--- a/hyphy_fade.xml	Thu Mar 02 14:58:21 2023 +0000
+++ b/hyphy_fade.xml	Tue Oct 07 20:37:49 2025 +0000
@@ -13,29 +13,51 @@
             @INPUT_TREE@
             @branch_options@
             --model '$model'
-            --method '$posteriorEstimationMethod.method'
-            --grid '$grid_points'
-            --concentration_parameter '$concentration'
+            --method '$advanced_options.posteriorEstimationMethod.method'
             @posteriorEstimationMethod_cmd@
+            --grid '$advanced_options.grid_points'
+            --concentration_parameter '$advanced_options.concentration'
             --output '$fade_output'
+            > fade_stdout.md 
         @ERRORS@
     ]]></command>
     <inputs>
         <expand macro="inputs"/>
         <expand macro="branches"/>
         <expand macro="substitution" argument="--model"/>
-        <expand macro="conditional_posteriorEstimationMethod" />
-        <param argument="--grid" name="grid_points" type="integer" value="20" min="5" max="50" label="Grid points"/>
-        <param argument="--concentration_parameter" name="concentration" type="float" value="0.5" min="0.001" max="1" label="Concentration parameter of the Dirichlet prior"/>
+        <section name="advanced_options" title="Advanced Options" expanded="false">
+            <expand macro="conditional_posteriorEstimationMethod" />
+            <param argument="--grid" name="grid_points" type="integer" value="20" min="5" max="50" label="Grid points" help="The number of grid points." />
+            <param argument="--concentration_parameter" name="concentration" type="float" value="0.5" min="0.001" max="1" label="Concentration parameter of the Dirichlet prior" help="The concentration parameter of the Dirichlet prior." />
+        </section>
     </inputs>
     <outputs>
         <data name="fade_output" format="hyphy_results.json" />
+        <data name="fade_md_report" format="markdown" from_work_dir="fade_stdout.md" label="FADE Report (Markdown) for ${tool.name} on ${on_string}" />
     </outputs>
     <tests>
-        <test>
+        <test expect_num_outputs="2">
             <param name="input_file" ftype="fasta" value="fade-in1.fa"/>
             <param name="input_nhx" ftype="nhx" value="fade-in1.nhx"/>
-            <output name="fade_output" file="fade-out1.json" compare="sim_size"/>
+            <param name="model" value="WAG"/>
+            <section name="advanced_options">
+                <conditional name="posteriorEstimationMethod">
+                    <param name="method" value="Variational-Bayes"/>
+                </conditional>
+                <param name="grid_points" value="20"/>
+                <param name="concentration" value="0.5"/>
+            </section>
+            <output name="fade_output">
+                <assert_contents>
+                    <has_text text="Empiricial Bayes Factor for substitution bias"/>
+                    <has_text text="Substitution history on selected branches"/>
+                </assert_contents>
+            </output>
+            <output name="fade_md_report">
+                <assert_contents>
+                    <has_text text="FADE analysis summary. Evidence for directional selection evaluated using empirical Bayes factor threshold of 100"/>
+                </assert_contents>
+            </output>
         </test>
     </tests>
     <help><![CDATA[
@@ -59,12 +81,9 @@
 Brief description
 -----------------
 
-FFADE (FUBAR Approach to Directional Evolution) is a fast method to test
-whether or not a subset of sites in a protein alignment evolve towards a
-particular residue along a subset of branches at accelerated rates
-compared to reference model. FADE uses a random effects model and latent
-Dirichlet allocation (LDA) - inspired approximation methods to allocate
-sites to rate classes.
+FADE (FUBAR Approach to Directional Evolution) is a fast method to test whether or not a subset of sites in a protein alignment evolve towards a particular residue along a subset of branches at accelerated rates compared to a reference model. FADE uses a random effects model and latent Dirichlet allocation (LDA)-inspired approximation methods to allocate sites to rate classes.
+
+The intuition behind FADE is to detect directional selection, where amino acid substitutions are consistently biased towards a particular residue type. This can be indicative of adaptation to new functional constraints or environments. By comparing the observed substitution patterns to a null model (e.g., a standard protein substitution model or a gene-average model), FADE identifies sites that exhibit significant directional bias in their evolutionary trajectory.
 
 Input
 -----
@@ -137,9 +156,16 @@
                         The concentration parameter of the Dirichlet prior
                         default value: 0.5
 
+    Output
+    ------
 
+    A JSON file with analysis results (http://hyphy.org/resources/json-fields.pdf).
 
-]]>
+    A custom visualization module for viewing these results is available (see http://vision.hyphy.org/FADE for an example)
+
+    A Markdown file with a summary of the analysis.
+
+    ]]>
 </help>
     <expand macro="citations">
     </expand>