diff scHicClusterMinHash.xml @ 1:68648299ffc4 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/schicexplorer commit 72e1e90ac05a32dbd6fc675073429c0086048b18"

--- a/scHicClusterMinHash.xml	Thu Jan 23 16:04:57 2020 -0500
+++ b/scHicClusterMinHash.xml	Tue Mar 10 15:11:23 2020 -0400
@@ -8,7 +8,7 @@
     <command detect_errors="exit_code"><![CDATA[
         @BINARY@
 
-        --matrix '$matrix_mcooler'
+        --matrix '$matrix_scooler'
 
         --numberOfClusters $numberOfClusters
 
@@ -24,6 +24,7 @@
         #end if
 
         --outFileName cluster_list.txt
+        --numberOfNearestNeighbors $numberOfNearestNeighbors
 
         --threads @THREADS@
 
@@ -32,7 +33,7 @@
     ]]></command>
     <inputs>
         
-        <expand macro="matrix_mcooler_macro"/>
+        <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>
@@ -40,6 +41,7 @@
 
         <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="numberOfHashFunctions" type="integer" value="800"  label="Number of hash functions" help='How many hash functions the minHash algorithm uses.' />   
+        <param name="numberOfNearestNeighbors" type="integer" value="100"  label="Number of nearest neighbors" help='How many nearest neighbors should be computed for the k-nn graph?' />   
 
         <param name='chromosomes' type='text' label='List of chromosomes to consider' help='Please separate the chromosomes by space'/>
         <param name='exactModeMinhash' type='boolean' truevalue='--exactModeMinHash' label='The MinHash algorithm computes additional the exact euclidean distance.'/>
@@ -50,7 +52,7 @@
     </outputs>
     <tests>
         <test>
-            <param name='matrix_mcooler' value='test_matrix.mcool' />
+            <param name='matrix_scooler' value='test_matrix.scool' />
             <param name='clusterMethod_selector' value='kmeans' />
             <param name='numberOfClusters' value='3' />
             <param name='numberOfHashFunctions' value='800' />
@@ -58,7 +60,7 @@
             <output name="outFileName" file="scHicClusterMinHash/cluster_kmeans.txt" ftype="txt" compare="sim_size" delta="4000"/>
         </test>
         <test>
-            <param name='matrix_mcooler' value='test_matrix.mcool' />
+            <param name='matrix_scooler' value='test_matrix.scool' />
             <param name='clusterMethod_selector' value='spectral' />
             <param name='numberOfClusters' value='3' />
             <param name='numberOfHashFunctions' value='800' />
@@ -66,7 +68,7 @@
             <output name="outFileName" file="scHicClusterMinHash/cluster_spectral.txt" ftype="txt" compare="sim_size" delta="4000"/>
         </test>
         <test>
-            <param name='matrix_mcooler' value='test_matrix.mcool' />
+            <param name='matrix_scooler' value='test_matrix.scool' />
             <param name='clusterMethod_selector' value='kmeans' />
             <param name='numberOfClusters' value='3' />
             <param name='numberOfHashFunctions' value='800' />
@@ -75,7 +77,7 @@
             <output name="outFileName" file="scHicClusterMinHash/cluster_kmeans_exact.txt" ftype="txt" compare="sim_size" delta="4000"/>
         </test>
         <test>
-            <param name='matrix_mcooler' value='test_matrix.mcool' />
+            <param name='matrix_scooler' value='test_matrix.scool' />
             <param name='clusterMethod_selector' value='spectral' />
             <param name='numberOfClusters' value='3' />
             <param name='numberOfHashFunctions' value='800' />
@@ -92,10 +94,10 @@
 Clustering with dimension reduction via MinHash
 ===============================================
 
-scHicClusterMinHash 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 an approximate kNN search with the local sensitive hashing technique MinHash. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * samples. 
-Please consider also the other clustering and dimension reduction approaches of the scHicExplorer suite. They can give you better results, 
-can be faster or less memory demanding.
+scHicClusterMinHash 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 an approximate kNN search with the local sensitive hashing technique MinHash. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * samples. 	The clustering is applied on dimension reduced data based on an approximate kNN search with the local sensitive hashing technique MinHash. This approach reduces the number of dimensions from samples * (number of bins)^2 to samples * samples.
+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, 	Please consider also the other clustering and dimension reduction approaches of the scHicExplorer suite such as `scHicCluster`, `scHicClusterCompartments` and `scHicClusterSVL`. They can give you better results,
+can be faster or less memory demanding.	can be faster or less memory demanding.
 
 For more information about scHiCExplorer please consider our documentation on readthedocs.io_