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comparison plasmidtrakr.xml @ 15:58006290e654 draft

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planemo upload commit 07e8ec488fa1fb8323b5e90bfc9842aa7337b950
author galaxytrakr
date Thu, 30 Apr 2026 19:20:50 +0000
parents 9a84b8511fc2
children 706b2bbc64ed
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14:9a84b8511fc2 15:58006290e654
1 <tool id="plasmidtrakr" name="PlasmidTrakr" version="0.2.0"> 1 <tool id="plasmidtrakr" name="PlasmidTrakr" version="0.2.1">
2 <description>Screens assemblies against a Mash database and predicts isolate source using a trained machine learning model</description> 2 <description>Screens assemblies against a Mash database and predicts isolate source using a trained machine learning model</description>
3 3
4 <requirements> 4 <requirements>
5 <requirement type="package" version="2.3">mash</requirement> 5 <requirement type="package" version="2.3">mash</requirement>
6 <requirement type="package" version="2.3.3">pandas</requirement> 6 <requirement type="package" version="2.3.3">pandas</requirement>
7 <requirement type="package" version="1.6.1">scikit-learn</requirement> 7 <requirement type="package" version="1.6.1">scikit-learn</requirement>
8 </requirements> 8 </requirements>
9 9
10 <command detect_errors="exit_code"><![CDATA[ 10 <command detect_errors="exit_code"><![CDATA[
11 ## 1. Symlink the Mash database from the tool data table 11 ## 1. Create a sanitized variable for the input name (removes spaces/special chars for the shell)
12 #set $input_name = $assembly_input.element_identifier.replace(" ", "_")
13
14 ## 2. Symlink the Mash database
12 ln -s '$mash_database.fields.path' queries.msh && 15 ln -s '$mash_database.fields.path' queries.msh &&
13 16
14 ## 2. Run Mash Screen internally 17 ## 3. Run Mash Screen
18 ## We redirect the output to a file named after the original input
15 mash screen 19 mash screen
16 -w 20 -w
17 -i $threshold 21 -i $threshold
18 queries.msh 22 queries.msh
19 '$assembly_input' 23 '$assembly_input'
20 > mash_results.tabular 24 > '${input_name}.tabular'
21 && 25 &&
22 26
23 ## 3. Run PlasmidTrakr prediction 27 ## 4. Run PlasmidTrakr prediction
28 ## We pass the newly named file to the python script
24 python $__tool_directory__/predict_source.py 29 python $__tool_directory__/predict_source.py
25 -i mash_results.tabular 30 -i '${input_name}.tabular'
26 -b '$model_selection.fields.path' 31 -b '$model_selection.fields.path'
27 -t $threshold 32 -t $threshold
28 -o '$prediction_output' 33 -o '$prediction_output'
29 ]]></command> 34 ]]></command>
35
30 36
31 <inputs> 37 <inputs>
32 <param name="assembly_input" type="data" format="fasta,fasta.gz,fastq,fastq.gz" label="Genome Assembly / Reads" help="The FASTA/FASTQ file containing the isolate sequence."/> 38 <param name="assembly_input" type="data" format="fasta,fasta.gz,fastq,fastq.gz" label="Genome Assembly / Reads" help="The FASTA/FASTQ file containing the isolate sequence."/>
33 39
34 <param name="mash_database" type="select" label="Select Mash Database" help="Choose the pre-computed Mash sketch database to screen against."> 40 <param name="mash_database" type="select" label="Select Mash Database" help="Choose the pre-computed Mash sketch database to screen against.">