.names(plot_mat)
+plot_mat.melt <- melt(plot_mat, id.vars = "rows")
+names(plot_mat.melt)[2] <- "cols"
+
+#if $adv.cluster:
+
+plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = subset(plot_mat, select = -rows))))
+
+plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
+
+gg_rows = ggdendrogram(data = plot_mat.dendo, rotate = FALSE) +
+ theme(axis.text.y = element_text(size = 6), axis.text.x = element_blank())
+
+plot_mat.melt[,"rows"] <- factor(x = plot_mat.melt[,"rows"],
+ levels = unique(plot_mat.melt[,"rows"])[plot_mat.dendo.order],
+ ordered = TRUE)
+
+plot_mat.dendo <- as.dendrogram(hclust(d = dist(x = t(subset(plot_mat, select = -rows)))))
+plot_mat.dendo.order <- order.dendrogram(plot_mat.dendo)
+
+gg_cols = ggdendrogram(data = plot_mat.dendo, rotate = TRUE) +
+ theme(axis.text.x = element_text(size = 6), axis.text.y = element_blank())
+
+plot_mat.melt[,"cols"] <- factor(x = plot_mat.melt[,"cols"],
+ levels = unique(plot_mat.melt[,"cols"])[plot_mat.dendo.order],
+ ordered = TRUE)
+
+## plot the heatmap
+gg_hm = plot_mat.melt %>%
+ ggplot(aes(x = rows, y = cols, fill = value)) +
+ geom_tile() +
+ theme(legend.position = "bottom", axis.title.x = element_blank(), axis.title.y = element_blank(),
+ axis.text.x = element_text(angle = 90, hjust = 1)) +
+ colorscale
+
+gg_empty = plot_mat.melt %>%
+ ggplot(aes(x = cols, y = value)) +
+ geom_blank() +
+ theme(axis.text = element_blank(),
+ axis.title = element_blank(),
+ line = element_blank(),
+ panel.background = element_blank())
+
+plot_out <- ggarrange(
+ gg_rows, gg_empty, gg_hm, gg_cols,
+ nrow = 2, ncol = 2, widths = c(3, 1), heights = c(1, 3), newpage =F)
+
+#else
+
+## plot the heatmap
+gg_hm = plot_mat.melt %>%
+ ggplot(aes(x = rows, y = cols, fill = value)) +
+ geom_tile() + ggtitle('$title') +
+ theme(legend.position = "bottom", axis.title.x = element_blank(), axis.title.y = element_blank(), axis.text.x = element_text(angle = 90, hjust = 1)) +
+ colorscale
+
+plot_out <- gg_hm
+
+#end if
+
+@SAVE_OUTPUT@
+ ]]>
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diff -r 000000000000 -r f44dc95928aa macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml Mon Jun 11 16:04:51 2018 -0400
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+ r-ggplot2
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+ 2.2.1
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+ @book{wickham2009ggplot2,
+ author = {Hadley Wickham},
+ title = {ggplot2: Elegant Graphics for Data Analysis},
+ publisher = {Springer-Verlag New York},
+ year = {2009},
+ isbn = {978-0-387-98140-6},
+ url = {http://ggplot2.org},
+ }
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+ out['additional_output_format'] != "none"
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_heatmap2_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_heatmap_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_histogram_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_pca_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_point_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/ggplot_violin_result1.pdf
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diff -r 000000000000 -r f44dc95928aa test-data/mtcars.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mtcars.txt Mon Jun 11 16:04:51 2018 -0400
@@ -0,0 +1,33 @@
+brand mpg cyl disp hp drat wt qsec vs am gear carb
+Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4
+Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4
+Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1
+Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
+Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2
+Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1
+Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4
+Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2
+Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2
+Merc 280 19.2 6 167.6 123 3.92 3.44 18.3 1 0 4 4
+Merc 280C 17.8 6 167.6 123 3.92 3.44 18.9 1 0 4 4
+Merc 450SE 16.4 8 275.8 180 3.07 4.07 17.4 0 0 3 3
+Merc 450SL 17.3 8 275.8 180 3.07 3.73 17.6 0 0 3 3
+Merc 450SLC 15.2 8 275.8 180 3.07 3.78 18 0 0 3 3
+Cadillac Fleetwood 10.4 8 472 205 2.93 5.25 17.98 0 0 3 4
+Lincoln Continental 10.4 8 460 215 3 5.424 17.82 0 0 3 4
+Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4
+Fiat 128 32.4 4 78.7 66 4.08 2.2 19.47 1 1 4 1
+Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
+Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.9 1 1 4 1
+Toyota Corona 21.5 4 120.1 97 3.7 2.465 20.01 1 0 3 1
+Dodge Challenger 15.5 8 318 150 2.76 3.52 16.87 0 0 3 2
+AMC Javelin 15.2 8 304 150 3.15 3.435 17.3 0 0 3 2
+Camaro Z28 13.3 8 350 245 3.73 3.84 15.41 0 0 3 4
+Pontiac Firebird 19.2 8 400 175 3.08 3.845 17.05 0 0 3 2
+Fiat X1-9 27.3 4 79 66 4.08 1.935 18.9 1 1 4 1
+Porsche 914-2 26 4 120.3 91 4.43 2.14 16.7 0 1 5 2
+Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.9 1 1 5 2
+Ford Pantera L 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
+Ferrari Dino 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
+Maserati Bora 15 8 301 335 3.54 3.57 14.6 0 1 5 8
+Volvo 142E 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2