|
51
|
1 <tool id="MaREA RAS Generator" name="Expression2RAS" version="1.0.5">
|
|
47
|
2 <description>- Reaction Activity Scores computation</description>
|
|
45
|
3 <macros>
|
|
|
4 <import>marea_macros.xml</import>
|
|
|
5 </macros>
|
|
|
6 <requirements>
|
|
|
7 <requirement type="package" version="0.23.0">pandas</requirement>
|
|
|
8 <requirement type="package" version="1.1.0">scipy</requirement>
|
|
49
|
9 <requirement type="package" version="0.17.1">cobra</requirement>
|
|
45
|
10 <requirement type="package" version="4.2.1">lxml</requirement>
|
|
|
11 <requirement type="package" version="0.8.1">svglib</requirement>
|
|
|
12 <requirement type="package" version="3.4.0">reportlab</requirement>
|
|
|
13 </requirements>
|
|
|
14 <command detect_errors="exit_code">
|
|
|
15 <![CDATA[
|
|
47
|
16 python $__tool_directory__/ras_generator.py
|
|
|
17 --rules_selector $cond_rule.rules_selector
|
|
|
18 --input $input
|
|
|
19 --none $none
|
|
|
20 --tool_dir $__tool_directory__
|
|
|
21 --out_log $log
|
|
|
22 --ras_output $ras_output
|
|
51
|
23 --custom $cond_rule.Custom_rules
|
|
45
|
24 ]]>
|
|
|
25 </command>
|
|
|
26 <inputs>
|
|
|
27 <conditional name="cond_rule">
|
|
|
28 <expand macro="options"/>
|
|
|
29 <when value="HMRcore">
|
|
|
30 </when>
|
|
|
31 <when value="Recon">
|
|
|
32 </when>
|
|
|
33 <when value="Custom">
|
|
|
34 <param name="Custom_rules" type="data" format="tabular, csv, tsv, xml" label="Custom rules" />
|
|
|
35 </when>
|
|
|
36 </conditional>
|
|
47
|
37 <param name="input" argument="--input" type="data" format="tabular, csv, tsv" label="Gene Expression dataset:" />
|
|
|
38 <param name="name" argument="--name" type="text" label="Dataset's name:" value="Dataset" help="Default: Dataset" />
|
|
|
39 <param name="none" argument="--none" type="boolean" truevalue="true" falsevalue="false" checked="true" label="(A and NaN) solved as (A)?" />
|
|
45
|
40 </inputs>
|
|
|
41
|
|
|
42 <outputs>
|
|
47
|
43 <data format="txt" name="log" label="Expression2RAS - $name - Log" />
|
|
|
44 <data format="tabular" name="ras_output" label="$name RAS"/>
|
|
45
|
45 </outputs>
|
|
47
|
46
|
|
45
|
47 <help>
|
|
|
48 <![CDATA[
|
|
|
49
|
|
|
50 What it does
|
|
|
51 -------------
|
|
48
|
52
|
|
|
53 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.
|
|
|
54
|
|
|
55 Accepted files:
|
|
|
56 - A gene expression dataset
|
|
|
57
|
|
|
58 Format:
|
|
|
59 Tab-separated text file reporting the normalized expression level (e.g., TPM, RPKM, ...) of each gene (row) for a given sample (column).
|
|
|
60 Column header: sample ID.
|
|
|
61 Row header: gene ID.
|
|
|
62
|
|
|
63
|
|
|
64 Optional files:
|
|
|
65 - custom GPR (Gene-Protein-Reaction) rules. Two accepted formats:
|
|
|
66
|
|
|
67 * (Cobra Toolbox and CobraPy compliant) xml of metabolic model;
|
|
|
68 * .csv file specifyig for each reaction ID (column 1) the corresponding GPR rule (column 2).
|
|
|
69
|
|
|
70 Computation option ‘(A and NaN) solved as (A)’:
|
|
|
71 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’
|
|
|
72
|
|
|
73 If YES is selected: the GPR will be solved as A.
|
|
|
74
|
|
|
75 If NO is selected: the GPR will be disregarded tout-court (i.e., treated as NaN).
|
|
|
76
|
|
|
77 Example input
|
|
|
78 -------------
|
|
|
79
|
|
|
80 Custom GPR rules:
|
|
|
81
|
|
|
82 +------------+--------------------------------------+
|
|
|
83 | id | rule (with entrez-id |
|
|
|
84 +============+======================================+
|
|
|
85 | r1642 | 155060 or 10357 |
|
|
|
86 +------------+--------------------------------------+
|
|
|
87 | r1643 | 155060 or 100134869 |
|
|
|
88 +------------+--------------------------------------+
|
|
|
89 | r1640 | 155060 and 100134869 or 10357 |
|
|
|
90 +------------+--------------------------------------+
|
|
|
91
|
|
|
92 RNA-seq dataset:
|
|
|
93
|
|
|
94 +------------+----------------+----------------+----------------+
|
|
|
95 | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 |
|
|
|
96 +============+================+================+================+
|
|
|
97 | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 |
|
|
|
98 +------------+----------------+----------------+----------------+
|
|
|
99 | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 |
|
|
|
100 +------------+----------------+----------------+----------------+
|
|
|
101 | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 |
|
|
|
102 +------------+----------------+----------------+----------------+
|
|
|
103 | HGNC:9 | 0.456788 | 0.876543 | 0.876542 |
|
|
|
104 +------------+----------------+----------------+----------------+
|
|
|
105 | HGNC:23 | 0.876543 | 0.786543 | 0.897654 |
|
|
|
106 +------------+----------------+----------------+----------------+
|
|
|
107
|
|
45
|
108 ]]>
|
|
|
109 </help>
|
|
|
110 <expand macro="citations" />
|
|
|
111 </tool>
|
|
|
112
|
