Repository 'qiime2__longitudinal__feature_volatility'
hg clone https://toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__longitudinal__feature_volatility

Changeset 0:89d35e7b6d90 (2022-08-29)
Next changeset 1:e2fd93e4e3f7 (2023-01-13)
Commit message:
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__longitudinal commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
added:
qiime2__longitudinal__feature_volatility.xml
test-data/.gitkeep
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diff -r 000000000000 -r 89d35e7b6d90 qiime2__longitudinal__feature_volatility.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/qiime2__longitudinal__feature_volatility.xml Mon Aug 29 20:12:21 2022 +0000
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b'@@ -0,0 +1,162 @@\n+<?xml version=\'1.0\' encoding=\'utf-8\'?>\n+<!--\n+Copyright (c) 2022, QIIME 2 development team.\n+\n+Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)\n+-->\n+<!--\n+This tool was automatically generated by:\n+    q2galaxy (version: 2022.8.1)\n+for:\n+    qiime2 (version: 2022.8.1)\n+-->\n+<tool name="qiime2 longitudinal feature-volatility" id="qiime2__longitudinal__feature_volatility" version="2022.8.0+q2galaxy.2022.8.1.2" profile="22.05" license="BSD-3-Clause">\n+    <description>Feature volatility analysis</description>\n+    <requirements>\n+        <container type="docker">quay.io/qiime2/core:2022.8</container>\n+    </requirements>\n+    <version_command>q2galaxy version longitudinal</version_command>\n+    <command detect_errors="aggressive">q2galaxy run longitudinal feature_volatility \'$inputs\'</command>\n+    <configfiles>\n+        <inputs name="inputs" data_style="paths"/>\n+    </configfiles>\n+    <inputs>\n+        <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency]" help="[required]  Feature table containing all features that should be used for target prediction.">\n+            <options options_filter_attribute="metadata.semantic_type">\n+                <filter type="add_value" value="FeatureTable[Frequency]"/>\n+            </options>\n+            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in [\'FeatureTable[Frequency]\']</validator>\n+        </param>\n+        <repeat name="metadata" min="1" help="[required]  Sample metadata file containing individual_id_column." title="metadata: Metadata">\n+            <conditional name="__q2galaxy__GUI__conditional__metadata__">\n+                <param name="type" type="select" label="metadata: Metadata">\n+                    <option value="tsv" selected="true">Metadata from TSV</option>\n+                    <option value="qza">Metadata from Artifact</option>\n+                </param>\n+                <when value="tsv">\n+                    <param name="source" type="data" format="tabular,qiime2.tabular" label="Metadata Source"/>\n+                </when>\n+                <when value="qza">\n+                    <param name="source" type="data" format="qza" label="Metadata Source"/>\n+                </when>\n+            </conditional>\n+        </repeat>\n+        <param name="state_column" type="text" label="state_column: Str" help="[required]  Metadata containing collection time (state) values for each sample. Must contain exclusively numeric values.">\n+            <sanitizer>\n+                <valid initial="string.printable"/>\n+            </sanitizer>\n+            <validator type="expression" message="Please verify this parameter.">value is not None and len(value) &gt; 0</validator>\n+        </param>\n+        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">\n+            <conditional name="__q2galaxy__GUI__conditional__individual_id_column__" label="individual_id_column: Str">\n+                <param name="__q2galaxy__GUI__select__" type="select" label="individual_id_column: Str" help="[optional]  Metadata column containing IDs for individual subjects.">\n+                    <option value="__q2galaxy__::control::default" selected="true">None (Use default behavior)</option>\n+                    <option value="__q2galaxy__::control::provide">Provide a value</option>\n+                </param>\n+                <when value="__q2galaxy__::control::default">\n+                    <param name="individual_id_column" type="hidden" value="__q2galaxy__::literal::None"/>\n+                </when>\n+                <when value="__q2galaxy__::control::provide">\n+                    <param name="individual_id_column" type="text">\n+                        <sanitizer>\n+                            <valid initial="string.printable"/>\n+                        </sanitizer>\n+                    </param>\n+            '..b'\n+                </when>\n+                <when value="q2">\n+                    <param name="importance_threshold" type="hidden" value="q2"/>\n+                </when>\n+                <when value="q3">\n+                    <param name="importance_threshold" type="hidden" value="q3"/>\n+                </when>\n+                <when value="__q2galaxy__::control::Float X Range(0__comma__ None__comma__ inclusive_start=False)">\n+                    <param name="importance_threshold" type="float" min="1e-06" value="" label="importance_threshold: Float % Range(0, None, inclusive_start=False)" help="[required]  Filter feature table to exclude any features with an importance score less than this threshold. Set to &quot;q1&quot;, &quot;q2&quot;, or &quot;q3&quot; to select the first, second, or third quartile of values. Set to &quot;None&quot; to disable this filter."/>\n+                </when>\n+            </conditional>\n+            <conditional name="__q2galaxy__GUI__conditional__feature_count__">\n+                <param name="__q2galaxy__GUI__select__" type="select" label="feature_count: Int % Range(1, None) | Str % Choices(\'all\')" help="[default: 100]  Filter feature table to include top N most important features. Set to &quot;all&quot; to include all features.">\n+                    <option value="all">all (Str)</option>\n+                    <option value="__q2galaxy__::control::Int X Range(1__comma__ None)" selected="true">Provide a value (Int % Range(1, None))</option>\n+                </param>\n+                <when value="all">\n+                    <param name="feature_count" type="hidden" value="all"/>\n+                </when>\n+                <when value="__q2galaxy__::control::Int X Range(1__comma__ None)">\n+                    <param name="feature_count" type="integer" min="1" value="100" label="feature_count: Int % Range(1, None)" help="[default: 100]  Filter feature table to include top N most important features. Set to &quot;all&quot; to include all features."/>\n+                </when>\n+            </conditional>\n+        </section>\n+    </inputs>\n+    <outputs>\n+        <data name="filtered_table" format="qza" label="${tool.name} on ${on_string}: filtered_table.qza" from_work_dir="filtered_table.qza"/>\n+        <data name="feature_importance" format="qza" label="${tool.name} on ${on_string}: feature_importance.qza" from_work_dir="feature_importance.qza"/>\n+        <data name="volatility_plot" format="qzv" label="${tool.name} on ${on_string}: volatility_plot.qzv" from_work_dir="volatility_plot.qzv"/>\n+        <data name="accuracy_results" format="qzv" label="${tool.name} on ${on_string}: accuracy_results.qzv" from_work_dir="accuracy_results.qzv"/>\n+        <data name="sample_estimator" format="qza" label="${tool.name} on ${on_string}: sample_estimator.qza" from_work_dir="sample_estimator.qza"/>\n+    </outputs>\n+    <tests/>\n+    <help>\n+QIIME 2: longitudinal feature-volatility\n+========================================\n+Feature volatility analysis\n+\n+\n+Outputs:\n+--------\n+:filtered_table.qza: Feature table containing only important features.\n+:feature_importance.qza: Importance of each input feature to model accuracy.\n+:volatility_plot.qzv: Interactive volatility plot visualization.\n+:accuracy_results.qzv: Accuracy results visualization.\n+:sample_estimator.qza: Trained sample regressor.\n+\n+|  \n+\n+Description:\n+------------\n+Identify features that are predictive of a numeric metadata column, state_column (e.g., time), and plot their relative frequencies across states using interactive feature volatility plots. A supervised learning regressor is used to identify important features and assess their ability to predict sample states. state_column will typically be a measure of time, but any numeric metadata column can be used.\n+\n+\n+|  \n+\n+</help>\n+    <citations>\n+        <citation type="doi">10.1128/mSystems.00219-18</citation>\n+        <citation type="doi">10.1038/s41587-019-0209-9</citation>\n+    </citations>\n+</tool>\n'