Mercurial > repos > vandelj > giant_hierarchical_clustering

changeset 3:dd0f4da5f68f draft

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Uploaded
author vandelj
date Tue, 15 Sep 2020 15:54:23 +0000
parents ccca6ad98f78
children d75a74a93587
files galaxy/wrappers/ExprHeatmapClustering.xml
diffstat 1 files changed, 6 insertions(+), 3 deletions(-) [+]
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line diff
--- a/galaxy/wrappers/ExprHeatmapClustering.xml	Mon Sep 14 13:17:45 2020 +0000
+++ b/galaxy/wrappers/ExprHeatmapClustering.xml	Tue Sep 15 15:54:23 2020 +0000
@@ -1,4 +1,4 @@
-<tool name="GIANT-Heatmap and Hierarchical clustering" id="giant_hierarchical_clustering" version="0.5.2">
+<tool name="GIANT-Heatmap and Hierarchical clustering" id="giant_hierarchical_clustering" version="0.5.3">
   <description>Run hierarchical clustering and plot heatmap from expression data and/or differential expression analysis</description>
   <requirements>
     <requirement type="package" version="4.8.0">r-plotly</requirement>
@@ -619,13 +619,16 @@
       <option value="log2">Base 2 Logarithm</option>
     </param>
 
-    <param name="distanceMeasure" type="select" label="Distance measure used for clustering" help="See documentation of 'Dist' R package for more information">
+    <param name="distanceMeasure" type="select" label="Distance measure used for clustering">
       <option value="euclidean" selected="true">euclidean</option>
       <option value="manhattan">manhattan</option>
       <option value="binary">binary</option>
       <option value="pearson">pearson</option>
       <option value="spearman">spearman</option>
       <option value="kendall">kendall</option>
+      <option value="absPearson">absolute pearson</option>
+      <option value="absSpearman">absolute spearman</option>
+      <option value="absKendall">absolute kendall</option>
     </param>
 
     <param name="aggloMethod" type="select" label="Agglomeration method used for clustering" help="See documentation of 'hclust' R method for more information">
@@ -879,7 +882,7 @@
 
 \- **Mathematical transformation** can be applied to clustered data before clustering and visualization. Data used for the filtering step are not modified by this transformation.
 
-\- **Distance measure** used to cluster rows and columns.
+\- **Distance measure** used to cluster rows and columns. For "euclidean", "manhattan" and "binary" distances the 'dist' R function is directly called, for "pearson", "spearman" and "kendall" distances the '(1-correlation)/2' term is used  as a classical distance, for "absPearson", "absSpearman" and "absKendall" the 'abs(1-correlation)'' term is used.
 
 \- **Agglomeration method** used to cluster rows and columns.