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comparison plasmidtrakr.xml @ 16:706b2bbc64ed draft

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planemo upload commit e5fa85f6befc345ab8f2b0af283f96834038cefd
author galaxytrakr
date Thu, 30 Apr 2026 19:40:55 +0000
parents 58006290e654
children 36d49a2e6bbe
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15:58006290e654 16:706b2bbc64ed
1 <tool id="plasmidtrakr" name="PlasmidTrakr" version="0.2.1"> 1 <tool id="plasmidtrakr" name="PlasmidTrakr" version="0.2.2">
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. Create a sanitized variable for the input name (removes spaces/special chars for the shell) 11 ## 1. Setup names and database
12 #set $input_name = $assembly_input.element_identifier.replace(" ", "_") 12 #set $input_name = $assembly_input.element_identifier.replace(" ", "_")
13
14 ## 2. Symlink the Mash database
15 ln -s '$mash_database.fields.path' queries.msh && 13 ln -s '$mash_database.fields.path' queries.msh &&
16 14
17 ## 3. Run Mash Screen 15 ## 2. Run Mash Screen
18 ## We redirect the output to a file named after the original input
19 mash screen 16 mash screen
20 -w 17 -w
21 -i $threshold 18 -i $threshold
22 queries.msh 19 queries.msh
23 '$assembly_input' 20 '$assembly_input'
24 > '${input_name}.tabular' 21 > mash_results.tabular
25 && 22 &&
26 23
27 ## 4. Run PlasmidTrakr prediction 24 ## 3. Conditional Logic: Check if Mash produced hits
28 ## We pass the newly named file to the python script 25 ## [ -s file ] checks if file exists and has size > 0
29 python $__tool_directory__/predict_source.py 26 if [ -s mash_results.tabular ]; then
30 -i '${input_name}.tabular' 27 ## Run the prediction script only if there is data
31 -b '$model_selection.fields.path' 28 python $__tool_directory__/predict_source.py
32 -t $threshold 29 -i mash_results.tabular
33 -o '$prediction_output' 30 -b '$model_selection.fields.path'
31 -t $threshold
32 -o '$prediction_output';
33
34 ## Optional: If the script ran but produced no results (e.g. filtered out)
35 ## ensure we still provide the "No Prediction" fallback
36 if [ \$(wc -l < '$prediction_output') -le 1 ]; then
37 echo -e "Run\tPredicted_Source\tConfidence_Score" > '$prediction_output';
38 echo -e "${input_name}\tNo Prediction\t0.0" >> '$prediction_output';
39 fi
40 else
41 ## Skip Python and create the fallback file immediately
42 echo -e "Run\tPredicted_Source\tConfidence_Score" > '$prediction_output';
43 echo -e "${input_name}\tNo Prediction\t0.0" >> '$prediction_output';
44 fi
34 ]]></command> 45 ]]></command>
35
36 46
37 <inputs> 47 <inputs>
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."/> 48 <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."/>
39 49
40 <param name="mash_database" type="select" label="Select Mash Database" help="Choose the pre-computed Mash sketch database to screen against."> 50 <param name="mash_database" type="select" label="Select Mash Database" help="Choose the pre-computed Mash sketch database to screen against.">