--- a/hyphy_fade.xml	Mon Feb 17 14:52:56 2020 -0500
+++ b/hyphy_fade.xml	Thu Feb 20 18:12:40 2020 -0500
@@ -14,15 +14,10 @@
             --tree ./fade_input.nhx
             --branches '$branches'
             --model '$model'
-            --method '$posteriorEstimationMethod'
+            --method '$posteriorEstimationMethod.method'
             --grid '$grid_points'
             --concentration_parameter '$concentration'
-            #if $posteriorEstimationMethod != "Metropolis-Hastings"
-                --chains '$mcmc'
-                --chain-length '$chain_length'
-                --burn-in '$samples'
-                --samples '$samples_per_chain'
-            #end if
+            @posteriorEstimationMethod_cmd@
             --output '$fade_output'
             > '$fade_log'
     ]]></command>
@@ -30,23 +25,11 @@
         <param name="input_file" type="data" format="fasta" label="Input amino acid FASTA file"/>
         <param name="input_nhx" type="data" format="nhx" label="Input rooted newick file"/>
         <expand macro="branches"/>
-        <expand macro="substitution" />
-        <param name="grid_points" type="integer" value="20" min="5" max="50" label="Grid points"/>
-        <param name="mcmc" type="integer" value="5" min="2" max="20" label="Number of MCMC chains"/>
-        <param name="chain_length" type="integer" value="2000000" min="500000" max="50000000" label="Length of each chain"/>
-        <param name="samples" type="integer" value="1000000" min="100000" max="1900000" label="Samples to use for burn-in"/>
-        <param name="samples_per_chain" type="integer" value="100" min="50" max="1000000" label="Samples to draw from each chain"/>
-        <param name="concentration" type="float" value="0.5" min="0.001" max="1" label="Concentration parameter of the Dirichlet prior"/>
+        <expand macro="substitution"/>
         <expand macro="branches"/>
-        <param name="posteriorEstimationMethod" type="select" label="Posterior estimation method">
-            <option value="Variational-Bayes">Metropolis-Hastings - Full
-            Metropolis-Hastings MCMC algorithm (slowest, original 2013
-            paper implementation)</option>
-            <option value="Collapsed-Gibbs">Collapsed Gibbs - Collapsed Gibbs sampler
-            (intermediate speed)</option>
-            <option value="Metropolis-Hastings">Variational Bayes - 0-th order Variational
-            Bayes approximations (fastest, recommended default)</option>
-        </param>
+        <expand macro="conditional_posteriorEstimationMethod" />
+        <param name="grid_points" type="integer" value="20" min="5" max="50" label="Grid points"/>
+        <param name="concentration" type="float" value="0.5" min="0.001" max="1" label="Concentration parameter of the Dirichlet prior"/>
     </inputs>
     <outputs>
         <data name="fade_log" format="txt"/>
@@ -60,13 +43,108 @@
         </test>
     </tests>
     <help><![CDATA[
-FADE (FUBAR Approach to Directional Evolution) uses the same underlying algorithmic advances as impletented in FUBAR to apply Baysian MCMC accounting of parameter uncertiantiy to detect sites evolving under directional evolution in protien alignments.
+
+FADE : FUBAR Approach to Directional Evolution
+==============================================
+
+What question does this method answer?
+--------------------------------------
+
+Which site(s) in an alignment evolve towards to or away from a particular residue.
+
+Recommended Applications
+------------------------
+
+Screen protein sequence alignments where the direction of evolution can be resolved
+(via tree rooting, e.g. using an outgroup) to find sites which evolve differently from
+a standard protein model (selected by the user), or a gene-average model (GTR) to find
+evidence of directional selection.
+
+Brief description
+-----------------
 
-See the online documentation_ for more information.
+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.
+
+Input
+-----
+
+1. A *FASTA* sequence alignment of protein sequences.
+2. A *rooted* phylogenetic tree in the *Newick* format
+
+Note: the names of sequences in the alignment must match the names of the sequences in the tree.
+
+
+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)
+
+Further reading
+---------------
+
+http://hyphy.org/methods/selection-methods/#FADE
+
+
+Tool options
+------------
 
-.. _documentation: http://hyphy.org/methods/selection-methods/#fade
-    ]]></help>
+::
+
+
+    --model            The baseline substitution model to use
+                            [default] use GTR
+
+    --branches          Which branches should be tested for selection?
+                            All [default] : test all branches
+
+                            Internal : test only internal branches (suitable for
+                            intra-host pathogen evolution for example, where terminal branches
+                            may contain polymorphism data)
+
+                            Leaves: test only terminal (leaf) branches
+
+                            Unlabeled: if the Newick string is labeled using the {} notation,
+                            test only branches without explicit labels
+                            (see http://hyphy.org/tutorials/phylotree/)
+
+    --grid             The number of grid points
+                        Smaller : faster
+                        Larger : more precise posterior estimation but slower
+                        default value: 20
+
+    --method           Inference method to use
+                            Variational-Bayes : 0-th order Variational Bayes approximation; fastest [default]
+                            Metropolis-Hastings : Full Metropolis-Hastings MCMC algorithm; orignal method [slowest]
+                            Collapsed-Gibbs  : Collapsed Gibbs sampler [intermediate speed]
+
+
+    --chains           How many MCMC chains to run (does not apply to Variational-Bayes)
+                            default value: 5
+
+    --chain-length     MCMC chain length (does not apply to Variational-Bayes)
+                            default value: 2,000,000
+
+    --burn-in          MCMC chain burn in (does not apply to Variational-Bayes)
+                            default value: 1,000,000
+
+    --samples          MCMC samples to draw (does not apply to Variational-Bayes)
+                            default value: 1,000
+
+    --concentration_parameter
+                        The concentration parameter of the Dirichlet prior
+                        default value: 0.5
+
+
+
+]]>
+</help>
     <expand macro="citations">
-        <citation type="doi">10.1093/molbev/msv022</citation>
     </expand>
 </tool>