changeset 0:bd16566ac9d9 draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
author q2d2
date Mon, 29 Aug 2022 20:25:34 +0000
parents
children b2a04cea7140
files qiime2__sample_classifier__scatterplot.xml test-data/.gitkeep
diffstat 1 files changed, 93 insertions(+), 0 deletions(-) [+]
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+++ b/qiime2__sample_classifier__scatterplot.xml	Mon Aug 29 20:25:34 2022 +0000
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+<?xml version='1.0' encoding='utf-8'?>
+<!--
+Copyright (c) 2022, QIIME 2 development team.
+
+Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)
+-->
+<!--
+This tool was automatically generated by:
+    q2galaxy (version: 2022.8.1)
+for:
+    qiime2 (version: 2022.8.1)
+-->
+<tool name="qiime2 sample-classifier scatterplot" id="qiime2__sample_classifier__scatterplot" version="2022.8.0+q2galaxy.2022.8.1.2" profile="22.05" license="BSD-3-Clause">
+    <description>Make 2D scatterplot and linear regression of regressor predictions.</description>
+    <requirements>
+        <container type="docker">quay.io/qiime2/core:2022.8</container>
+    </requirements>
+    <version_command>q2galaxy version sample_classifier</version_command>
+    <command detect_errors="aggressive">q2galaxy run sample_classifier scatterplot '$inputs'</command>
+    <configfiles>
+        <inputs name="inputs" data_style="paths"/>
+    </configfiles>
+    <inputs>
+        <param name="predictions" type="data" format="qza" label="predictions: SampleData[RegressorPredictions]" help="[required]  Predicted values to plot on y axis. Must be predictions of numeric data produced by a sample regressor.">
+            <options options_filter_attribute="metadata.semantic_type">
+                <filter type="add_value" value="SampleData[RegressorPredictions]"/>
+            </options>
+            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['SampleData[RegressorPredictions]']</validator>
+        </param>
+        <conditional name="truth">
+            <param name="type" type="select" label="truth: MetadataColumn[Numeric]" help="[required]  Metadata column (true values) to plot on x axis.">
+                <option value="tsv" selected="true">Metadata from TSV</option>
+                <option value="qza">Metadata from Artifact</option>
+            </param>
+            <when value="tsv">
+                <param name="source" type="data" format="tabular,qiime2.tabular" label="Metadata Source"/>
+                <param name="column" type="data_column" label="Column Name" data_ref="source" use_header_names="true">
+                    <validator type="expression" message="The first column cannot be selected (they are IDs).">value != "1"</validator>
+                </param>
+            </when>
+            <when value="qza">
+                <param name="source" type="data" format="qza" label="Metadata Source"/>
+                <param name="column" type="text" label="Column Name">
+                    <validator type="empty_field"/>
+                </param>
+            </when>
+        </conditional>
+        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
+            <param name="missing_samples" type="select" label="missing_samples: Str % Choices('error', 'ignore')" display="radio">
+                <option value="error" selected="true">error</option>
+                <option value="ignore">ignore</option>
+            </param>
+        </section>
+    </inputs>
+    <outputs>
+        <data name="visualization" format="qzv" label="${tool.name} on ${on_string}: visualization.qzv" from_work_dir="visualization.qzv"/>
+    </outputs>
+    <tests/>
+    <help>
+QIIME 2: sample-classifier scatterplot
+======================================
+Make 2D scatterplot and linear regression of regressor predictions.
+
+
+Outputs:
+--------
+:visualization.qzv: &lt;no description&gt;
+
+|  
+
+Description:
+------------
+Make a 2D scatterplot and linear regression of predicted vs. true values for a set of samples predicted using a sample regressor.
+
+
+|  
+
+</help>
+    <citations>
+        <citation type="doi">10.21105/joss.00934</citation>
+        <citation type="bibtex">@article{cite2,
+ author = {Pedregosa, Fabian and Varoquaux, Gaël and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and Vanderplas, Jake and Passos, Alexandre and Cournapeau, David and Brucher, Matthieu and Perrot, Matthieu and Duchesnay, Édouard},
+ journal = {Journal of machine learning research},
+ number = {Oct},
+ pages = {2825--2830},
+ title = {Scikit-learn: Machine learning in Python},
+ volume = {12},
+ year = {2011}
+}
+</citation>
+        <citation type="doi">10.1038/s41587-019-0209-9</citation>
+    </citations>
+</tool>