Mercurial > repos > iuc > ggplot2_heatmap2

comparison heatmap2.xml @ 6:0a2a2e19bf2d draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/heatmap2 commit 4f9970932fa3521656d5618582ba5df4173ca66c"
author iuc
date Wed, 13 Apr 2022 09:33:56 +0000
parents f4899d509faa
children 76b642b4638c
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5:f4899d509faa 6:0a2a2e19bf2d
1 <tool id="ggplot2_heatmap2" name="heatmap2" version="@VERSION@"> 1 <tool id="ggplot2_heatmap2" name="heatmap2" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@">
2 <macros> 2 <macros>
3 <token name="@VERSION@">3.1.1</token> 3 <token name="@TOOL_VERSION@">3.1.1</token>
4 <token name="@VERSION_SUFFIX@">1</token>
4 </macros> 5 </macros>
5 <requirements> 6 <requirements>
6 <requirement type="package" version="@VERSION@">r-gplots</requirement> 7 <requirement type="package" version="@TOOL_VERSION@">r-gplots</requirement>
7 <requirement type="package" version="1.1_3">r-rcolorbrewer</requirement> 8 <requirement type="package" version="1.1_3">r-rcolorbrewer</requirement>
8 </requirements> 9 </requirements>
9 <command detect_errors="exit_code"><![CDATA[ 10 <command detect_errors="exit_code"><![CDATA[
10 cat '$script' && 11 cat '$script' &&
11 Rscript '$script' 12 Rscript '$script'
39 linput <- log10(mat_input+1) 40 linput <- log10(mat_input+1)
40 #end if 41 #end if
41 42
42 #if $zscore_cond.zscore == "rows": 43 #if $zscore_cond.zscore == "rows":
43 linput <- t(apply(linput, 1, scale)) 44 linput <- t(apply(linput, 1, scale))
44 colnames(linput) <- colnames(input) 45 colnames(linput) <- colnames(input)[2:ncol(input)]
45 rownames(linput) <- input[,1] 46 rownames(linput) <- input[,1]
46 scale <- "none" 47 scale <- "none"
47 #elif $zscore_cond.zscore == "cols": 48 #elif $zscore_cond.zscore == "cols":
48 linput <- apply(linput, 2, scale) 49 linput <- apply(linput, 2, scale)
49 rownames(linput) <- input[,1] 50 rownames(linput) <- input[,1]
276 <param name="cluster" value="yes"/> 277 <param name="cluster" value="yes"/>
277 <param name="distance" value="pearson_correlation"/> 278 <param name="distance" value="pearson_correlation"/>
278 <param name="type" value="two"/> 279 <param name="type" value="two"/>
279 <output name="output1" file="result1pearson.pdf" compare="sim_size"/> 280 <output name="output1" file="result1pearson.pdf" compare="sim_size"/>
280 </test> 281 </test>
282 <test>
283 <param name="input1" value="mtcars.txt"/>
284 <param name="zscore" value="rows"/>
285 <param name="type" value="three"/>
286 <param name="image_file_format" value="png"/>
287 <output name="output1" file="result4.png" compare="sim_size"/>
288 </test>
289 <test>
290 <param name="input1" value="mtcars.txt"/>
291 <param name="cluster" value="yes"/>
292 <param name="distance" value="pearson_correlation"/>
293 <param name="scale" value="row"/>
294 <param name="type" value="three"/>
295 <param name="image_file_format" value="png"/>
296 <output name="output1" file="result5.png" compare="sim_size"/>
297 </test>
298 <test>
299 <param name="input1" value="mtcars.txt"/>
300 <param name="cluster" value="yes"/>
301 <param name="distance" value="spearmann_correlation"/>
302 <param name="scale" value="column"/>
303 <param name="type" value="three"/>
304 <param name="image_file_format" value="png"/>
305 <output name="output1" file="result6.png" compare="sim_size"/>
306 </test>
281 </tests> 307 </tests>
282 <help><![CDATA[ 308 <help><![CDATA[
283 This tool employs the heatmap.2 function from the R gplots package and will generate a heatmap of your data. If clustering is enabled, the heatmap uses the Euclidean distance method and the Complete hierarchical clustering method by default. 309 This tool employs the heatmap.2 function from the R gplots package and will generate a heatmap of your data. If clustering is enabled, the heatmap uses the Euclidean distance method and the Complete hierarchical clustering method by default.
284 310
285 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. 311 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.