root/galaxy-central/tools/human_genome_variation/funDo.xml

リビジョン 2, 2.9 KB (コミッタ: hatakeyama, 14 年 前)

import galaxy-central

行番号 
1<tool id="hgv_funDo" name="FunDO" Version="1.0.0">
2  <description>human genes associated with disease terms</description>
3
4  <command interpreter="perl">
5    disease_ontology_gene_fuzzy_selector.pl $build $out_file1 ${GALAXY_DATA_INDEX_DIR}/funDo.loc '$term'
6  </command>
7
8  <inputs>
9    <param name="build" type="select" label="Database build">
10      <options from_file="funDo.loc">
11        <column name="name" index="0"/>
12        <column name="value" index="0"/>
13        <filter type="unique_value" column="0"/>
14      </options>
15    </param>
16    <param name="term" size="40" type="text" label="Disease term(s)" />
17  </inputs>
18
19  <outputs>
20    <data format="interval" name="out_file1">
21    </data>
22  </outputs>
23
24  <tests>
25    <test>
26      <param name="term" value="lung"/>
27      <param name="build" value="hg18"/>
28      <output name="out_file1" file="funDo_output1.interval" />
29    </test>
30  </tests>
31
32  <help>
33**Dataset formats**
34
35There is no input dataset.  The output is in interval_ format.
36
37.. _interval: ./static/formatHelp.html#interval
38
39-----
40
41**What it does**
42
43This tool searches the disease-term field of the DOLite mappings
44used by the FunDO project and returns a set of genes that
45are associated with terms matching the specified pattern.  (This is the
46reverse of what FunDO's own server does.)
47
48The search is case insensitive, and selects terms that contain any of
49the given words, either exactly or within a longer word (e.g. "nemia"
50selects not only "anemia", but also "hyperglycinemia", "tyrosinemias",
51and many other things).  Multiple words should be separated by spaces,
52not commas.  As a special case, entering the word "disease" returns all
53genes associated with any disease, even if that word does not actually
54appear in the term field.
55
56Website: http://django.nubic.northwestern.edu/fundo/
57
58-----
59
60**Example**
61
62Typing::
63
64    carcinoma
65
66results in::
67
68    1.     2.         3.         4. 5.       6.     7.
69    chr11  89507465   89565427   +  NAALAD2  10003  Adenocarcinoma
70    chr15  50189113   50192264   -  BCL2L10  10017  Carcinoma
71    chr7   150535855  150555250  -  ABCF2    10061  Clear cell carcinoma
72    chr7   150540508  150555250  -  ABCF2    10061  Clear cell carcinoma
73    chr10  134925911  134940397  -  ADAM8    101    Adenocarcinoma
74    chr10  134925911  134940397  -  ADAM8    101    Adenocarcinoma
75    etc.
76
77where the column contents are as follows::
78
79 1. chromosome name
80 2. start position of the gene
81 3. end position of the gene
82 4. strand
83 4. gene name
84 6. Entrez Gene ID
85 7. disease term
86
87-----
88
89**References**
90
91Du P, Feng G, Flatow J, Song J, Holko M, Kibbe WA, Lin SM. (2009)
92From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose
93ontology for the test of gene-ontology associations.
94Bioinformatics. 25(12):i63-8.
95
96Osborne JD, Flatow J, Holko M, Lin SM, Kibbe WA, Zhu LJ, Danila MI, Feng G, Chisholm RL. (2009)
97Annotating the human genome with Disease Ontology.
98BMC Genomics. 10 Suppl 1:S6.
99
100  </help>
101</tool>
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