| Next changeset 1:fe8d4655ee10 (2019-02-11) |
|
Commit message:
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ggplot2 commit f9fb73a88ab8b52ce11c25a966d4fe99e67c9fbf |
|
added:
ggplot2_heatmap.xml macros.xml test-data/ggplot_heatmap2_result1.pdf test-data/ggplot_heatmap_result1.pdf test-data/ggplot_histogram_result1.pdf test-data/ggplot_pca_result1.pdf test-data/ggplot_point_result1.pdf test-data/ggplot_violin_result1.pdf test-data/mtcars.txt |
| b |
| 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 @@ +<tool id="ggplot2_heatmap" name="Heatmap w ggplot" version="@VERSION@"> + <macros> + <import>macros.xml</import> + </macros> + <requirements> + <requirement type="package" version="0.9.2">r-cowplot</requirement> + <requirement type="package" version="0.2.0">r-egg</requirement> + <requirement type="package" version="0.1_20">r-ggdendro</requirement> + <requirement type="package" version="0.7.4">r-dplyr</requirement> + <requirement type="package" version="1.4.3">r-reshape2</requirement> + <requirement type="package" version="1.2.1">r-svglite</requirement> + </requirements> + <command detect_errors="exit_code"><![CDATA[ +cat '$script' && +Rscript '$script' + ]]></command> + <configfiles> + <configfile name="script"><![CDATA[ +@R_INIT@ + +## Import library + +library(ggplot2) +library(cowplot) +library(egg) +library(dplyr) +library(ggdendro) +library(reshape2) + +input <- '$input1' +header <- ${inputdata.header} +rowname_index <- as.integer('$inputdata.row_names_index') + +transform <- '$adv.transform' + +## read table with or with out header or row_names +if(rowname_index > 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@ + ]]></configfile> + </configfiles> + <inputs> + <expand macro="read_complex_input"/> + <expand macro="title"/> + <!-- Advanced Options --> + <section name="adv" title="Advanced Options" expanded="false"> + <expand macro="transform" /> + <param name="cluster" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Enable data clustering" /> + <param name="colorscheme" type="select" label="Heatmap colorscheme" > + <option value="whrd" selected="true">White to red</option> + <option value="whblu">White to blue</option> + <option value="blwhre">Blue to white to red</option> + </param> + </section> + <!-- Output Options --> + <section name="out" title="Output Options" expanded="true"> + <expand macro="dimensions" /> + </section> + </inputs> + <outputs> + <expand macro="additional_output" /> + </outputs> + <tests> + <test> + <param name="input1" value="mtcars.txt" ftype="tabular"/> + <conditional name="inputdata"> + <param name="input_type" value="with_header_rownames"/> + <param name="header" value="TRUE"/> + <param name="row_names_index" value="1"/> + <param name="sample_name_orientation" value="TRUE"/> + </conditional> + <param name="transform" value="log10plus1"/> + <param name="cluster" value="true"/> + <param name="colorscheme" value="blwhre"/> + <param name="additional_output_format" value="pdf"/> + <output name="output2" file="ggplot_heatmap_result1.pdf" compare="sim_size"/> + </test> + </tests> + <help><![CDATA[ +This tool will generate a clustered heatmap of your data. More customization options will be added, for now the heatmap uses a red coloring scheme and clustering is performed using the "maximum" similarity measure and the "complete" hierarchical clustering measure. + +Input data should have row labels in the first column and column labels. For example, the row labels (the first column) should represent gene IDs and the column labels should represent sample IDs. + ]]></help> + <citations> + </citations> +</tool> |
| b |
| 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 |
| [ |
| b'@@ -0,0 +1,291 @@\n+<?xml version="1.0"?>\n+<macros>\n+ <xml name="requirements">\n+ <requirements>\n+ <requirement type="package" version="@VERSION@">r-ggplot2</requirement>\n+ <yield />\n+ </requirements>\n+ </xml>\n+ <token name="@VERSION@">2.2.1</token>\n+\n+ <token name="@R_INIT@"><![CDATA[\n+ ## Setup R error handling to go to stderr\n+ options(show.error.messages=F, error=function(){cat(geterrmessage(), file=stderr()); q("no",1,F)})\n+\n+ ## Unify locale settings\n+ loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")\n+ ]]></token>\n+\n+ <token name="@TRANSFORM@"><![CDATA[\n+ #if $adv.transform == "log2"\n+ input["value"] <- log2(input["value"])\n+ #elif $adv.transform == "log2plus1"\n+ input["value"] <- log2(input["value"]+1)\n+ #elif $adv.transform == "log10"\n+ input["value"] <- log10(input["value"])\n+ #elif $adv.transform == "log10plus1"\n+ input["value"] <- log10(input["value"]+1)\n+ #end if\n+ ]]></token>\n+\n+ <token name="@XY_SCALING@"><![CDATA[\n+ #Choose between automatically scaled x and y axis or user defined\n+ #if $adv.scaling.plot_scaling == "Automatic"\n+ gg_scalex = NULL\n+ gg_scaley = NULL\n+ #else\n+ gg_scalex = xlim($adv.scaling.xaxismin, $adv.scaling.xaxismax)\n+ gg_scaley = ylim($adv.scaling.yaxismin, $adv.scaling.yaxismax)\n+ cat("\\n xaxismin: ", $adv.scaling.xaxismin)\n+ cat("\\n xaxismax: ", $adv.scaling.xaxismax)\n+ cat("\\n yaxismin: ", $adv.scaling.yaxismin)\n+ cat("\\n yaxismax: ", $adv.scaling.yaxismax)\n+ #end if\n+ ]]></token>\n+\n+ <token name="@THEME@"><![CDATA[\n+ ## Choose theme for plot\n+ #if $adv.theme == "bw"\n+ gg_theme = theme_bw()\n+ #else\n+ gg_theme = NULL\n+ #end if\n+ ]]></token>\n+\n+ <token name="@LEGEND@"><![CDATA[\n+ ## Show/hide legend\n+ #if $adv.legend == "yes"\n+ gg_legend = theme(legend.position="right")\n+ #else\n+ gg_legend = theme(legend.position="none")\n+ cat("\\n no legend")\n+ #end if\n+ ]]></token>\n+ <token name="@SAVE_OUTPUT@"><![CDATA[\n+ ## output options need to be in out section\n+ gg_width <- as.double(\'$out.width_output_dim\')\n+ gg_height <- as.double(\'$out.height_output_dim\')\n+ gg_unit <- \'$out.unit_output_dim\'\n+ gg_dpi <- as.double(\'$out.dpi_output_dim\')\n+ gg_add_device <- \'$out.additional_output_format\'\n+ output1 <- \'$output1\'\n+ output2 <- \'$output2\'\n+\n+ ## ggsave to png\n+ ggsave(filename = output1, plot = plot_out, width = gg_width, height = gg_height, units = gg_unit, dpi = gg_dpi, device = "png")\n+ if(gg_add_device != "none"){\n+ ggsave(filename = output2, plot = plot_out, width = gg_width, height = gg_height, units = gg_unit, dpi = gg_dpi, device = gg_add_device)\n+ }\n+ ]]></token>\n+ <xml name="read_complex_input">\n+ <param name="input1" type="data" format="tabular" label="Select table"/>\n+ <conditional name="inputdata">\n+ <param name="input_type" type="select" label="Select input dataset options" help="specific dataset input for reading">\n+ <option value="with_header" selected="true">Dataset with header</option>\n+ <option value="with_rownames">Dataset with row names</option>\n+ <option value="with_header_rownames">Dataset with header and row names</option>\n+ <option value="no_header_rownames">Dataset without header or row names</option>\n+ </param>\n+ <when value="with_header">\n+ <param name="header" type="hidden" value="TRUE"/>\n+ <param name="row_names_index" type="hidden" value="0"/>\n+ <param name="sample_name_orientation" type="select" display="radio" multiple="'..b'ption>\n+ <option value="YlGn">Yellow to green (discrete, max=9 colors)</option>\n+ <option value="Reds">Shades of red from light to dark (discrete, max=9 colors)</option>\n+ <option value="RdPu">Red to purple (discrete, max=9 colors)</option>\n+ <option value="Purples">Shades of purple from light to dark (discrete, max=9 colors)</option>\n+ <option value="PuRd">Purple to red (discrete, max=9 colors)</option>\n+ <option value="PuBuGn">Purple to blue to green (discrete, max=9 colors)</option>\n+ <option value="PuBu">Purple to blue(discrete, max=9 colors)</option>\n+ <option value="OrRd">Orange to red (discrete, max=9 colors)</option>\n+ <option value="Oranges">Shades of orange from light to dark (discrete, max=9 colors)</option>\n+ <option value="Greys">Shades of grey from light to dark (discrete, max=9 colors)</option>\n+ <option value="Greens">Shades of greens from light to dark (discrete, max=9 colors)</option>\n+ <option value="GnBu">Green to blue (discrete, max=9 colors)</option>\n+ <option value="BuPu">Blue to purple (discrete, max=9 colors)</option>\n+ <option value="BuGn">Blue to green (discrete, max=9 colors)</option>\n+ <option value="Blues">Shades of blue from light to dark (discrete, max=9 colors)</option>\n+ <option value="Set1">Set 1 - predefined color pallete (discrete, max=9 colors)</option>\n+ <option value="Set2">Set 2 - predefined color pallete (discrete, max=8 colors)</option>\n+ <option value="Set3">Set 3 - predefined color pallete (discrete, max=12 colors)</option>\n+ <option value="Pastel1">Pastel 1 - predefined pastel color pallete (discrete, max=9 colors)</option>\n+ <option value="Pastel2">Pastel 2 - predefined pastel color pallete (discrete, max=8 colors)</option>\n+ <option value="Paired">Paired - predefined color pallete (discrete, max=12 colors)</option>\n+ <option value="Dark2">Dark 2 - predefined color pallete (discrete, max=12 colors)</option>\n+ <option value="Accent">Accent - predefined color pallete (discrete, max=12 colors)</option>\n+ <option value="Spectral">Spectral - Red to yellow to purple (discrete, max=11 colors)</option>\n+ <option value="RdYlGn">Red to yellow to green (discrete, max=11 colors)</option>\n+ <option value="RdYlBu">Red to yellow to blue (discrete, max=11 colors)</option>\n+ <option value="RdGy">Red to grey (discrete, max=11 colors)</option>\n+ <option value="RdBu">Red to blue (discrete, max=11 colors)</option>\n+ <option value="PuOr">Purple to orange (discrete, max=11 colors)</option>\n+ <option value="PRGn">Purple to green (discrete, max=11 colors)</option>\n+ <option value="BrBG">Brown to teal (discrete, max=11 colors)</option>\n+ </param>\n+ </xml>\n+ <xml name="additional_output">\n+ <data name="output1" format="png" label="${tool.name} on ${on_string}: png"/>\n+ <data format="pdf" name="output2" label="${tool.name} on ${on_string}: ${out.additional_output_format}">\n+ <change_format>\n+ <when input="out.additional_output_format" value="svg" format="svg" />\n+ <when input="out.additional_output_format" value="eps" format="eps" />\n+ <when input="out.additional_output_format" value="ps" format="ps" />\n+ <when input="out.additional_output_format" value="tex" format="txt" />\n+ <when input="out.additional_output_format" value="jpeg" format="jpg" />\n+ <when input="out.additional_output_format" value="tiff" format="tiff" />\n+ <when input="out.additional_output_format" value="bmp" format="bmp" />\n+ </change_format>\n+ <filter>out[\'additional_output_format\'] != "none"</filter>\n+ </data>\n+ </xml>\n+</macros>\n' |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_heatmap2_result1.pdf |
| b |
| Binary file test-data/ggplot_heatmap2_result1.pdf has changed |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_heatmap_result1.pdf |
| b |
| Binary file test-data/ggplot_heatmap_result1.pdf has changed |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_histogram_result1.pdf |
| b |
| Binary file test-data/ggplot_histogram_result1.pdf has changed |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_pca_result1.pdf |
| b |
| Binary file test-data/ggplot_pca_result1.pdf has changed |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_point_result1.pdf |
| b |
| Binary file test-data/ggplot_point_result1.pdf has changed |
| b |
| diff -r 000000000000 -r f44dc95928aa test-data/ggplot_violin_result1.pdf |
| b |
| Binary file test-data/ggplot_violin_result1.pdf has changed |
| b |
| 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 |
| b |
| @@ -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 |