--- a/tools/mapping/ORApathwayEnrichment/ORApathwayEnrichment.xml	Fri Jan 31 18:28:53 2025 +0000
+++ b/tools/mapping/ORApathwayEnrichment/ORApathwayEnrichment.xml	Mon Feb 03 15:59:46 2025 +0000
@@ -1,11 +1,11 @@
 <?xml version="1.0" encoding="UTF-8" standalone="no"?>
-<tool id="met4j_ORApathwayEnrichment" name="ORApathwayEnrichment" version="develop">
+<tool id="met4j_ORApathwayEnrichment" name="ORApathwayEnrichment" version="2.0.0">
   <description>Perform Over Representation Analysis for Pathway Enrichment, using one-tailed exact Fisher Test.</description>
   <xrefs>
     <xref type="bio.tools">met4j</xref>
   </xrefs>
   <requirements>
-    <container type="singularity">oras://registry.forgemia.inra.fr/metexplore/met4j/met4j-singularity:develop</container>
+    <container type="singularity">oras://registry.forgemia.inra.fr/metexplore/met4j/met4j-singularity:2.0.0</container>
   </requirements>
   <command detect_errors="exit_code"><![CDATA[sh /usr/bin/met4j.sh mapping.ORApathwayEnrichment#if str($th) != 'nan':
  -th "$th"
@@ -32,262 +32,39 @@
   </outputs>
   <tests>
     <test>
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       <param name="sbml" value="XF_network.sbml"/>
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       <param name="input" value="XF_network_C_NOI.txt"/>
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       <param name="input" value="XF_network_C_NOI.txt"/>
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       <param name="corr" value="HolmBonferroni"/>
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       <param name="th" value="0.005"/>
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           <has_n_columns n="3"/>
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           <has_n_lines n="2"/>
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       </output>
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     </test>
   </tests>
   <help><![CDATA[Perform Over Representation Analysis for Pathway Enrichment, using one-tailed exact Fisher Test.
 The fisher exact test computes the probability p to randomly get the given set of values. 
 This version computes the probability to get at least the given overlap between the given set and the given modality :
 Sum the hypergeometric probability with increasing target/query intersection cardinality.
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 The hypergeometric probability is computed from the following contingency table entries.
 (values in cells correspond to the marginal totals of each intersection groups)
 				Query	!Query
 	Target		a		b
 	!Target		c		d
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 The probability of obtaining the set of value is computed as following:
 p = ((a+b)!(c+d)!(a+c)!(b+d)!)/(a!b!c!d!(a+b+c+d)!)
-
 The obtained p-value is then adjusted for multiple testing using one of the following methods:
  - Bonferroni: adjusted p-value = p*n
  - Benjamini-Hochberg: adjusted p-value = p*n/k