Mercurial > repos > q2d2 > qiime2__longitudinal__feature_volatility
changeset 0:89d35e7b6d90 draft
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__longitudinal commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
| author | q2d2 |
|---|---|
| date | Mon, 29 Aug 2022 20:12:21 +0000 |
| parents | |
| children | e2fd93e4e3f7 |
| files | qiime2__longitudinal__feature_volatility.xml test-data/.gitkeep |
| diffstat | 1 files changed, 162 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/qiime2__longitudinal__feature_volatility.xml Mon Aug 29 20:12:21 2022 +0000 @@ -0,0 +1,162 @@ +<?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 longitudinal feature-volatility" id="qiime2__longitudinal__feature_volatility" version="2022.8.0+q2galaxy.2022.8.1.2" profile="22.05" license="BSD-3-Clause"> + <description>Feature volatility analysis</description> + <requirements> + <container type="docker">quay.io/qiime2/core:2022.8</container> + </requirements> + <version_command>q2galaxy version longitudinal</version_command> + <command detect_errors="aggressive">q2galaxy run longitudinal feature_volatility '$inputs'</command> + <configfiles> + <inputs name="inputs" data_style="paths"/> + </configfiles> + <inputs> + <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."> + <options options_filter_attribute="metadata.semantic_type"> + <filter type="add_value" value="FeatureTable[Frequency]"/> + </options> + <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Frequency]']</validator> + </param> + <repeat name="metadata" min="1" help="[required] Sample metadata file containing individual_id_column." title="metadata: Metadata"> + <conditional name="__q2galaxy__GUI__conditional__metadata__"> + <param name="type" type="select" label="metadata: Metadata"> + <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"/> + </when> + <when value="qza"> + <param name="source" type="data" format="qza" label="Metadata Source"/> + </when> + </conditional> + </repeat> + <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."> + <sanitizer> + <valid initial="string.printable"/> + </sanitizer> + <validator type="expression" message="Please verify this parameter.">value is not None and len(value) > 0</validator> + </param> + <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options"> + <conditional name="__q2galaxy__GUI__conditional__individual_id_column__" label="individual_id_column: Str"> + <param name="__q2galaxy__GUI__select__" type="select" label="individual_id_column: Str" help="[optional] Metadata column containing IDs for individual subjects."> + <option value="__q2galaxy__::control::default" selected="true">None (Use default behavior)</option> + <option value="__q2galaxy__::control::provide">Provide a value</option> + </param> + <when value="__q2galaxy__::control::default"> + <param name="individual_id_column" type="hidden" value="__q2galaxy__::literal::None"/> + </when> + <when value="__q2galaxy__::control::provide"> + <param name="individual_id_column" type="text"> + <sanitizer> + <valid initial="string.printable"/> + </sanitizer> + </param> + </when> + </conditional> + <param name="cv" type="integer" min="1" value="5" label="cv: Int % Range(1, None)" help="[default: 5] Number of k-fold cross-validations to perform."/> + <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/> + <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1] Number of jobs to run in parallel."/> + <param name="n_estimators" type="integer" min="1" value="100" label="n_estimators: Int % Range(1, None)" help="[default: 100] Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting."/> + <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')"> + <option value="RandomForestRegressor" selected="true">RandomForestRegressor</option> + <option value="ExtraTreesRegressor">ExtraTreesRegressor</option> + <option value="GradientBoostingRegressor">GradientBoostingRegressor</option> + <option value="AdaBoostRegressor">AdaBoostRegressor</option> + <option value="ElasticNet">ElasticNet</option> + <option value="Ridge">Ridge</option> + <option value="Lasso">Lasso</option> + <option value="KNeighborsRegressor">KNeighborsRegressor</option> + <option value="LinearSVR">LinearSVR</option> + <option value="SVR">SVR</option> + </param> + <param name="parameter_tuning" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="parameter_tuning: Bool" help="[default: No] Automatically tune hyperparameters using random grid search."/> + <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> + <conditional name="__q2galaxy__GUI__conditional__importance_threshold__"> + <param name="__q2galaxy__GUI__select__" type="select" label="importance_threshold: Float % Range(0, None, inclusive_start=False) | Str % Choices('q1', 'q2', 'q3')" help="[optional] Filter feature table to exclude any features with an importance score less than this threshold. Set to "q1", "q2", or "q3" to select the first, second, or third quartile of values. Set to "None" to disable this filter."> + <option value="__q2galaxy__::literal::None" selected="true">None (Use default behavior)</option> + <option value="q1">q1 (Str)</option> + <option value="q2">q2 (Str)</option> + <option value="q3">q3 (Str)</option> + <option value="__q2galaxy__::control::Float X Range(0__comma__ None__comma__ inclusive_start=False)">Provide a value (Float % Range(0, None, inclusive_start=False))</option> + </param> + <when value="__q2galaxy__::literal::None"> + <param name="importance_threshold" type="hidden" value="__q2galaxy__::literal::None"/> + </when> + <when value="q1"> + <param name="importance_threshold" type="hidden" value="q1"/> + </when> + <when value="q2"> + <param name="importance_threshold" type="hidden" value="q2"/> + </when> + <when value="q3"> + <param name="importance_threshold" type="hidden" value="q3"/> + </when> + <when value="__q2galaxy__::control::Float X Range(0__comma__ None__comma__ inclusive_start=False)"> + <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 "q1", "q2", or "q3" to select the first, second, or third quartile of values. Set to "None" to disable this filter."/> + </when> + </conditional> + <conditional name="__q2galaxy__GUI__conditional__feature_count__"> + <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 "all" to include all features."> + <option value="all">all (Str)</option> + <option value="__q2galaxy__::control::Int X Range(1__comma__ None)" selected="true">Provide a value (Int % Range(1, None))</option> + </param> + <when value="all"> + <param name="feature_count" type="hidden" value="all"/> + </when> + <when value="__q2galaxy__::control::Int X Range(1__comma__ None)"> + <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 "all" to include all features."/> + </when> + </conditional> + </section> + </inputs> + <outputs> + <data name="filtered_table" format="qza" label="${tool.name} on ${on_string}: filtered_table.qza" from_work_dir="filtered_table.qza"/> + <data name="feature_importance" format="qza" label="${tool.name} on ${on_string}: feature_importance.qza" from_work_dir="feature_importance.qza"/> + <data name="volatility_plot" format="qzv" label="${tool.name} on ${on_string}: volatility_plot.qzv" from_work_dir="volatility_plot.qzv"/> + <data name="accuracy_results" format="qzv" label="${tool.name} on ${on_string}: accuracy_results.qzv" from_work_dir="accuracy_results.qzv"/> + <data name="sample_estimator" format="qza" label="${tool.name} on ${on_string}: sample_estimator.qza" from_work_dir="sample_estimator.qza"/> + </outputs> + <tests/> + <help> +QIIME 2: longitudinal feature-volatility +======================================== +Feature volatility analysis + + +Outputs: +-------- +:filtered_table.qza: Feature table containing only important features. +:feature_importance.qza: Importance of each input feature to model accuracy. +:volatility_plot.qzv: Interactive volatility plot visualization. +:accuracy_results.qzv: Accuracy results visualization. +:sample_estimator.qza: Trained sample regressor. + +| + +Description: +------------ +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. + + +| + +</help> + <citations> + <citation type="doi">10.1128/mSystems.00219-18</citation> + <citation type="doi">10.1038/s41587-019-0209-9</citation> + </citations> +</tool>