comparison plotCorrelation.xml @ 5:ae54e08b15d7 draft

planemo upload for repository https://github.com/fidelram/deepTools/tree/master/galaxy/wrapper/ commit 8b9cdb8dc4a8fedd2b2286e7afab6529e49a9d22-dirty

4:d5b93c88cc6b

<tool id="deeptools_plot_correlation" name="plotCorrelation" version="@WRAPPER_VERSION@.0">
    <description>creates a heatmap of correlation scores between different samples </description>
    <macros>
        <token name="@BINARY@">plotCorrelation</token>
        <import>deepTools_macros.xml</import>
    </macros>
    <expand macro="requirements"/>

    <help>
<![CDATA[
**What it does**

This tools takes a compressed matrix of scores (such as read coverages) for a number of genomic regions
and different samples. It can visualize the correlation among samples as scatterplots or as 
heatmap of correlation coefficients. Further output files are optional.
The compressed input matrices are easily generated using the "bamCorrelate" and "bigwigCorrelate" modules of deeptools.


.. image:: $PATH_TO_IMAGES/QC_bamCorrelate_humanSamples.png

You can find more details on plotCorrelation here http://deeptools.readthedocs.org/en/release-1.6/content/tools/plotCorrelation.html


**Output files**:

- **correlation structure**: a scatterplot of all mutual correlations between all samples in matrix
- **diagnostic plot**: clustered heatmap displaying the values for each pair-wise correlation, see below for an example
- data matrix (optional): if you want to analyze or plot the correlation values using a different program, e.g. R, this matrix can be used

-----

@REFERENCES@
]]>

5:ae54e08b15d7

<tool id="deeptools_plot_correlation" name="plotCorrelation" version="@WRAPPER_VERSION@.0">
    <description>creates 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"/>

    <help>
<![CDATA[
**What it does**

This tools takes a compressed matrix of scores (such as read coverages) for a number of genomic regions
and different samples. It can visualize the correlation among samples as scatterplots or as
heatmap of correlation coefficients. Further output files are optional.
The compressed input matrices are easily generated using the "bamCorrelate" and "bigwigCorrelate" modules of deeptools.


.. image:: $PATH_TO_IMAGES/QC_bamCorrelate_humanSamples.png

You can find more details on plotCorrelation here http://deeptools.readthedocs.org/en/release-1.6/content/tools/plotCorrelation.html


**Output files**:

- **diagnostic plot**: Either a scatterplot or clustered heatmap (select above) displaying the values for each pair-wise correlation,
  see below for an example
- data matrix (optional): if you want to analyze or plot the correlation values using a different program, e.g. R, this matrix can be used

**Output with test dataset**:

Following is the output of plotCorrelation with our test ChIP-Seq datasets. Average coverages were computed over 10kb bins for chromosome X,
from bigwig files using bigwigCorrelate. The output was used by plotCorrelation to make a heatmap of spearman correlation between samples.

.. image:: $PATH_TO_IMAGES/plotCorrelation_galaxy_bw_heatmap_output.png


-----

@REFERENCES@
]]>