diff plotCorrelation.xml @ 3:df65a17fb5d1 draft

planemo upload for repository https://github.com/fidelram/deepTools/tree/master/galaxy/wrapper/ commit 2e8510e4f4015f51f7726de5697ba2de9b4e2f4c

--- a/plotCorrelation.xml	Thu Feb 18 11:50:18 2016 -0500
+++ b/plotCorrelation.xml	Wed Mar 09 18:20:03 2016 -0500
@@ -75,7 +75,7 @@
             <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="200" />
+            <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" />
@@ -83,20 +83,19 @@
             <param name="whatToPlot" value="scatterplot" />
             <param name="removeOutliers" value="True" />
             <param name="plotTitle" value="Test Plot" />
-            <output name="outFileName" file="plotCorrelation_result2.png" ftpye="png" compare="sim_size" delta="200" />
+            <output name="outFileName" file="plotCorrelation_result2.png" ftpye="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).
+Results can be visualized as **scatterplots** or as a **heatmap** of correlation coefficients (see below for examples).
 
-Background
-------------
+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.)
 
@@ -106,18 +105,18 @@
 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
+    :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").
 
@@ -125,14 +124,14 @@
 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
+    :width: 600
+    :height: 518
 
 The scatterplot could look like this:
 
 .. image:: $PATH_TO_IMAGES/plotCorrelation_scatterplot_PearsonCorr_bigwigScores.png
-   :width: 600
-   :height: 600
+    :width: 600
+    :height: 600
 
 -----