Mercurial > repos > iuc > mageck_pathway

annotate mageck_pathway.xml @ 0:c871e57e2abb draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mageck commit 71cef018eec5ee7ff7f3853599c027e80e2637fe
author iuc
date Wed, 14 Feb 2018 06:41:39 -0500
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c871e57e2abb planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mageck commit 71cef018eec5ee7ff7f3853599c027e80e2637fe
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1 <?xml version="1.0"?>
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2 <tool id="mageck_pathway" name="MAGeCK pathway" version="@VERSION@" >
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3 <description>- given a ranked gene list, test whether one pathway is enriched</description>
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4 <macros>
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5 <import>mageck_macros.xml</import>
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6 </macros>
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7 <expand macro="requirements" />
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8 <expand macro="version" />
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9 <command detect_errors="exit_code"><![CDATA[
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11 mageck pathway
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13 --gene-ranking '$gene_ranking'
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14 --gmt-file '$gmt_file'
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15 -n sample1
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17 #if $adv.single_ranking:
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18 --single-ranking
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19 #end if
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20 --method $adv.method
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21 --sort-criteria $adv.sort_criteria
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22 --ranking-column $adv.ranking_column
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23 --ranking-column-2 $adv.ranking_column2
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24 --pathway-alpha $adv.pathway_alpha
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25 --permutation $adv.permutation
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26
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27 ]]></command>
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28 <inputs>
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29 <param name="gene_ranking" argument="--gene-ranking" type="data" format="tabular" label="Gene Ranking file" help="The gene ranking file generated by the gene test step. Only one enrichment comparison will be performed." />
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30 <param name="gmt_file" argument="--gmt-file" type="data" format="tabular" label="Pathway GMT file" help="The pathway file in GMT format. See Help below for more information" />
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31
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32 <section name="adv" title="Advanced Options">
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33 <param name="single_ranking" argument="--single-ranking" type="boolean" truevalue="--single-ranking" falsevalue="" checked="false" optional="true"
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34 label="Single ranking file"
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35 help="The provided file is a (single) gene ranking file, either positive or negative selection. Only one enrichment comparison will be performed. Default: No" />
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36 <param name="method" argument="--method" type="select" label="Method for testing pathway enrichment" >
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37 <option value="gsea" selected="True">GSEA</option>
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38 <option value="rra">RRA</option>
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39 </param>
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40 <expand macro="sort_criteria" />
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41 <param name="ranking_column" argument="--ranking-column" type="data_column" data_ref="gene_ranking" value="2" optional="true"
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42 label="Gene Summary file column" help="Column number or label in gene summary file for gene ranking; can be either an integer of column number, or a string of column label. Default: 2 (the 3rd column)" />
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43 <param name="ranking_column2" argument="--ranking-column-2" type="data_column" data_ref="gene_ranking" value="8" optional="true"
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44 label="Gene Summary file column" help="Column number or label in gene summary file for gene ranking; can be either an integer of column number, or a string of column label. This option is used to determine the column for positive selections and is disabled if --single-ranking is specified. Default: 8 (the 9th column)" />
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45 <param name="pathway_alpha" argument="--pathway-alpha" type="float" min="0" value="0.25" optional="true"
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46 label="Alpha value for RRA pathway enrichment" help="The default alpha value for RRA pathway enrichment. Default: 0.25" />
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47 <param argument="--permutation" type="integer" min="0" value="1000" optional="true" label="Permutation number for GSEA" help="Default: 1000" />
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48 <param name="out_log" type="boolean" truevalue="True" falsevalue="" checked="false"
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49 label="Output logfile" help="This file includes the logging information during the execution. Default: No" />
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50 </section>
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51
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52 </inputs>
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53
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54 <outputs>
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55 <data name="pathway_summary" format="tabular" from_work_dir="*.pathway_summary.txt" label="${tool.name} on ${on_string}: Pathway Summary" />
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56 <data name="log" format="tabular" from_work_dir="*.log" label="${tool.name} on ${on_string}: Log" >
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57 <filter>adv['out_log'] is True</filter>
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58 </data>
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59 </outputs>
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60 <tests>
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61 <test><!-- Ensure MAGeCK's demo1 test works -->
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62 <param name="gene_ranking" ftype="tabular" value="out.test.gene_summary.txt" />
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63 <param name="gmt_file" ftype="tabular" value="in.mageckQC.gmt" />
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64 <param name="ranking_column" value="2" />
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65 <param name="out_log" value="True"/>
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66 <output name="pathway_summary" value="out.pathway.pathway_summary.txt" />
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67 <output name="log" value="out.pathway.log.txt" compare="sim_size" />
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68 </test>
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69 </tests>
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70
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71 <help><![CDATA[
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72 .. class:: infomark
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74 **What it does**
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76 MAGeCK pathway can also invoke robust ranking aggregation (RRA) to test if a pathway is enriched in one particular gene ranking, see **More Information** below.
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78 -----
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80 **Inputs**
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82 **Gene Ranking files**
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84 A gene ranking file is required as input and can be produced using **mageck test**. An example of the gene ranking file (gene summary file) is as follows:
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85
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86 ======= ======= ============= =============== =========== ============ ================= =========== ============= =============== =========== ============ ================= ===========
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87 **id** **num** **neg|score** **neg|p-value** **neg|fdr** **neg|rank** **neg|goodsgrna** **neg|lfc** **pos|score** **pos|p-value** **pos|fdr** **pos|rank** **pos|goodsgrna** **pos|lfc**
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88 ------- ------- ------------- --------------- ----------- ------------ ----------------- ----------- ------------- --------------- ----------- ------------ ----------------- -----------
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89 ESPL1 12 6.4327e-10 7.558e-06 7.9e-05 1 -2.35 11 0.99725 0.99981 0.999992 615 0 -0.07
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90 RPL18 12 6.4671e-10 7.558e-06 7.9e-05 2 -2.12 11 0.99799 0.99989 0.999992 620 0 -0.32
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91 CDK1 12 2.6439e-09 7.558e-06 7.9e-05 3 -1.93 12 1.0 0.99999 0.999992 655 0 -0.12
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92 ======= ======= ============= =============== =========== ============ ================= =========== ============= =============== =========== ============ ================= ===========
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93
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94
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95 **Pathway file**
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96
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97 MAGeCK pathway also requires a pathway file in GMT format. The GMT (Gene Matrix Transposed) file format is a tab delimited file format that describes gene sets and is consistent with the `GMT file in Gene Set Enrichment Analysis (GSEA)`_. In the GMT format, each row represents a gene set, with the first column containing the gene set name, and the second column containing a description for the gene set, followed by the names or ids of the genes in the gene set. You can download different GMT pathway files directly from the `GSEA MSigDB database`_. An example of the GMT format is as follows:
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98
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99 ============= ============================================================= =======================
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100 Gene Set Name Description Genes
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101 ------------- ------------------------------------------------------------- -----------------------
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102 KEGG_RIBOSOME http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_RIBOSOME RPL35 RPL23 RPL3...
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103 ============= ============================================================= =======================
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104
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105 -----
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106
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107 **Outputs**
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108
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109 **Pathway summary file**
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110
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111 An example of the pathway summary output file is as follows:
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112
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113 ============= ======= ============= =========== =============== =========== ============ ================ ============= ============= =========== =============== =========== ============ ================ ===========
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114 **id** **num** **neg|score** **neg|rra** **neg|p-value** **neg|fdr** **neg|rank** **neg|goodgene** **neg|lfc** **pos|score** **pos|rra** **pos|p-value** **pos|fdr** **pos|rank** **pos|goodgene** **pos|lfc**
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115 ------------- ------- ------------- ----------- --------------- ----------- ------------ ---------------- ------------- ------------- ----------- --------------- ----------- ------------ ---------------- -----------
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116 KEGG_RIBOSOME 88 1 0 0 0 1 0 0 1 0 0 0 1 00
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117 ============= ======= ============= =========== =============== =========== ============ ================ ============= ============= =========== =============== =========== ============ ================ ===========
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118
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119 The contents of each column is as follows:
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120
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121 * **id** Gene ID
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122 * **num** The number of targeting sgRNAs for each gene
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123 * **neg|score** The RRA lo value of this gene in negative selection
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124 * **neg|p-value** The raw p-value (using permutation) of this gene in negative selection
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125 * **neg|fdr** The false discovery rate of this gene in negative selection
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126 * **neg|rank** The ranking of this gene in negative selection
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127 * **neg|goodsgrna** The number of "good" sgRNAs, i.e., sgRNAs whose ranking is below the alpha cutoff (determined by the --gene-test-fdr-threshold option), in negative selection.
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128 * **neg|lfc** The log fold change of this gene in negative selection
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129 * **pos|score** The number of targeting sgRNAs for each gene in positive selection (usually the same as num.neg)
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130 * **pos|score** The RRA lo value of this gene in negative selection
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131 * **pos|p-value** The raw p-value of this gene in positive selection
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132 * **pos|fdr** The false discovery rate of this gene in positive selection
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133 * **pos|rank** The ranking of this gene in positive selection
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134 * **pos|goodsgrna** The number of "good" sgRNAs, i.e., sgRNAs whose ranking is below the alpha cutoff (determined by the --gene-test-fdr-threshold option), in positive selection.
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135 * **pos|lfc** The log fold change of this gene in positive selection
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136
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137 Genes are ranked by the p.neg field (by default). If you need a ranking by the p.pos, you can use the --sort-criteria option.
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138
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139 -----
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140
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141 **More Information**
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142
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143 **Overview of the MAGeCK algorithm**
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144
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145 Briefly, read counts from different samples are first median-normalized to adjust for the effect of library sizes and read count distributions. Then the variance of read counts is estimated by sharing information across features, and a negative binomial (NB) model is used to test whether sgRNA abundance differs significantly between treatments and controls. This approach is similar to those used for differential RNA-Seq analysis. We rank sgRNAs based on P-values calculated from the NB model, and use a modified robust ranking aggregation (RRA) algorithm named α-RRA to identify positively or negatively selected genes. More specifically, α-RRA assumes that if a gene has no effect on selection, then sgRNAs targeting this gene should be uniformly distributed across the ranked list of all the sgRNAs. α-RRA ranks genes by comparing the skew in rankings to the uniform null model, and prioritizes genes whose sgRNA rankings are consistently higher than expected. α-RRA calculates the statistical significance of the skew by permutation, and a detailed description of the algorithm is presented in the Materials and methods section of the `MAGeCK paper`_. Finally, MAGeCK reports positively and negatively selected pathways by applying α-RRA to the rankings of genes in a pathway.
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146
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147 For more information on using MAGeCK, see the `MAGeCK website here`_.
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148
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149 .. _`GMT file in Gene Set Enrichment Analysis (GSEA)`: http://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats#GMT:_Gene_Matrix_Transposed_file_format_.28.2A.gmt.29
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150 .. _`GSEA MSigDB database`: http://software.broadinstitute.org/gsea/login.jsp
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151 .. _`MAGeCK paper`: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0554-4
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152 .. _`MAGeCK website here`: https://sourceforge.net/p/mageck/wiki/QA/#using-mageck
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153
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154 ]]></help>
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155 <expand macro="citations" />
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156 </tool>