diff virhunter.xml @ 0:457fd8fd681a draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/VirHunter commit 628688c1302dbf972e48806d2a5bafe27847bdcc

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/virhunter.xml	Wed Nov 09 12:19:26 2022 +0000
@@ -0,0 +1,55 @@
+<tool id="virhunter" name="virhunter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
+    <description>
+        Deep learning method to identify viruses in sequencing datasets..
+    </description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <xrefs>
+        <xref type="bio.tools">virhunter</xref>
+    </xrefs>
+    <expand macro="requirements"/>
+    <command detect_errors="exit_code"><![CDATA[
+
+    mkdir -p '${predicted_fragments.extra_files_path}' &&
+    python '$__tool_directory__/predict.py'
+        --test_ds '${fasta_file}'
+        --weights '${weights.fields.path}'
+        --out_path '${predicted_fragments.extra_files_path}'
+        --return_viral True
+        --limit $limit
+    && cp '${predicted_fragments.extra_files_path}'/predicted_fragments.csv predicted_fragments.csv
+    && cp '${predicted_fragments.extra_files_path}'/predicted.csv predicted.csv
+    && cp '${predicted_fragments.extra_files_path}'/viral.fasta viral.fasta
+
+    ]]></command>
+    <inputs>
+        <param name="fasta_file" type="data" format="fasta" label="DNA FASTA file(s)"/>
+        <param name="weights" type="select" label="Select a reference model" help="If your model of interest is not listed, contact the Galaxy team">
+            <options from_data_table="virhunter_models">
+                <validator type="no_options" message="No models are available for the selected input dataset" />
+            </options>
+        </param>
+        <param argument="--limit" type="integer" min="0" value="750" label="Minimum contig length" help="Do not predict contigs shorter than this value. Default: 750" />
+    </inputs>
+    <outputs>
+        <data format="csv" name="predicted_fragments" from_work_dir="predicted_fragments.csv" label="${tool.name} on ${on_string}: predicted fragments"/>
+        <data format="csv" name="predicted" from_work_dir="predicted.csv" label="${tool.name} on ${on_string}: predicted "/>
+        <data format="fasta" name="viral" from_work_dir="viral.fasta" label="${tool.name} on ${on_string}: viral FASTA file" />
+    </outputs>
+    <tests>
+        <test>
+            <param name="fasta_file" value="viruses.fasta"/>
+            <param name="weights" value="test"/>
+            <output name="predicted_fragments" file="predicted_fragments.csv"  ftype="csv" lines_diff="2"/>
+            <output name="predicted" file="predicted.csv"  ftype="csv" lines_diff="2"/>
+            <output name="viral" file="viral.fasta"  ftype="fasta" lines_diff="2"/>
+        </test>
+    </tests>
+
+    <help>
+    <![CDATA[
+    VirHunter is a deep learning method that uses Convolutional Neural Networks (CNNs) and a Random Forest Classifier to identify viruses in sequening datasets. More precisely, VirHunter classifies previously assembled contigs as viral, host and bacterial (contamination).
+ ]]></help>
+    <expand macro="citations" />
+</tool>
\ No newline at end of file