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1 <tool id="MaREA RAS Generator" name="Expression2RAS" version="1.0.7">
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2 <description>- Reaction Activity Scores computation</description>
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3 <macros>
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4 <import>marea_macros.xml</import>
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5 </macros>
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6 <requirements>
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7 <requirement type="package" version="1.18.5">numpy</requirement>
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8 <requirement type="package" version="1.4.4">pandas</requirement>
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9 <requirement type="package" version="1.6.3">scipy</requirement>
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10 <requirement type="package" version="4.6.3">lxml</requirement>
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11 <requirement type="package" version="1.1.0">svglib</requirement>
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12 <requirement type="package" version="3.5.67">reportlab</requirement>
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13 </requirements>
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14 <command detect_errors="exit_code">
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15 <![CDATA[
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16 python $__tool_directory__/ras_generator.py
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17 --rules_selector $cond_rule.rules_selector
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18 --input $input
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19 --none $none
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20 --tool_dir $__tool_directory__
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21 --out_log $log
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22 --ras_output $ras_output
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23 #if $cond_rule.rules_selector == 'Custom'
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24 --rule_list $rule_list
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25 --rules_name $rule_list.element_identifier
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26 #end if
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27 ]]>
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28 </command>
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29 <inputs>
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30 <conditional name="cond_rule">
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31 <expand macro="options"/>
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32 <when value="Custom">
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33 <param name="rule_list" argument="--rule_list" type="data" format="tabular, csv, pickle, p, pk" label="Custom rules" />
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34 </when>
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35 </conditional>
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36 <param name="input" argument="--input" type="data" format="tabular, csv, tsv" label="Gene Expression dataset:" />
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37 <param name="name" argument="--name" type="text" label="Dataset's name:" value="Dataset" help="Default: Dataset" />
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38 <param name="none" argument="--none" type="boolean" checked="true" label="(A and NaN) solved as (A)?" />
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39 </inputs>
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40
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41 <outputs>
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42 <data format="txt" name="log" label="Expression2RAS - $name - Log" />
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43 <data format="tabular" name="ras_output" label="$name RAS"/>
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44 </outputs>
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45
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46 <help>
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47 <![CDATA[
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48
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49 What it does
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50 -------------
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51
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52 This tool computes Reaction Activity Scores from gene expression (RNA-seq) dataset(s), as described in Graudenzi et al. Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power. Journal of Biomedical Informatics, 2018, 87: 37-49.
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53
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54 Accepted files:
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55 - A gene expression dataset
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56
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57 Format:
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58 Tab-separated text file reporting the normalized expression level (e.g., TPM, RPKM, ...) of each gene (row) for a given sample (column).
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59 Column header: sample ID.
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60 Row header: gene ID.
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61
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62
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63 Optional files:
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64 - custom GPR (Gene-Protein-Reaction) rules. Two accepted formats:
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65
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66 * (Cobra Toolbox and CobraPy compliant) xml of metabolic model;
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67 * .csv file specifyig for each reaction ID (column 1) the corresponding GPR rule (column 2).
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68
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69 Computation option ‘(A and NaN) solved as (A)’:
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70 In case of missing expression value, referred to as NaN (Not a Number), for a gene joined with an AND operator in a given GPR rule, the rule ‘A and NaN’
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71
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72 If YES is selected: the GPR will be solved as A.
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73
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74 If NO is selected: the GPR will be disregarded tout-court (i.e., treated as NaN).
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75
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76 Example input
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77 -------------
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78
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79 Custom GPR rules:
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80
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81 +------------+--------------------------------------+
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82 | id | rule (with entrez-id |
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83 +============+======================================+
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84 | r1642 | 155060 or 10357 |
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85 +------------+--------------------------------------+
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86 | r1643 | 155060 or 100134869 |
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87 +------------+--------------------------------------+
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88 | r1640 | 155060 and 100134869 or 10357 |
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89 +------------+--------------------------------------+
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90
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91 RNA-seq dataset:
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92
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93 +------------+----------------+----------------+----------------+
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94 | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 |
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95 +============+================+================+================+
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96 | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 |
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97 +------------+----------------+----------------+----------------+
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98 | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 |
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99 +------------+----------------+----------------+----------------+
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100 | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 |
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101 +------------+----------------+----------------+----------------+
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102 | HGNC:9 | 0.456788 | 0.876543 | 0.876542 |
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103 +------------+----------------+----------------+----------------+
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104 | HGNC:23 | 0.876543 | 0.786543 | 0.897654 |
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105 +------------+----------------+----------------+----------------+
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106
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107 ]]>
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108 </help>
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109 <expand macro="citations" />
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110 </tool>
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111
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