changeset 3:e327fe59be69 draft default tip

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/schicexplorer commit c535679b4086f5bd1a75e9765b8708bf1bd2d81b

--- a/macros.xml	Fri Apr 14 14:18:56 2023 +0000
+++ b/macros.xml	Thu Jul 31 16:53:51 2025 +0000
@@ -3,6 +3,12 @@
     <token name="@TOOL_VERSION@">4</token>
     <token name="@PROFILE@">22.05</token>
 
+    <xml name="xrefs">
+        <xrefs>
+            <xref type="bio.tools">hicexplorer</xref>
+        </xrefs>
+    </xml>
+
      <xml name="requirements">
         <requirements>
             <requirement type="package" version="@TOOL_VERSION@">schicexplorer</requirement>
@@ -173,4 +179,4 @@
             <option value="plasma_r">plasma reversed</option>
         </param>
     </xml>
-</macros>
\ No newline at end of file
+</macros>

--- a/scHicClusterSVL.xml	Fri Apr 14 14:18:56 2023 +0000
+++ b/scHicClusterSVL.xml	Thu Jul 31 16:53:51 2025 +0000
@@ -4,6 +4,7 @@
         <token name="@BINARY@">scHicClusterSVL</token>
         <import>macros.xml</import>
     </macros>
+    <expand macro="xrefs"/>
     <expand macro="requirements" />
     <command detect_errors="exit_code"><![CDATA[
         @BINARY@
@@ -26,16 +27,16 @@
         --threads @THREADS@
     ]]></command>
     <inputs>
-        
+
         <expand macro="matrix_scooler_macro"/>
         <param name="clusterMethod_selector" type="select" label="Cluster method:">
                 <option value="kmeans" selected="True">K-means</option>
                 <option value="spectral" >Spectral clustering</option>
         </param>
 
-        <param name="numberOfClusters" type="integer" value="7"  label="Number of clusters" help='How many clusters should be computed by kmeans or spectral clustering' />   
-        <param name="distanceShortRange" type="integer" value="2000000"  label="Distance short range" help='Distance for the short range to compute the ratio of sum (short range interactions) / sum (long range interactions)' />   
-        <param name="distanceLongRange" type="integer" value="12000000"  label="Distance long range" help='Distance for the long range to compute the ratio of sum (short range interactions) / sum (long range interactions)' />   
+        <param name="numberOfClusters" type="integer" value="7"  label="Number of clusters" help='How many clusters should be computed by kmeans or spectral clustering' />
+        <param name="distanceShortRange" type="integer" value="2000000"  label="Distance short range" help='Distance for the short range to compute the ratio of sum (short range interactions) / sum (long range interactions)' />
+        <param name="distanceLongRange" type="integer" value="12000000"  label="Distance long range" help='Distance for the long range to compute the ratio of sum (short range interactions) / sum (long range interactions)' />
 
         <param name='chromosomes' type='text' label='List of chromosomes to consider' help='Please separate the chromosomes by space'/>
     </inputs>
@@ -62,16 +63,16 @@
 
             <output name="outFileName" file="scHicClusterSVL/cluster_spectral.txt" ftype="txt" compare="sim_size" delta="4000"/>
         </test>
-   
+
     </tests>
     <help><![CDATA[
 
 Clustering with dimension reduction via short vs long range ratio
 =================================================================
 
-scHicClusterSVL uses kmeans or spectral clustering to associate each cell to a cluster and therefore to its cell cycle. 
-The clustering is applied on dimension reduced data based on the ratio of short vs long range contacts per chromosome. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * (number of chromosomes). 
-Please consider also the other clustering and dimension reduction approaches of the scHicExplorer suite such as `scHicCluster`, `scHicClusterMinHash` and `scHicClusterSVL`. They can give you better results, 
+scHicClusterSVL uses kmeans or spectral clustering to associate each cell to a cluster and therefore to its cell cycle.
+The clustering is applied on dimension reduced data based on the ratio of short vs long range contacts per chromosome. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * (number of chromosomes).
+Please consider also the other clustering and dimension reduction approaches of the scHicExplorer suite such as `scHicCluster`, `scHicClusterMinHash` and `scHicClusterSVL`. They can give you better results,
 can be faster or less memory demanding.
 
 For more information about scHiCExplorer please consider our documentation on readthedocs.io_