--- a/plotCorrelation.xml	Tue Jan 24 04:57:11 2017 -0500
+++ b/plotCorrelation.xml	Fri Mar 31 09:27:20 2017 -0400
@@ -1,142 +1,142 @@
-<tool id="deeptools_plot_correlation" name="plotCorrelation" version="@WRAPPER_VERSION@.0">
-    <description>Create a heatmap or scatterplot of correlation scores between different samples </description>
-    <macros>
-        <token name="@BINARY@">plotCorrelation</token>
-        <import>deepTools_macros.xml</import>
-    </macros>
-    <expand macro="requirements"/>
-    <command>
-<![CDATA[
-        @BINARY@
-            --corData "$corData"
-            --plotFile "$outFileName"
-            --corMethod "$corMethod"
-            --whatToPlot "$plotting_type.whatToPlot"
-            #if str($plotting_type.whatToPlot) == 'heatmap':
-                @HEATMAP_OPTIONS@
-            #else:
-                --plotTitle '$plotting_type.plotTitle'
-            #end if
-            $skipZeros
-            --plotFileFormat "$outFileFormat"
-            $removeOutliers
-            #if $outFileCorMatrix:
-                --outFileCorMatrix "$matrix"
-            #end if
-
-]]>
-    </command>
-    <inputs>
-        <param name="corData" format="deeptools_coverage_matrix" type="data" label="Matrix file from the multiBamSummary tool"/>
-        <expand macro="corMethod" />
-
-        <conditional name="plotting_type" >
-            <param argument="--whatToPlot" type="select" label="Plotting type">
-                <option value="heatmap" selected="True">Heatmap</option>
-                <option value="scatterplot">Scatterplot</option>
-            </param>
-            <when value="heatmap">
-                <expand macro="heatmap_options" />
-            </when>
-            <when value="scatterplot">
-                <expand macro="plotTitle" />
-            </when>
-        </conditional>
-
-        <expand macro="skipZeros" />
-
-        <expand macro="input_image_file_format" />
-
-        <param argument="--removeOutliers" type="boolean"
-            truevalue="--removeOutliers" falsevalue="" label="Remove regions with very large counts"
-            help="If set, bins with very large counts are removed. Bins
-                with abnormally high reads counts artificially
-                increase pearson correlation; that's why, by default,
-                plotCorrelation tries to remove outliers using the median
-                absolute deviation (MAD) method applying a threshold
-                of 200 to only consider extremely large deviations
-                from the median. ENCODE blacklist page (https://sites.
-                google.com/site/anshulkundaje/projects/blacklists)
-                contains useful information about regions with
-                unusually high counts."/>
-
-        <param name="outFileCorMatrix" type="boolean" label="Save the matrix of values underlying the heatmap"/>
-
-    </inputs>
-    <outputs>
-        <expand macro="output_image_file_format_not_nested" />
-        <data format="tabular" name="matrix" label="${tool.name} on ${on_string}: Correlation matrix">
-            <filter>outFileCorMatrix is True</filter>
-        </data>
-    </outputs>
-    <tests>
-        <test>
-            <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
-            <param name="outFileFormat" value="png" />
-            <param name="outFileCorMatrix" value="True" />
-            <output name="matrix" file="plotCorrelation_result1.tabular" ftype="tabular" />
-            <output name="outFileName" file="plotCorrelation_result1.png" ftype="png" compare="sim_size" delta="300" />
-        </test>
-        <test>
-            <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
-            <param name="outFileFormat" value="png" />
-            <param name="whatToPlot" value="scatterplot" />
-            <param name="removeOutliers" value="True" />
-            <param name="plotTitle" value="Test Plot" />
-            <output name="outFileName" file="plotCorrelation_result2.png" ftype="png" compare="sim_size" delta="300" />
-        </test>
-    </tests>
-    <help>
-<![CDATA[
-What it does
-------------
-
-This tools takes the default output of ``multiBamSummary`` or ``multiBigwigSummary``, and computes the pairwise correlation among samples.
-Results can be visualized as **scatterplots** or as a **heatmap** of correlation coefficients (see below for examples).
-
-Theoretical Background
-----------------------
-
-The result of the correlation computation is a **table of correlation coefficients** that indicates how "strong" the relationship between two samples is and it will consist of numbers between -1 and 1. (-1 indicates perfect anti-correlation, 1 perfect correlation.)
-
-We offer two different functions for the correlation computation: *Pearson* or *Spearman*.
-
-The *Pearson method* measures the **metric differences** between samples and is therefore influenced by outliers.
-The *Spearman method* is based on **rankings**.
-
-Output
-------
-
-The default output is a **diagnostic plot** -- either a scatterplot or a clustered heatmap displaying the values for each pair-wise correlation (see below for example plots).
-
-Optionally, you can also obtain a table of the pairwise correlation coefficients.
-
-.. image:: $PATH_TO_IMAGES/plotCorrelation_output.png
-    :width: 600
-    :height: 271
-
-Example plots
--------------
-
-The following is the output of ``plotCorrelation`` with our test ChIP-Seq datasets (to be found under "Shared Data" --> "Data Library").
-
-Average coverages were computed over 10 kb bins for chromosome X,
-from bigWig files using ``multiBigwigSummary``. This was then used with ``plotCorrelation`` to make a heatmap of Spearman correlation coefficients.
-
-.. image:: $PATH_TO_IMAGES/plotCorrelation_galaxy_bw_heatmap_output.png
-    :width: 600
-    :height: 518
-
-The scatterplot could look like this:
-
-.. image:: $PATH_TO_IMAGES/plotCorrelation_scatterplot_PearsonCorr_bigwigScores.png
-    :width: 600
-    :height: 600
-
------
-
-@REFERENCES@
-]]>
-    </help>
-    <expand macro="citations" />
-</tool>
+<tool id="deeptools_plot_correlation" name="plotCorrelation" version="@WRAPPER_VERSION@.0">
+    <description>Create a heatmap or scatterplot of correlation scores between different samples </description>
+    <macros>
+        <token name="@BINARY@">plotCorrelation</token>
+        <import>deepTools_macros.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <command>
+<![CDATA[
+        @BINARY@
+            --corData "$corData"
+            --plotFile "$outFileName"
+            --corMethod "$corMethod"
+            --whatToPlot "$plotting_type.whatToPlot"
+            #if str($plotting_type.whatToPlot) == 'heatmap':
+                @HEATMAP_OPTIONS@
+            #else:
+                --plotTitle '$plotting_type.plotTitle'
+            #end if
+            $skipZeros
+            --plotFileFormat "$outFileFormat"
+            $removeOutliers
+            #if $outFileCorMatrix:
+                --outFileCorMatrix "$matrix"
+            #end if
+
+]]>
+    </command>
+    <inputs>
+        <param name="corData" format="deeptools_coverage_matrix" type="data" label="Matrix file from the multiBamSummary tool"/>
+        <expand macro="corMethod" />
+
+        <conditional name="plotting_type" >
+            <param argument="--whatToPlot" type="select" label="Plotting type">
+                <option value="heatmap" selected="True">Heatmap</option>
+                <option value="scatterplot">Scatterplot</option>
+            </param>
+            <when value="heatmap">
+                <expand macro="heatmap_options" />
+            </when>
+            <when value="scatterplot">
+                <expand macro="plotTitle" />
+            </when>
+        </conditional>
+
+        <expand macro="skipZeros" />
+
+        <expand macro="input_image_file_format" />
+
+        <param argument="--removeOutliers" type="boolean"
+            truevalue="--removeOutliers" falsevalue="" label="Remove regions with very large counts"
+            help="If set, bins with very large counts are removed. Bins
+                with abnormally high reads counts artificially
+                increase pearson correlation; that's why, by default,
+                plotCorrelation tries to remove outliers using the median
+                absolute deviation (MAD) method applying a threshold
+                of 200 to only consider extremely large deviations
+                from the median. ENCODE blacklist page (https://sites.
+                google.com/site/anshulkundaje/projects/blacklists)
+                contains useful information about regions with
+                unusually high counts."/>
+
+        <param name="outFileCorMatrix" type="boolean" label="Save the matrix of values underlying the heatmap"/>
+
+    </inputs>
+    <outputs>
+        <expand macro="output_image_file_format_not_nested" />
+        <data format="tabular" name="matrix" label="${tool.name} on ${on_string}: Correlation matrix">
+            <filter>outFileCorMatrix is True</filter>
+        </data>
+    </outputs>
+    <tests>
+        <test>
+            <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
+            <param name="outFileFormat" value="png" />
+            <param name="outFileCorMatrix" value="True" />
+            <output name="matrix" file="plotCorrelation_result1.tabular" ftype="tabular" />
+            <output name="outFileName" file="plotCorrelation_result1.png" ftype="png" compare="sim_size" delta="300" />
+        </test>
+        <test>
+            <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
+            <param name="outFileFormat" value="png" />
+            <param name="whatToPlot" value="scatterplot" />
+            <param name="removeOutliers" value="True" />
+            <param name="plotTitle" value="Test Plot" />
+            <output name="outFileName" file="plotCorrelation_result2.png" ftype="png" compare="sim_size" delta="300" />
+        </test>
+    </tests>
+    <help>
+<![CDATA[
+What it does
+------------
+
+This tools takes the default output of ``multiBamSummary`` or ``multiBigwigSummary``, and computes the pairwise correlation among samples.
+Results can be visualized as **scatterplots** or as a **heatmap** of correlation coefficients (see below for examples).
+
+Theoretical Background
+----------------------
+
+The result of the correlation computation is a **table of correlation coefficients** that indicates how "strong" the relationship between two samples is and it will consist of numbers between -1 and 1. (-1 indicates perfect anti-correlation, 1 perfect correlation.)
+
+We offer two different functions for the correlation computation: *Pearson* or *Spearman*.
+
+The *Pearson method* measures the **metric differences** between samples and is therefore influenced by outliers.
+The *Spearman method* is based on **rankings**.
+
+Output
+------
+
+The default output is a **diagnostic plot** -- either a scatterplot or a clustered heatmap displaying the values for each pair-wise correlation (see below for example plots).
+
+Optionally, you can also obtain a table of the pairwise correlation coefficients.
+
+.. image:: $PATH_TO_IMAGES/plotCorrelation_output.png
+    :width: 600
+    :height: 271
+
+Example plots
+-------------
+
+The following is the output of ``plotCorrelation`` with our test ChIP-Seq datasets (to be found under "Shared Data" --> "Data Library").
+
+Average coverages were computed over 10 kb bins for chromosome X,
+from bigWig files using ``multiBigwigSummary``. This was then used with ``plotCorrelation`` to make a heatmap of Spearman correlation coefficients.
+
+.. image:: $PATH_TO_IMAGES/plotCorrelation_galaxy_bw_heatmap_output.png
+    :width: 600
+    :height: 518
+
+The scatterplot could look like this:
+
+.. image:: $PATH_TO_IMAGES/plotCorrelation_scatterplot_PearsonCorr_bigwigScores.png
+    :width: 600
+    :height: 600
+
+-----
+
+@REFERENCES@
+]]>
+    </help>
+    <expand macro="citations" />
+</tool>