| Next changeset 1:c58c1a99578b (2023-06-10) |
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Commit message:
planemo upload for repository https://github.com/paulzierep/DeepMicro commit 1bbea291a9d77beafaeba83ab775d870ec24719e |
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added:
deepmicro.xml macros.xml static/images/ML_Workflow.png test-data/UserDataExample.csv test-data/UserLabelExample.csv |
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| diff -r 000000000000 -r 77cbfe3e1b0d deepmicro.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/deepmicro.xml Tue May 02 17:39:13 2023 +0000 |
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| b'@@ -0,0 +1,289 @@\n+<tool id="deepmicro" name="DeepMicro" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">\n+ <description>\n+ Representation learning and classification framework\n+ </description>\n+ <macros>\n+ <import>macros.xml</import>\n+ </macros>\n+ <expand macro="biotools" />\n+ <expand macro="requirements" />\n+ <expand macro="version" />\n+ <command detect_errors="exit_code"><![CDATA[\n+ mkdir data &&\n+ mkdir results &&\n+ ln -s \'$features\' data/features.csv &&\n+\n+ #if $mode.mode_type == "only_encoding":\n+\n+ #for $params in $mode.parameter_set:\n+\n+ #if $params.rl_type.rl_type_choice == "--pca" or $params.rl_type.rl_type_choice == "--rp":\n+ DM.py -r 1 -cd features.csv \'$params.rl_type.rl_type_choice\' --save_rep --no_clf -t \\${GALAXY_SLOTS:-8} &&\n+ #else: \n+ DM.py -r 1 -cd features.csv \'$params.rl_type.rl_type_choice\' -dm \'$params.rl_type.dm\' --save_rep --no_clf -t \\${GALAXY_SLOTS:-8} &&\n+ #end if\n+ #end for\n+\n+ #else:\n+\n+ ln -s \'$mode.class_labels\' data/labels.csv &&\n+\n+ #for $params in $mode.parameter_set:\n+\n+ #if $params.rl_type.rl_type_choice == "--pca" or $params.rl_type.rl_type_choice == "--rp":\n+ DM.py -r 1 -cd features.csv -cl labels.csv \'$params.rl_type.rl_type_choice\' --save_rep -m \'$params.rl_type.classifier\' -t \\${GALAXY_SLOTS:-8} &&\n+ #else: \n+ DM.py -r 1 -cd features.csv -cl labels.csv \'$params.rl_type.rl_type_choice\' -dm \'$params.rl_type.dm\' --save_rep -m \'$params.rl_type.classifier\' -t \\${GALAXY_SLOTS:-8} &&\n+ #end if\n+ #end for\n+\n+ #end if\n+\n+ echo Done !\n+ ]]>\n+ </command>\n+ <inputs>\n+ <param argument="--features" type="data" format="tabular" label="Feature table" help="Dataset containing the features of samples"/>\n+ <conditional name="mode">\n+ <param name="mode_type" type="select" label="Mode" help="The tool can either only create a latent \n+ representation of the data or create a latent representation of the data and cross validate a classifier using that encoding.">\n+ <option value="only_encoding">Create only encoding</option>\n+ <option value="e_and_c">Create encoding and cross validate a classifier</option>\n+ </param>\n+ <when value="only_encoding">\n+ <repeat name="parameter_set" title="Parameter Set">\n+ <conditional name="rl_type">\n+ <param name="rl_type_choice" type="select" label="Representation learning type" help="The type of representation learning" >\n+ <option value="--pca">PCA</option>\n+ <option value="--rp">Random Projection</option>\n+ <option value="--ae">Autoencoder or Deep Autoencoder</option>\n+ <option value="--vae">Variational Autoencoder</option>\n+ <option value="--cae">Convolutional Autoencoder</option>\n+ </param>\n+ <when value="--pca"/>\n+ <when value="--rp"/>\n+ <when value="--ae">\n+ <expand macro="dm" /> \n+ </when>\n+ <when value="--vae">\n+ <expand macro="dm" /> \n+ </when>\n+ <when value="--cae">\n+ <expand macro="dm" /> \n+ </when>\n+ </conditional>\n+ </repeat>\n+ </when>\n+ <when value="e_and_c">\n+ <param argument="--class_labels" type="data" format="tabular" label="Class labels" help="Da'..b' </test> \n+\n+ <!-- encoding and clf -->\n+ <!-- test one parameter set -->\n+\n+ <test expect_num_outputs="1">\n+ <param name="features" value="UserDataExample.csv" />\n+ <param name="mode_type" value="e_and_c" />\n+ <param name="class_labels" value="UserLabelExample.csv" />\n+ <param name="rl_type_choice" value="--vae" />\n+ <param name="dm" value="40" />\n+ <param name="classifier" value="rf" /> \n+ <output ftype="tabular" name="results" >\n+ <assert_contents>\n+ <has_text text="VAE[40]_rf" />\n+ </assert_contents>\n+ </output>\n+\n+ </test>\n+\n+ <!-- test multiple parameter sets -->\n+ <test expect_num_outputs="1">\n+ <param name="features" value="UserDataExample.csv" />\n+ <conditional name="mode">\n+ <param name="mode_type" value="e_and_c" />\n+ <param name="class_labels" value="UserLabelExample.csv" />\n+\n+ <repeat name="parameter_set">\n+ <conditional name="rl_type">\n+ <param name="rl_type_choice" value="--cae" />\n+ <param name="dm" value="20" />\n+ <param name="classifier" value="rf" /> \n+ </conditional>\n+ </repeat>\n+\n+ <repeat name="parameter_set">\n+ <conditional name="rl_type">\n+ <param name="rl_type_choice" value="--vae" />\n+ <param name="dm" value="40" />\n+ <param name="classifier" value="mlp" /> \n+ </conditional>\n+ </repeat>\n+ \n+ </conditional>\n+ \n+ <output ftype="tabular" name="results" >\n+ <assert_contents>\n+ <has_text text="CAE[20]_rf" />\n+ <has_text text="VAE[40]_mlp" />\n+ </assert_contents>\n+ </output>\n+\n+ </test> \n+\n+ </tests>\n+ <help>\n+ <![CDATA[\n+DeepMicro is a deep representation learning framework exploiting various autoencoders \n+to learn robust low-dimensional representations from high-dimensional data and training\n+classification models based on the learned representation.\n+\n+======================================\n+Option 1) Only representation learning\n+====================================== \n+\n+The representation learning does not require class labels and can be learned from the features alone. \n+The wrapper allows to explore multiple paramertes (i.e. different modes to\n+generate the features, please refer to the publication for details), for each \n+added parameter the encoded features are generated. Those features can then be passed to subsequent ML tools,\n+such as `Ensemble methods for classification and regression` or `Split Dataset into training and test subsets`\n+\n+=====================================================\n+Option 2) Representation learning and classification\n+=====================================================\n+\n+The tool itself can also evaluate the performance of the generated representation learning for different\n+classifiers internally using 5 fold CV. The wrapper allows to explore multiple paramertes and clfs.\n+Each parameter run will be stored as a line to the result file. If this option is chosen the latent representation is not\n+exported as output. To create the latent representation of the complete feature set, run the tool again\n+with the same parameters using the `Only representation learning` option.\n+The header of the result file is: \n+\n+\'{Encoding}_{classifier}, AUC, ACC, Recall, Precision, F1_score, time-end, runtime(sec), classfication time(sec), best hyper-parameter\'\n+\n+The overall schema of the tool is shown in:\n+\n+.. image:: ML_Workflow.png\n+ ]]>\n+ </help>\n+ <expand macro="citations" />\n+ <expand macro="creator" />\n+</tool>\n' |
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| diff -r 000000000000 -r 77cbfe3e1b0d macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Tue May 02 17:39:13 2023 +0000 |
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| @@ -0,0 +1,49 @@ +<?xml version="1.0"?> +<macros> + <token name="@TOOL_VERSION@">1.4</token> + <token name="@VERSION_SUFFIX@">0</token> + <token name="@PROFILE@">22.05</token> + <xml name="biotools"> + <xrefs> + <xref type="bio.tools"> + DeepMicro + </xref> + </xrefs> + </xml> + <xml name="requirements"> + <requirements> + <requirement type="package" version="@TOOL_VERSION@">deepmicro</requirement> + </requirements> + </xml> + <xml name="version"> + <version_command><![CDATA[ + echo "@TOOL_VERSION@" + ]]></version_command> + </xml> + <xml name="citations"> + <citations> + <citation type="doi"> + 10.1038/s41598-020-63159-5 + </citation> + </citations> + </xml> + <xml name="creator"> + <creator> + <person givenName="Paul" familyName="Zierep" email="zierep@informatik.uni-freiburg.de" /> + </creator> + </xml> + <xml name="dm"> + <param name="dm" type="text" value="40" label="Dimensions for deep representation learning" help="Comma-separated dimensions for deep representation learning e.g. [50,30,20]"> + <validator type="regex" message="Use only numbers and commas for this input">^(\d+|\,)+$</validator> + </param > + + </xml> + <xml name="clfs"> + <param name="classifier" type="select" label="Classifier for the cross validation" help="The classifier used for the cross validation (`all` will create a run for each classifier)"> + <option value="svm">svm</option> + <option value="mlp">mlp</option> + <option value="rf">rf</option> + <option value="all">all</option> + </param> + </xml> +</macros> |
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| diff -r 000000000000 -r 77cbfe3e1b0d static/images/ML_Workflow.png |
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| Binary file static/images/ML_Workflow.png has changed |
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| diff -r 000000000000 -r 77cbfe3e1b0d test-data/UserDataExample.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/UserDataExample.csv Tue May 02 17:39:13 2023 +0000 |
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| b'@@ -0,0 +1,20 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| diff -r 000000000000 -r 77cbfe3e1b0d test-data/UserLabelExample.csv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/UserLabelExample.csv Tue May 02 17:39:13 2023 +0000 |
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