--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scanpy-run-tsne.xml	Wed Apr 03 11:10:51 2019 -0400
@@ -0,0 +1,127 @@
+<?xml version="1.0" encoding="utf-8"?>
+<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>
+  </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
+    #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
+    #end if
+
+@PLOT_OPTS@
+]]></command>
+
+  <inputs>
+    <expand macro="input_object_params"/>
+    <expand macro="output_object_params"/>
+    <param name="embeddings" type="boolean" checked="true" label="Output embeddings in csv format"/>
+
+    <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"/>
+        <param name="learning_rate" argument="--learning-rate" type="float" value="1000" label="Learning rate, should be between 100 and 1000"/>
+        <param name="fast_tsne" type="boolean" checked="true" label="Use multicoreTSNE"/>
+        <param name="n_job" argument="--n-jobs" type="integer" optional="true" label="The number of jobs"/>
+        <param name="n_pc" argument="--n-pcs" type="integer" optional="true" label="The number of PCs to use"/>
+        <param name="random_seed" argument="--random-seed" type="integer" value="0" label="Seed for random number generator"/>
+      </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>
+  </outputs>
+
+  <tests>
+    <test>
+      <param name="input_obj_file" value="find_cluster.h5"/>
+      <param name="input_format" value="anndata"/>
+      <param name="output_format" value="anndata"/>
+      <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=","/>
+        </assert_contents>
+      </output>
+    </test>
+  </tests>
+
+  <help><![CDATA[
+==================================================================
+t-distributed stochastic neighborhood embedding (tSNE) (`tl.tsne`)
+==================================================================
+
+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,
+we use the implementation of *scikit-learn* (Pedregosa et al, 2011).
+
+It yields `X_tsne`, tSNE coordinates of data.
+
+@HELP@
+
+@VERSION_HISTORY@
+]]></help>
+  <expand macro="citations"/>
+</tool>