Mercurial > repos > recetox > matchms_fingerprint_similarity
view matchms_fingerprint_similarity.xml @ 9:1d3ee4f9f63d draft
planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit b797ce0fea5cb3d9a0cf0ec31a21f9b73f112b4e
author | recetox |
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date | Mon, 15 Jan 2024 12:31:52 +0000 |
parents | 79accd21387c |
children | 5be32c7ce669 |
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<tool id="matchms_fingerprint_similarity" name="matchms fingerprint similarity" version="@TOOL_VERSION@+galaxy0" profile="21.09"> <description>calculate similarity between molecular fingerprints calculated from structural spectrum metadata descriptors</description> <macros> <import>macros.xml</import> <import>help.xml</import> </macros> <expand macro="creator"/> <edam_operations> <edam_operation>operation_0360</edam_operation> </edam_operations> <expand macro="bio.tools"/> <requirements> <requirement type="package" version="@TOOL_VERSION@">matchms</requirement> </requirements> <command detect_errors="exit_code"><![CDATA[ python3 ${python_wrapper} ]]> </command> <configfiles> <configfile name="python_wrapper"> @init_logger@ from matchms.similarity import FingerprintSimilarity similarity = FingerprintSimilarity(similarity_measure="${fingerprint_similarity}") @init_scores@ from matchms.filtering import add_fingerprint import numpy as np name="FingerprintSimilarity_${fingerprint_similarity}" layer = similarity.matrix( references=np.asarray(list(map(add_fingerprint, scores.references))), queries=np.asarray(list(map(add_fingerprint, scores.queries))), array_type = "numpy", is_symmetric=scores.is_symmetric) scores._scores.add_dense_matrix(layer, name) scores.to_json("$scores_out") </configfile> </configfiles> <inputs> <expand macro="input_param"/> <param label="Fingerprint similarity distance" name="fingerprint_similarity" type="select" display="radio" help="Distance measure to use to compute between the molecular fingerprints - see [2] for details regarding the used fingerprint."> <option value="jaccard" selected="true">jaccard</option> <option value="dice">dice</option> <option value="cosine">cosine</option> </param> </inputs> <outputs> <data label="$fingerprint_similarity distance between fingerprints in ${on_string}" name="scores_out" format="json"/> </outputs> <tests> <test> <param name="queries" value="similarity/rcx_gc-ei_ms_subset.msp" ftype="msp"/> <param name="references" value="similarity/rcx_exposome_pesticides_subset.msp" ftype="msp"/> <param name="fingerprint_similarity" value="dice" /> <output name="scores_out" value="fingerprints/dice.json" ftype="json" /> </test> <test> <param name="queries" value="similarity/rcx_gc-ei_ms_subset.msp" ftype="msp"/> <param name="references" value="similarity/rcx_exposome_pesticides_subset.msp" ftype="msp"/> <param name="fingerprint_similarity" value="cosine" /> <output name="scores_out" value="fingerprints/cosine.json" ftype="json" /> </test> <test> <param name="use_scores" value="True"/> <param name="scores_in" value="metadata_match/inner_join_ri_20.json" ftype="json"/> <param name="fingerprint_similarity" value="jaccard" /> <output name="scores_out" value="fingerprints/jaccard_scores.json" ftype="json" /> </test> </tests> <help> Description Molecular fingerprints are a digital representation of a molecule based on specific patterns, such as substructures or physicochemical properties. They usually have a fixed length with each entry representing the presence or absence of a certain attribute. Similarity between molecular fingerprints can serve as a proxy for structural similarity and can therefore be used to compare molecules. .. rubric:: **Footnotes** .. [1] SQL join types explained on LearnSQL_. .. [2] Fingerprint - the `daylight fingerprint`_ is used to compute chemical similarity. Fingerprints are derived from SMILES or InChI structure notations present in the spectrum metadata. .. _LearnSQL: https://learnsql.com/blog/sql-joins-types-explained/ .. _daylight fingerprint: https://www.daylight.com/dayhtml/doc/theory/theory.finger.html @HELP_matchms@ </help> <expand macro="citations"/> </tool>