changeset 1:5f589c91566e draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/heinz commit a4b0969b33a68a0ea9ba12291f6694aec24f13ed

--- a/heinz.xml	Thu Aug 02 11:57:44 2018 -0400
+++ b/heinz.xml	Tue Oct 30 18:57:02 2018 -0400
@@ -4,13 +4,13 @@
         <requirement type="package" version="2.0">heinz</requirement>
     </requirements>
     <command detect_errors="aggressive"><![CDATA[
-heinz -m \${GALAXY_SLOTS:-2} -n '$score' -e '$edge' 1> '$subnetwork'
+heinz -m \${GALAXY_SLOTS:-2} -n '$score' -e '$edge' > '$subnetwork'
     ]]></command>
     <inputs>
-        <param type="data" name="score" format="txt" label="File containing Heinz scores"
-        help="The file should contain two columns: the node identifier (e.g. gene) and the corresponding Heinz score" />
-        <param type="data" name="edge" format="txt" label="Edge file"
-        help="In this file, two nodes define one edge, one edge per line" />
+        <param name="score" type="data" format="txt" label="File containing Heinz scores"
+            help="The file should contain two columns: the node identifier (e.g. gene) and the corresponding Heinz score" />
+        <param name="edge" type="data" format="txt" label="Edge file"
+            help="In this file, two nodes define one edge, one edge per line" />
     </inputs>
     <outputs>
         <data name="subnetwork" format="txt" label="${tool.name} on ${on_string}: Optimal subgraph" />
@@ -43,16 +43,15 @@
 the second, Heinz score.
 
 ========= ===================
-BRCA2    -6.991782933819368
+BRCA2     -6.991782933819368
 --------- -------------------
-BRCA1    -5.206139799106934
+BRCA1     -5.206139799106934
 --------- -------------------
-AACS     -0.9299868303078357
+AACS      -0.9299868303078357
 --------- -------------------
 ABCC11    -5.845009850430119
 ========= ===================
 
-
 Edge file: the background network Heinz uses in the form of a list of edges; each line is made up of
 two node identifiers (e.g., genes, KEGG ORTHOLOGY (KO)) delimited by a tab. In practice, we could
 prepare this file using different pathway databases, such as Reactome, STRING and KEGG. Which database
@@ -67,8 +66,6 @@
 --------- ---------
 NPTX1     CIAO1
 ========= =========
-
-
     ]]></help>
     <citations>
         <citation type="doi">10.1093/bioinformatics/btn161</citation>

--- a/heinz_scoring.py	Thu Aug 02 11:57:44 2018 -0400
+++ b/heinz_scoring.py	Tue Oct 30 18:57:02 2018 -0400
@@ -85,10 +85,7 @@
 # Calculate the scores
 input_pvalues = pd.read_csv(args.nodes, sep='\t', names=['node', 'pvalue'])
 input_pvalues.loc[:, 'score'] = input_pvalues.pvalue.apply(lambda x:
-                                                           (alpha - 1) *
-                                                           (np.log(x) -
-                                                            np.log(
-                                                                p_threshold)))
+                                                           (alpha - 1) * (np.log(x) - np.log(p_threshold)))
 # print(input_pvalues.loc[:, ['node', 'score']])
 input_pvalues.loc[:, ['node', 'score']].to_csv(args.output, sep='\t',
                                                index=False, header=False)