Mercurial > repos > malex > gait_gm
annotate add_kegg_anno_info.xml @ 2:2c218a253d56 draft default tip
"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
author | malex |
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date | Thu, 29 Jul 2021 20:48:10 +0000 |
parents | ec9ee8edb84d |
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rev | line source |
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1 | 1 <tool id="secimtools_add_kegg_anno_info" name="Link Name to KEGGID" version="@WRAPPER_VERSION@"> |
2 <description></description> | |
3 <macros> | |
4 <import>macros.xml</import> | |
5 </macros> | |
6 <expand macro="requirements" /> | |
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7 <stdio> |
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8 <exit_code range="1" level="fatal" description="Repeated Unique IDs"/> |
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9 </stdio> |
1 | 10 <command detect_errors="exit_code"><![CDATA[ |
11 add_kegg_anno_info.py | |
12 -s=$species | |
13 #if $dataSets.whichDataSet == "geneDataset": | |
14 -ga=$dataSets.geneAnnot | |
15 -gid=$dataSets.geneUniqId | |
16 -gn=$dataSets.geneName | |
17 #end if | |
18 #if $dataSets.whichDataSet == "metDataset": | |
19 -ma=$dataSets.metAnnot | |
20 -mid=$dataSets.metUniqId | |
21 -mn=$dataSets.metName | |
22 #end if | |
23 #if $dataSets.whichDataSet == "geneDataset,metDataset": | |
24 -ga=$dataSets.geneAnnot | |
25 -gid=$dataSets.geneUniqId | |
26 -gn=$dataSets.geneName | |
27 -ma=$dataSets.metAnnot | |
28 -mid=$dataSets.metUniqId | |
29 -mn=$dataSets.metName | |
30 #end if | |
31 -go=$geneOutput | |
32 -mo=$metOutput | |
33 ]]></command> | |
34 <inputs> | |
35 <param name="species" type="select" label="Select Species from the list" > | |
36 <option value="hsa">Homo sapiens</option> | |
37 <option value="mmu">Mus musculus</option> | |
38 <option value="rno">Rattus norvegicus</option> | |
39 <option value="dme">Drosophila melanogaster</option> | |
40 <option value="ath">Arabidopsis thaliana</option> | |
41 <option value="sce">Saccharomyces cerevisiae</option> | |
42 <option value="eco">Escherichia coli</option> | |
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43 <option value="cel">Caenorhabditis elegans</option> |
1 | 44 </param> |
45 <conditional name="dataSets"> | |
46 <param name="whichDataSet" type="select" display="radio" label="Select Annotation Dataset(s)"> | |
47 <option value="geneDataset,metDataset" selected="true">Gene Expression + Metabolomic Annotation Datasets</option> | |
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48 <option value="geneDataset">Gene Expression Annotation Dataset</option> |
1 | 49 <option value="metDataset">Metabolomic Annotation Dataset</option> |
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50 <validator type="no_options" message="You must select at least one option." /> |
1 | 51 </param> |
52 <when value="geneDataset"> | |
53 <param name="geneAnnot" type="data" format="tabular" label="Select the Gene Expression Annotation dataset from your History"/> | |
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54 <param name="geneUniqId" type="text" size="30" value="" label="Gene Unique FeatureID" help="Name of the column in your Gene Expression Annotation dataset that contains the unique FeatureIDs."/> |
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55 <param name="geneName" type="text" size="30" value="" label="Gene Symbol" help="Name of the column in your Gene Expression Annotation dataset that contains Gene Symbols to use for linking to KEGGIDs."/> |
1 | 56 </when> |
57 <when value="metDataset"> | |
58 <param name="metAnnot" type="data" format="tabular" label="Select the Metabolomic Annotation dataset from your History" /> | |
59 <param name="metUniqId" type="text" size="30" value="" label="Metabolite Unique FeatureID" help="Name of the column in your Metabolomic Annotation dataset that contains the unique FeatureIDs."/> | |
60 <param name="metName" type="text" size="30" value="" label="Metabolite Names" help="Name of the column in your Metabolomic Annotation dataset that has metabolite names to use for linking to KEGGIDs."/> | |
61 </when> | |
62 <when value="geneDataset,metDataset"> | |
63 <param name="geneAnnot" type="data" format="tabular" label="Select the Gene Expression Annotation dataset from your History"/> | |
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64 <param name="geneUniqId" type="text" size="30" value="" label="Gene Unique FeatureID" help="Name of the column in your Gene Expression Annotation dataset that contains the unique FeatureIDs."/> |
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65 <param name="geneName" type="text" size="30" value="" label="Gene Symbol" help="Name of the Column in your Gene Expression Annotation dataset that contains Gene Symbols to use for linking to KEGGIDs."/> |
1 | 66 <param name="metAnnot" type="data" format="tabular" label="Select the Metabolomic Annotation dataset from your History" /> |
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67 <param name="metUniqId" type="text" size="30" value="" label="Metabolite Unique FeatureID" help="Name of the Column in your Metabolomic Annotation dataset that contains the unique FeatureIDs."/> |
1 | 68 <param name="metName" type="text" size="30" value="" label="Metabolite Names" help="Name of the Column in your Metabolomic Annotation dataset that has metabolite names to use for linking to KEGGIDs."/> |
69 </when> | |
70 </conditional> | |
71 </inputs> | |
72 <outputs> | |
73 <data format="tabular" name="geneOutput" label="${tool.name} on ${on_string}: Gene to KEGGID link"> | |
74 <filter>(dataSets['whichDataSet'] == 'geneDataset') or (dataSets['whichDataSet'] == 'geneDataset,metDataset')</filter> | |
75 </data> | |
76 <data format="tabular" name="metOutput" label="${tool.name} on ${on_string}: Metabolite to KEGGID link"> | |
77 <filter>(dataSets['whichDataSet'] == 'metDataset') or (dataSets['whichDataSet'] == 'geneDataset,metDataset')</filter> | |
78 </data> | |
79 </outputs> | |
80 <tests> | |
81 <test> | |
82 <param name="species" value="rno"/> | |
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83 <param name="geneAnnot" value="ensembl2symbol_annotation.tsv"/> |
1 | 84 <param name="geneUniqId" value="UniqueID"/> |
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85 <param name="geneName" value="GeneName"/> |
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86 <param name="metAnnot" value="metabolite_annotation.tsv"/> |
1 | 87 <param name="metUniqId" value="UniqueID"/> |
88 <param name="metName" value="MetName"/> | |
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89 <output name="geneOutput" value="gene_to_keggId_link.tsv" compare="diff" lines_diff="100000"/> |
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90 <output name="metOutput" value="metabolite_to_keggId_link.tsv" compare="diff" lines_diff="10000"/> |
1 | 91 </test> |
92 </tests> | |
93 <help><![CDATA[ | |
94 | |
95 **Tool Description** | |
96 | |
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97 This tool takes an annotation dataset containing metabolite compound names or gene symbols and links them to identifiers in KEGG (KEGGIDs) |
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98 creating either: |
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99 (a) a Gene to KEGGID Link or |
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100 (b) a Metabolite to KEGGID Link dataset. |
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101 |
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102 For gene expression data, the tool is designed to |
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"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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103 take the output from the 'Map ENSEMBLIDs to Gene Symbols' tool as input. If your input dataset |
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104 contains a Selected column, the tool will |
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105 link GeneSymbols to KEGGIDs where Selected = 'Yes'. Input Files without a Selected column must |
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106 have a column containing unique FeatureIDs. |
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107 This tool takes an annotation dataset containing unique FeatureIDs, ENSEMBLIDs (for gene |
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108 expression data) and GeneSymbol/MetaboliteName |
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109 and adds the following columns: |
1 | 110 |
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111 1) Name_in_KEGG, the name found in KEGG |
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112 2) Matched, a column indicating whether a match was found in KEGG, |
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113 3) KEGGID, the KEGG identifier for the Match |
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114 4) Score, a similarity score representing match similarity (calculated using the python internal function SequenceMatcher from difflib (check) |
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115 5) a Tie column to indicate if a gene symbol or metabolite name matched more than one KEGGID. |
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116 |
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117 User-specified metabolite names are linked to KEGGIDs by identifying the best match using the following procedure: Common metabolite prefixes |
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118 are removed (cis-, trans-, d- , l- , (s)-, alpha-, beta-, alpha, beta, alpha-d-, beta-d-, alpha-l-, beta-l-, l-beta-, l-alpha-, d-beta-, d-alpha-). |
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119 If the metabolite name given is an acid, then the name is modified to the conjugate base by replacing “ic acid”, “icacid” or “ic_acid” with “ate”. |
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120 If amino acids are given in 1-letter or 3-letter abbreviations, names are modified to the full amino acid name. The following commonly used lipid |
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121 abbreviations are modified to reflect the full names (SM = sphingomyelin, lysopc = lysophosphatidylcholine, PC = phosphatidylcholine, |
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122 PE = phosphatidylethanolamine and LysoPE = lysophosphatidylethanolamine). Similarly, abbreviations for other commonly assayed metabolites are |
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123 modified to reflect the full names (cit = citrate, orn = ornithine, thyr = thyroxine and boc = butoxycarbonyl). The code allows the addition of |
1 | 124 more synonyms. The user-specified metabolite names are retained in the output dataset for comparisons with the KEGG database. |
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125 |
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126 Each parsed metabolite name is compared to metabolite names in KEGG. The best match in KEGG based on similarity score is returned. The similarity |
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127 score (Score column) is based on the longest contiguous matching subsequence that does not contain 'junk' elements, where 'junk' elements are defined |
1 | 128 as duplicates making up more than 1% of a sequence with minimum length of 200 (python SequenceMatcher class from difflib) |
129 | |
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130 Selected = Yes for the match with the highest similarity score. |
1 | 131 |
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132 For metabolite names where the best match is tied with at least one other compound in KEGG, all matches are returned. A tie is determined as follows: |
1 | 133 if the Score is greater than 95% for 2 or more matches in the metabolite name then: |
134 1) the Tie column = 'Yes' and a warning message will appear | |
135 2) the Selected column is sorted alphabetically on the Name_in_KEGG column. Note that the user-specified FeatureID and MetaboliteName may not be unique in the resulting output dataset. | |
136 | |
137 -------------------------------------------------------------------------------- | |
138 | |
139 **INPUT** | |
140 | |
141 **Annotation File** | |
142 | |
143 +-------------+--------------+-----+ | |
144 | FeatureID | Name | ... | | |
145 +=============+==============+=====+ | |
146 | FeatureID_1 | one | ... | | |
147 +-------------+--------------+-----+ | |
148 | FeatureID_2 | two | ... | | |
149 +-------------+--------------+-----+ | |
150 | FeatureID_3 | three | ... | | |
151 +-------------+--------------+-----+ | |
152 | FeatureID_4 | four | ... | | |
153 +-------------+--------------+-----+ | |
154 | ... | ... | ... | | |
155 +-------------+--------------+-----+ | |
156 | |
157 **NOTE:** This dataset must contain at least two columns, a column of FeatureIDs and a column containing names (e.g. gene symbol or compound names) to use for linking to KEGGIDs. Other columns may be present in the dataset. The user can use a Gene Expression Annotation dataset, a Metabolomic Annotation dataset or both. | |
158 | |
159 **Unique FeatureID** | |
160 | |
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161 Name of the column in your gene expression or metabolomic Annotation dataset that contains the Unique FeatureIDs. |
1 | 162 |
163 **Gene Symbol or Metabolite Names** | |
164 | |
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165 Name of the column in your gene expression or metabolomic Annotation dataset with the names to use for matching to KEGGIDs. |
1 | 166 |
167 -------------------------------------------------------------------------------- | |
168 | |
169 **OUTPUT** | |
170 | |
171 For each input Annotation file, a TSV file containing the following columns is generated: | |
172 | |
173 (1) **unique FeatureID:** column from the Annotation dataset containing the unique FeatureIDs. | |
174 (2) **Name:** column from Annotation dataset used for matching in KEGG. | |
175 (3) **Feature_Type:** column indicating whether matching was for metabolites or genes. | |
176 (4) **Matched:** column indicating whether a match in KEGG was found. Yes/No | |
177 (5) **Name_in_KEGG:** column containing the KEGG name for the match. | |
178 (6) **KEGGID:** column containing the KEGG identifier for the match. | |
179 (7) **Similarity:** value indicating the similarity between the given feature and the match in KEGG. Ranges from 0 to 1. | |
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180 (8) **Tie:** in cases where multiple matches are found for a given feature, Tie = yes if the similarity is greater than 95%. |
1 | 181 (9) **Selected:** for features with multiple matches and different similarity scores, the 'Selected' column = yes for the match with the highest similarity score. For features with multiple matches and the same similarity score, the 'Selected' column = yes based on the alphabetical order of the returned match. |
182 | |
183 | |
184 **Example Metabolite to KEGGID Link Table** | |
185 | |
186 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
187 | FeatureID | Name | Feature_Type | Matched | Name_in_KEGG | KEGG_ID | Similarity | Tie | Selected | | |
188 +=============+============+==============+=========+==============+==========+============+=====+==========+ | |
189 | FeatureID_1 | one | Metabolite | Yes | one* | cpd:... | 1.0 | No | Yes | | |
190 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
191 | FeatureID_2 | two | Metabolite | Yes | two* | cpd:... | 1.0 | No | Yes | | |
192 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
193 | FeatureID_3 | two | Metabolite | Yes | three* | cpd:... | 0.87 | No | No | | |
194 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
195 | FeatureID_4 | four | Metabolite | No | NA | NA | NA | NA | NA | | |
196 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
197 | ... | ... | ... | ... | ... | ... | ... | ... | ... | | |
198 +-------------+------------+--------------+---------+--------------+----------+------------+-----+----------+ | |
199 | |
200 **NOTE:** Warning messages appear in cases of a Tie (greater than 95% similarity). Please check these results carefully. | |
201 | |
202 ]]> | |
203 </help> | |
204 <citations> | |
205 <citation type="bibtex">@ARTICLE{Kirpich17secimtools, | |
206 author = {Alexander S. Kirpich, Miguel Ibarra, Oleksandr Moskalenko, Justin M. Fear, Joseph Gerken, Xinlei Mi, Ali Ashrafi, Alison M. Morse, Lauren M. McIntyre}, | |
207 title = {SECIMTools: A suite of Metabolomics Data Analysis Tools}, | |
208 journal = {BMC Bioinformatics}, | |
2
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209 year = {2018} |
1 | 210 }</citation> |
2
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"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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211 <citation type="bibtex">@article{Mor2021GaitGM, |
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"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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212 title={GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease}, |
2c218a253d56
"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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213 author={Mor, DE and Huertas, F and Morse, AM and Kaletsky, R and Murphy, CT and Kalia, V and Miller, GW and Moskalenko, O and Conesa, A and McIntyre, LM}, |
2c218a253d56
"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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214 journal={BMC Genomics}, |
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"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
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215 year={submitted}, |
1 | 216 }</citation> |
217 </citations> | |
218 </tool> |