Mercurial > repos > bgruening > deeptools_plot_correlation

annotate plotCorrelation.xml @ 7:b3589208f673 draft

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author bgruening
date Fri, 13 May 2016 14:24:25 -0400
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children cdde99ce71c8
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1 <tool id="deeptools_plot_correlation" name="plotCorrelation" version="@WRAPPER_VERSION@.0">
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2 <description>Create a heatmap or scatterplot of correlation scores between different samples </description>
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3 <macros>
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4 <token name="@BINARY@">plotCorrelation</token>
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5 <import>deepTools_macros.xml</import>
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6 </macros>
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7 <expand macro="requirements"/>
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8 <command>
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9 <![CDATA[
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10 @BINARY@
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11 --corData "$corData"
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12 --plotFile "$outFileName"
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13 --corMethod "$corMethod"
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14 --whatToPlot "$plotting_type.whatToPlot"
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15 #if str($plotting_type.whatToPlot) == 'heatmap':
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16 @HEATMAP_OPTIONS@
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17 #else:
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18 --plotTitle '$plotting_type.plotTitle'
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19 #end if
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20 $skipZeros
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21 --plotFileFormat "$outFileFormat"
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22 $removeOutliers
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23 #if $outFileCorMatrix:
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24 --outFileCorMatrix "$matrix"
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25 #end if
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26
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27 ]]>
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28 </command>
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29 <inputs>
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30 <param name="corData" format="deeptools_coverage_matrix" type="data" label="Matrix file from the multiBamSummary tool"/>
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31 <expand macro="corMethod" />
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32
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33 <conditional name="plotting_type" >
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34 <param argument="--whatToPlot" type="select" label="Plotting type">
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35 <option value="heatmap" selected="True">Heatmap</option>
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36 <option value="scatterplot">Scatterplot</option>
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37 </param>
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38 <when value="heatmap">
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39 <expand macro="heatmap_options" />
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40 </when>
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41 <when value="scatterplot">
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42 <expand macro="plotTitle" />
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43 </when>
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44 </conditional>
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45
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46 <expand macro="skipZeros" />
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47
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48 <expand macro="input_image_file_format" />
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49
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50 <param argument="--removeOutliers" type="boolean"
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51 truevalue="--removeOutliers" falsevalue="" label="Remove regions with very large counts"
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52 help="If set, bins with very large counts are removed. Bins
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53 with abnormally high reads counts artificially
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54 increase pearson correlation; that's why, by default,
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55 plotCorrelation tries to remove outliers using the median
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56 absolute deviation (MAD) method applying a threshold
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57 of 200 to only consider extremely large deviations
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58 from the median. ENCODE blacklist page (https://sites.
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59 google.com/site/anshulkundaje/projects/blacklists)
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60 contains useful information about regions with
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61 unusually high counts."/>
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62
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63 <param name="outFileCorMatrix" type="boolean" label="Save the matrix of values underlying the heatmap"/>
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64
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65 </inputs>
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66 <outputs>
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67 <expand macro="output_image_file_format_not_nested" />
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68 <data format="tabular" name="matrix" label="${tool.name} on ${on_string}: Correlation matrix">
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69 <filter>outFileCorMatrix is True</filter>
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70 </data>
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71 </outputs>
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72 <tests>
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73 <test>
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74 <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
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75 <param name="outFileFormat" value="png" />
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76 <param name="outFileCorMatrix" value="True" />
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77 <output name="matrix" file="plotCorrelation_result1.tabular" ftype="tabular" />
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78 <output name="outFileName" file="plotCorrelation_result1.png" ftype="png" compare="sim_size" delta="300" />
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79 </test>
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80 <test>
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81 <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" />
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82 <param name="outFileFormat" value="png" />
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83 <param name="whatToPlot" value="scatterplot" />
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84 <param name="removeOutliers" value="True" />
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85 <param name="plotTitle" value="Test Plot" />
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86 <output name="outFileName" file="plotCorrelation_result2.png" ftpye="png" compare="sim_size" delta="300" />
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87 </test>
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88 </tests>
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89 <help>
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90 <![CDATA[
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91 What it does
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92 ------------
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93
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94 This tools takes the default output of ``multiBamSummary`` or ``multiBigwigSummary``, and computes the pairwise correlation among samples.
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95 Results can be visualized as **scatterplots** or as a **heatmap** of correlation coefficients (see below for examples).
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96
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97 Theoretical Background
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98 ----------------------
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99
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100 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.)
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101
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102 We offer two different functions for the correlation computation: *Pearson* or *Spearman*.
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103
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104 The *Pearson method* measures the **metric differences** between samples and is therefore influenced by outliers.
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105 The *Spearman method* is based on **rankings**.
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106
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107 Output
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108 ------
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109
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110 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).
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111
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112 Optionally, you can also obtain a table of the pairwise correlation coefficients.
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113
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114 .. image:: $PATH_TO_IMAGES/plotCorrelation_output.png
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115 :width: 600
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116 :height: 271
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117
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118 Example plots
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119 -------------
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120
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121 The following is the output of ``plotCorrelation`` with our test ChIP-Seq datasets (to be found under "Shared Data" --> "Data Library").
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123 Average coverages were computed over 10 kb bins for chromosome X,
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124 from bigWig files using ``multiBigwigSummary``. This was then used with ``plotCorrelation`` to make a heatmap of Spearman correlation coefficients.
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125
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126 .. image:: $PATH_TO_IMAGES/plotCorrelation_galaxy_bw_heatmap_output.png
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127 :width: 600
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128 :height: 518
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129
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130 The scatterplot could look like this:
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131
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132 .. image:: $PATH_TO_IMAGES/plotCorrelation_scatterplot_PearsonCorr_bigwigScores.png
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133 :width: 600
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134 :height: 600
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136 -----
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138 @REFERENCES@
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139 ]]>
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140 </help>
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141 <expand macro="citations" />
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142 </tool>