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planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/ipapy2 commit 64b61ff2823b4f54868c0ab7a4c0dc49eaf2979a
author recetox
date Fri, 16 May 2025 08:01:15 +0000
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1 <tool id="ipapy2_MS2_annotation" name="ipaPy2 MS2 annotation" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
2 <description>annotate features from MS2 using a supplied MS2 database</description>
3 <macros>
4 <import>macros.xml</import>
5 </macros>
6
7 <expand macro="requirements"/>
8
9 <command detect_errors="exit_code"><![CDATA[
10 #set $computed_ppmthr = float($ppm) * 2
11 python3 '${__tool_directory__}/ipapy2_MS2_annotation.py'
12 --input_dataset_mapped_isotope_patterns '${mapped_isotope_patterns}' '${mapped_isotope_patterns.ext}'
13 --input_dataset_MS2 '${MS2_fragmentation_data}' '${MS2_fragmentation_data.ext}'
14 --input_dataset_adducts '${all_adducts}' '${all_adducts.ext}'
15 --input_dataset_MS2_DB '${MS2_DB}' '${MS2_DB.ext}'
16 --ppm ${ppm}
17 --ratiosd ${ratiosd}
18 #if $ppmunk
19 --ppmunk ${ppmunk}
20 #else
21 --ppmunk ${ppm}
22 #end if
23 --ratiounk ${ratiounk}
24 #if $ppmthr
25 --ppmthr ${ppmthr}
26 #else
27 --ppmthr ${computed_ppmthr}
28 #end if
29 --pRTNone ${pRTNone}
30 --pRTout ${pRTout}
31 --mzdCS ${mzdCS}
32 --ppmCS ${ppmCS}
33 --CSunk ${CSunk}
34 --evfilt ${evfilt}
35 --output_dataset '${MS2_annotations}' '${MS2_annotations.ext}'
36 --ncores \${GALAXY_SLOTS:-1}
37 ]]></command>
38
39 <inputs>
40 <param label="Mapped isotope patterns" name="mapped_isotope_patterns" type="data" format="csv,tsv,tabular,parquet" help="A dataset containing the MS1 data. Ideally obtained from map_isotope_patterns" />
41 <param label="MS2 fragmentation data" name="MS2_fragmentation_data" type="data" format="csv,tsv,tabular,parquet" help="A dataset containing the MS2 data. (If a csv file fails kindly use a tsv file.)" />
42 <param label="all possible adducts table" name="all_adducts" type="data" format="csv,tsv,tabular,parquet" help="A dataset containing the information on all the possible adducts given the database." />
43 <param label="MS2 Database" name="MS2_DB" type="data" format="csv,tsv,tabular,parquet" help="A dataset containing the database containing the MS2 information." />
44 <expand macro="ppm"/>
45 <section name="unknown" title="unknown settings">
46 <expand macro="ms_unknown"/>
47 <param name="CSunk" type="float" value="0.7">
48 <label>cosine similarity for unknown</label>
49 <help>cosine similarity score associated with the 'unknown' annotation. Default 0.7.</help>
50 </param>
51 </section>
52
53 <section name="optional_settings" title="optional settings">
54 <expand macro="ms_options"/>
55 <param name="mzdCS" type="integer" value="0" label="MS2 mz threshold">
56 <help>maximum mz difference allowed when computing cosine similarity scores.
57 If one wants to use this parameter instead of ppmCS, this must be set to 0. Default 0.</help>
58 </param>
59 <param name="ppmCS" type="integer" value="10" label="maximum ppm for cosine similarity scores">
60 <help>maximum ppm allowed when computing cosine similarity scores.
61 If one wants to use this parameter instead of mzdCS, this must be set to 0. Default 10.</help>
62 </param>
63 <param name="evfilt" type="select" label="same collision energy">
64 <help>If true, only spectrum acquired with the same collision energy are considered. Default value False.</help>
65 <option value="False">False</option>
66 <option value="True">True</option>
67 </param>
68 </section>
69 </inputs>
70
71 <outputs>
72 <data label="${tool.name} on ${on_string}" name="MS2_annotations" format_source="mapped_isotope_patterns"/>
73 </outputs>
74
75 <tests>
76 <test>
77 <param name="mapped_isotope_patterns" value="mapped_isotope_patterns.csv"/>
78 <param name="MS2_fragmentation_data" value="MS2_fragmentation_data.tsv"/>
79 <param name="all_adducts" value="all_adducts.csv"/>
80 <param name="MS2_DB" value="MS2_DB.csv"/>
81 <param name="ppm" value="3"/>
82 <output name="MS2_annotations">
83 <assert_contents>
84 <has_n_columns n="13" sep=","/>
85 <has_n_lines n="158" delta="5" />
86 </assert_contents>
87 </output>
88 </test>
89 </tests>
90
91 <help><![CDATA[
92
93 .. _ipapy2_ms2_annotation:
94
95 ==========================
96 ipaPy2 MS2 Annotation Tool
97 ==========================
98
99 **Tool Description**
100
101 This tool performs annotation of features in your dataset using MS2 fragmentation data and a supplied MS2 database. It integrates MS1 and MS2 information to provide high-confidence annotations, leveraging prior and posterior probabilities based on mass, retention time (RT), known chemical knowledge, and isotope patterns.
102
103 How it works
104 ------------
105
106 - **Prior probabilities** are calculated using only the mass information.
107 - **Posterior probabilities** incorporate mass, RT, prior knowledge, and isotope patterns for more accurate annotation.
108 - The tool matches features in your data to entries in the MS2 database, considering user-defined tolerances for mass (ppm), retention time, and cosine similarity thresholds for spectral matching.
109
110 Inputs
111 ------
112
113 1. **Mapped isotope patterns**
114 Dataset containing MS1 data, ideally obtained from the ``map_isotope_patterns`` tool.
115
116 2. **MS2 fragmentation data**
117 Dataset with MS2 spectra. If a CSV file fails, try using a TSV file.
118
119 3. **All possible adducts table**
120 Table listing all possible adducts for the database.
121
122 4. **MS2 Database**
123 Reference database containing MS2 information for annotation.
124
125 5. **Parameters**
126 - **ppm**: Mass tolerance in parts per million for matching.
127 - **Cosine similarity thresholds**:
128 - ``mzdCS``: Maximum m/z difference for cosine similarity (set to 0 to use ``ppmCS``).
129 - ``ppmCS``: Maximum ppm for cosine similarity (set to 0 to use ``mzdCS``).
130 - **evfilt**: If set to True, only spectra acquired with the same collision energy are considered.
131 - **Unknown settings**: Parameters for handling unknowns, such as cosine similarity threshold for unknown annotations.
132
133 Outputs
134 -------
135
136 - **MS2_annotations**
137 Annotated dataset with additional columns describing the best-matching database entries, probabilities, and spectral similarity scores.
138
139 Example
140 -------
141
142 Suppose you have mapped isotope patterns, MS2 fragmentation data, a list of all adducts, and an MS2 database. You can use this tool to annotate your features as follows:
143
144 .. code-block::
145
146 mapped_isotope_patterns.csv
147 MS2_fragmentation_data.tsv
148 all_adducts.csv
149 MS2_DB.csv
150
151 Set the desired tolerances (e.g., ``ppm = 3``) and run the tool. The output will be a table with annotations for each feature.
152
153 Notes
154 -----
155
156 - For best results, ensure your input files are correctly formatted and contain the required columns.
157 - If you encounter issues with CSV files, try converting them to TSV format.
158 - The tool is designed to be flexible and can handle various input formats (CSV, TSV, Parquet, Tabular).
159
160 References
161 ----------
162
163 - For more details on the annotation algorithm and scoring, refer to the ipaPy2 documentation or associated publications.
164
165 ]]></help>
166
167 <expand macro="citations"/>
168 </tool>