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comparison coVennTree/coVennTree.xml @ 0:745aede829e9 draft default tip

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author steffen
date Fri, 30 Jan 2015 09:55:45 -0500
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1 <tool id="coVennTree" name="CoVennTree (Comparative weighted Venn Tree) - Rooted Tree" version="1.6.0">
2 <description>Comparative rooted tree analysis for files in dsv format</description>
3 <requirements>
4 <requirement type="package" version="1.6">coVennTree</requirement>
5 <requirement type="package" version="5.18.1">perl</requirement>
6 </requirements>
7 <command interpreter="perl">
8 coVennTree.pl
9 $infile
10 $color_mode
11 $trans_func
12 $leafs_allInformation
13 $outfile_network
14 $outfile_attribute
15 </command>
16
17 <inputs>
18 <param name="infile" type="data" format="tabular" label="Path File" help="Tabular file containing the paths and values"/>
19
20
21 <param name="color_mode" multiple="false" type="select" label="Select color mode for Venn diagrams">
22 <option value="0">(1) Set1: blue Set2: red Set3: yellow</option>
23 <option value="1">(2) Set1: red Set2: green Set3: blue</option>
24 <option value="2">(3) Set1: green Set2: magenta Set3: blue</option>
25 <option value="3">(4) Set1: green Set2: purple Set3: red</option>
26 <option value="4">(5) Set1: dark gray Set2: mid-grey Set3: light gray</option>
27 </param>
28
29
30 <param name="trans_func" multiple="false" type="select" label="Select transformation function">
31 <option value="0">(1) datasets max: 3,000 data points in sum</option>
32 <option value="1">(2) datasets max: 30,000 data points in sum</option>
33 <option value="2">(3) datasets max: 300,000 data points in sum</option>
34 <option value="3">(4) datasets max: 3,000,000 data points in sum</option>
35 <option value="4">(5) datasets max: 30,000,000 data points in sum</option>
36 <option value="5">(6) datasets max: 300,000,000 data points in sum</option>
37 <option value="6">(7) datasets max: 3,000,000,000 data points in sum</option>
38 </param>
39
40
41 <param name="leafs_allInformation" multiple="false" type="select" label="Select tree analyzes function">
42 <option value="1">(1) leaf + inner nodes informations</option>
43 <option value="0">(2) only leaf information</option>
44 </param>
45
46 </inputs>
47
48 <outputs>
49 <data format="tabular" name="outfile_network" label="Network" />
50 <data format="tabular" name="outfile_attribute" label="Attributes" />
51 </outputs>
52
53 <tests>
54 <test>
55 </test>
56 </tests>
57
58 <help>
59 .. class:: infomark
60
61 CoVennTree compares up to three rooted trees at the same time.
62
63 CoVennTree (Comparative weighted Venn Tree) is a software to analyze and compare up to three datasets. Unlike other
64 methods, CoVennTree correlates data on the leaf level and transfers this information to the root node. CoVennTree works with numbers to compute weighted
65 Venn diagrams for each node in the graph (rooted tree). Therefore any kind of input data can be processed as long as the data structure will be taken into account.
66
67
68
69 **Input**
70
71 *Input example*
72
73
74 .. image:: $PATH_TO_IMAGES/example1.png
75 :height: 430
76 :width: 600
77
78
79 *dsv-format: The following table represents the graph.*
80
81
82 =========== ====== ====== ======
83 #Datasets set1 set2 set3
84 =========== ====== ====== ======
85 "root;" 0 0 0
86 "root;A;" 10000 0 0
87 "root;A;C;" 600000 300000 500000
88 "root;A;D;" 0 100000 200000
89 "root;A;E;" 800000 0 100000
90 "root;B;" 10000 20000 50000
91 =========== ====== ====== ======
92
93
94 -------
95
96
97 **Results**
98
99 A specific color is assigned to each dataset in five optional color schemes (see parameter "Select color mode for weighted Venn diagrams").
100 In this example set1 corresponds to color blue, set2 to red and set3 to yellow.
101 In order to cover a wide numerical range a non linear transformation function is used.
102
103
104 *Data format \*.sif*
105
106 [parent_node] [connected_with] [child_node]
107
108
109 *Data format \*.venn*
110
111 [id] [google_url] [id_vds] [Venn_abs_values]
112
113
114 *Output example "leaf information and not assigned information"*
115
116 By selecting "leaf information + not assigned information" artificial nodes can be inserted.
117 Artificial nodes will be inserted if inner nodes have values larger than zero.
118
119 .. image:: $PATH_TO_IMAGES/venn-graph-off.png
120 :height: 358
121 :width: 425
122
123
124 -------
125
126
127 *Output example "only leaf information"*
128
129 By selecting "only leaf information" only leaf nodes are considered for the computation of weighted Venn diagrams.
130
131 .. image:: $PATH_TO_IMAGES/venn-graph-on.png
132 :height: 358
133 :width: 400
134
135
136
137 </help>
138 <citations>
139 <citation type="doi">
140
141 </citation>>
142 </citations>
143 </tool>