--- a/scanpy-run-tsne.xml	Wed Apr 03 11:10:51 2019 -0400
+++ b/scanpy-run-tsne.xml	Mon Sep 16 08:17:58 2019 -0400
@@ -2,45 +2,45 @@
 <tool id="scanpy_run_tsne" name="Scanpy RunTSNE" version="@TOOL_VERSION@+galaxy1">
   <description>visualise cell clusters using tSNE</description>
   <macros>
-    <import>scanpy_macros.xml</import>
+    <import>scanpy_macros2.xml</import>
   </macros>
   <expand macro="requirements"/>
   <command detect_errors="exit_code"><![CDATA[
 ln -s '${input_obj_file}' input.h5 &&
-PYTHONIOENCODING=utf-8 scanpy-run-tsne.py
-    -i input.h5
-    -f '${input_format}'
-    -o output.h5
-    -F '${output_format}'
-    #if $embeddings
-        --output-embeddings-file embeddings.csv
+PYTHONIOENCODING=utf-8 scanpy-run-tsne
+#if $use_rep != "auto"
+    --use-rep '${use_rep}'
+#end if
+#if $key_added
+    --key-added '${key_added}'
+#end if
+#if $embeddings
+    --export-embedding embeddings.csv
+#end if
+#if $settings.default == "false"
+    #if $settings.perplexity_file
+        --perplexity \$( cat $settings.perplexity_file )
+    #else
+        --perplexity '${settings.perplexity}'
     #end if
-    #if $settings.default == "false"
-        #if $settings.perplexity_file
-          --perplexity \$( cat $settings.perplexity_file )
-        #else
-          --perplexity '${settings.perplexity}'
-        #end if
-        --early-exaggeration '${settings.early_exaggeration}'
-        --learning-rate '${settings.learning_rate}'
-        #if $settings.use_rep != "auto"
-            -r '${settings.use_rep}'
-        #end if
-        #if $settings.n_pc
-            -n '${settings.n_pc}'
-        #end if
-        #if not $settings.fast_tsne
-            --no-fast-tsne
-        #end if
-        #if $settings.n_job
-            --n-jobs '${settings.n_job}'
-        #end if
-        #if $settings.random_seed is not None
-            -s '${settings.random_seed}'
-        #end if
+    --early-exaggeration '${settings.early_exaggeration}'
+    --learning-rate '${settings.learning_rate}'
+    #if $settings.n_pc
+        --n-pcs ${settings.n_pc}
+    #end if
+    #if not $settings.fast_tsne
+        --no-fast-tsne
     #end if
+    #if $settings.n_job
+        --n-jobs ${settings.n_job}
+    #end if
+    #if $settings.random_seed is not None
+        --random-state ${settings.random_seed}
+    #end if
+#end if
+    @INPUT_OPTS@
+    @OUTPUT_OPTS@
 
-@PLOT_OPTS@
 ]]></command>
 
   <inputs>
@@ -48,15 +48,18 @@
     <expand macro="output_object_params"/>
     <param name="embeddings" type="boolean" checked="true" label="Output embeddings in csv format"/>
 
+    <param name="use_rep" argument="--use-rep" type="select" label="Use the indicated representation">
+      <option value="X_pca">X_pca, use PCs</option>
+      <option value="X">X, use normalised expression values</option>
+      <option value="auto" selected="true">Automatically chosen based on problem size</option>
+    </param>
+    <param name="key_added" argument="--key-added" type="text" optional="true"
+           label="Additional suffix to the name of the slot to save the embedding"/>
+
     <conditional name="settings">
       <param name="default" type="boolean" checked="true" label="Use programme defaults"/>
       <when value="true"/>
       <when value="false">
-        <param name="use_rep" argument="--use-rep" type="select" label="Use the indicated representation">
-          <option value="X_pca">X_pca, use PCs</option>
-          <option value="X">X, use normalised expression values</option>
-          <option value="auto" selected="true">Automatically chosen based on problem size</option>
-        </param>
         <param name="perplexity" argument="--perplexity" type="float" value="30" label="The perplexity is related to the number of nearest neighbours, select a value between 5 and 50"/>
         <param name="perplexity_file" argument="--perplexity" type="data" format="txt,tsv" label="The perplexity is related to the number of nearest neighbours" help="For use with the parameter iterator. Overrides the persplexity option above" optional="true"/>
         <param name="early_exaggeration" argument="--early-exaggeration" type="float" value="12" label="Controls the tightness within and between clusters"/>
@@ -68,21 +71,10 @@
       </when>
     </conditional>
 
-    <conditional name="do_plotting">
-      <param name="plot" type="boolean" checked="false" label="Make tSNE plot"/>
-      <when value="true">
-        <expand macro="output_plot_params"/>
-        <param name="color_by" argument="--color-by" type="text" value="louvain" label="Color by attributes, comma separated strings"/>
-      </when>
-      <when value="false"/>
-    </conditional>
   </inputs>
 
   <outputs>
     <data name="output_h5" format="h5" from_work_dir="output.h5" label="${tool.name} on ${on_string}: tSNE object"/>
-    <data name="output_png" format="png" from_work_dir="output.png" label="${tool.name} on ${on_string}: tSNE plot">
-      <filter>do_plotting['plot']</filter>
-    </data>
     <data name="output_embed" format="csv" from_work_dir="embeddings.csv" label="${tool.name} on ${on_string}: tSNE embeddings">
       <filter>embeddings</filter>
     </data>
@@ -96,10 +88,7 @@
       <param name="default" value="false"/>
       <param name="embeddings" value="true"/>
       <param name="random_seed" value="0"/>
-      <param name="plot" value="true"/>
-      <param name="color_by" value="louvain"/>
       <output name="output_h5" file="run_tsne.h5" ftype="h5" compare="sim_size"/>
-      <output name="output_png" file="run_tsne.png" ftype="png" compare="sim_size"/>
       <output name="output_embed" file="run_tsne.embeddings.csv" ftype="csv" compare="sim_size">
         <assert_contents>
           <has_n_columns n="2" sep=","/>
@@ -109,9 +98,12 @@
   </tests>
 
   <help><![CDATA[
-==================================================================
-t-distributed stochastic neighborhood embedding (tSNE) (`tl.tsne`)
-==================================================================
+=========================================================================
+t-distributed stochastic neighborhood embedding (tSNE) (`scanpy.tl.tsne`)
+=========================================================================
+
+For making TSNE plots, please use `Scanpy PlotEmbed` with the output of this tool and enter "tsne" as the
+name of the embedding to plot.
 
 t-distributed stochastic neighborhood embedding (tSNE) (Maaten et al, 2008) has been
 proposed for visualizating single-cell data by (Amir et al, 2013). Here, by default,