Mercurial > repos > bgruening > deeptools_plot_correlation
annotate plotCorrelation.xml @ 17:90d5df0a49bd draft
planemo upload for repository https://github.com/deeptools/deepTools/tree/master/galaxy/wrapper/ commit b1f975422b307927bbbe245d57609e9464d5d5c8-dirty
author | bgruening |
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date | Thu, 15 Feb 2018 05:49:05 -0500 |
parents | d40bd147adf3 |
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planemo upload for repository https://github.com/fidelram/deepTools/tree/master/galaxy/wrapper/ commit 09975f870c75347fba5c6777c9f3b442bdeeb289
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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 --plotWidth $plotting_type.plotWidth |
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18 --plotHeight $plotting_type.plotHeight |
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19 #else: |
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20 --plotTitle '$plotting_type.plotTitle' |
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21 #if str($plotting_type.maxRange) != '': |
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22 --maxRange '$plotting_type.maxRange' |
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23 #end if |
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24 $plotting_type.log1p |
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25 #end if |
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26 $skipZeros |
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27 --plotFileFormat "$outFileFormat" |
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28 $removeOutliers |
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29 #if $outFileCorMatrix: |
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30 --outFileCorMatrix "$matrix" |
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31 #end if |
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32 |
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33 ]]> |
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34 </command> |
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35 <inputs> |
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36 <param name="corData" format="deeptools_coverage_matrix" type="data" label="Matrix file from the multiBamSummary tool"/> |
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37 <expand macro="corMethod" /> |
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38 |
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39 <conditional name="plotting_type" > |
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40 <param argument="--whatToPlot" type="select" label="Plotting type"> |
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41 <option value="heatmap" selected="True">Heatmap</option> |
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42 <option value="scatterplot">Scatterplot</option> |
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43 </param> |
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44 <when value="heatmap"> |
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45 <expand macro="heatmap_options" /> |
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46 <expand macro="plotWidthHeight" PLOTWIDTH="11.0" PLOTHEIGHT="9.5" /> |
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47 </when> |
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48 <when value="scatterplot"> |
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49 <expand macro="plotTitle" /> |
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50 <param argument="--maxRange" type="integer" value="" optional="true" |
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51 label="Maximum Range" |
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52 help="Maximum (integer) value for the X and Y axes. The default scales these such that the full range of dots is displayed. If you specify --log1p, please ensure that this value is within the range it will produce." /> |
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53 <param argument="--log1p" type="boolean" truevalue="--log1p" falsevalue="" |
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54 label="Log transform" |
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55 help="Plot the natural log of the scatter plot after adding 1. Note that this is ONLY for plotting, the correlation is unaffected." /> |
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56 </when> |
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57 </conditional> |
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58 |
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59 <expand macro="skipZeros" /> |
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60 |
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61 <expand macro="input_image_file_format" /> |
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62 |
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63 <param argument="--removeOutliers" type="boolean" |
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64 truevalue="--removeOutliers" falsevalue="" label="Remove regions with very large counts" |
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65 help="If set, bins with very large counts are removed. Bins |
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66 with abnormally high reads counts artificially |
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67 increase pearson correlation; that's why, by default, |
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68 plotCorrelation tries to remove outliers using the median |
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69 absolute deviation (MAD) method applying a threshold |
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70 of 200 to only consider extremely large deviations |
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71 from the median. ENCODE blacklist page (https://sites. |
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72 google.com/site/anshulkundaje/projects/blacklists) |
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73 contains useful information about regions with |
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74 unusually high counts."/> |
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75 |
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76 <param name="outFileCorMatrix" type="boolean" label="Save the matrix of values underlying the heatmap"/> |
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77 |
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78 </inputs> |
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79 <outputs> |
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80 <expand macro="output_image_file_format_not_nested" /> |
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81 <data format="tabular" name="matrix" label="${tool.name} on ${on_string}: Correlation matrix"> |
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82 <filter>outFileCorMatrix is True</filter> |
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83 </data> |
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84 </outputs> |
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85 <tests> |
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86 <test> |
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87 <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" /> |
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88 <param name="outFileFormat" value="png" /> |
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89 <param name="outFileCorMatrix" value="True" /> |
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90 <output name="matrix" file="plotCorrelation_result1.tabular" ftype="tabular" /> |
17
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91 <output name="outFileName" file="plotCorrelation_result1.png" ftype="png" compare="sim_size" delta="400" /> |
12
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92 </test> |
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93 <test> |
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94 <param name="corData" value="multiBamSummary_result1.npz" ftype="deeptools_coverage_matrix" /> |
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95 <param name="outFileFormat" value="png" /> |
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96 <param name="whatToPlot" value="scatterplot" /> |
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97 <param name="removeOutliers" value="True" /> |
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98 <param name="plotTitle" value="Test Plot" /> |
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99 <output name="outFileName" file="plotCorrelation_result2.png" ftype="png" compare="sim_size" delta="300" /> |
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100 </test> |
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101 </tests> |
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102 <help> |
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103 <![CDATA[ |
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104 What it does |
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105 ------------ |
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106 |
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107 This tools takes the default output of ``multiBamSummary`` or ``multiBigwigSummary``, and computes the pairwise correlation among samples. |
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108 Results can be visualized as **scatterplots** or as a **heatmap** of correlation coefficients (see below for examples). |
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109 |
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110 Theoretical Background |
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111 ---------------------- |
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112 |
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113 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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114 |
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115 We offer two different functions for the correlation computation: *Pearson* or *Spearman*. |
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116 |
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117 The *Pearson method* measures the **metric differences** between samples and is therefore influenced by outliers. |
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118 The *Spearman method* is based on **rankings**. |
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119 |
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120 Output |
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121 ------ |
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122 |
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123 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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124 |
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125 Optionally, you can also obtain a table of the pairwise correlation coefficients. |
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126 |
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127 .. image:: $PATH_TO_IMAGES/plotCorrelation_output.png |
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128 :width: 600 |
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129 :height: 271 |
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130 |
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131 Example plots |
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132 ------------- |
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133 |
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134 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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135 |
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136 Average coverages were computed over 10 kb bins for chromosome X, |
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137 from bigWig files using ``multiBigwigSummary``. This was then used with ``plotCorrelation`` to make a heatmap of Spearman correlation coefficients. |
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138 |
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139 .. image:: $PATH_TO_IMAGES/plotCorrelation_galaxy_bw_heatmap_output.png |
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140 :width: 600 |
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141 :height: 518 |
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142 |
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143 The scatterplot could look like this: |
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144 |
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145 .. image:: $PATH_TO_IMAGES/plotCorrelation_scatterplot_PearsonCorr_bigwigScores.png |
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146 :width: 600 |
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147 :height: 600 |
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148 |
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149 ----- |
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150 |
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151 @REFERENCES@ |
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152 ]]> |
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153 </help> |
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154 <expand macro="citations" /> |
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155 </tool> |