Mercurial > repos > goeckslab > vitessce_spatial
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planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/vitessce commit af71ccb3b89c9735c6f985a3e8ffe22cd14c0e04
author | goeckslab |
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date | Thu, 30 May 2024 17:24:44 +0000 |
parents | 4bf852448b5d |
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<tool id="vitessce_spatial" name="Run multi-modal single-cell visualization" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> <description>with Vitessce</description> <macros> <import>main_macros.xml</import> </macros> <edam_operations> <edam_operation>operation_3443</edam_operation> </edam_operations> <expand macro="vitessce_requirements"/> <expand macro="macro_stdio" /> <version_command> "@VERSION@"</version_command> <expand macro="vitessce_cmd" /> <configfiles> <inputs name="inputs" /> </configfiles> <inputs> <param name="image" type="data" format="ome.tiff" label="Select the OME Tiff image" /> <param name="masks" type="data" format="tiff,ome.tiff" optional="true" label="Select masks for the OME Tiff image (Optional)" /> <conditional name="do_phenotyping"> <param name="phenotyping_choice" type="select" label="Add annotations or visualizations from Anndata file"> <option value="no_h5ad" selected="true">Do not add elements from Anndata file</option> <option value="add_h5ad">Add elements from Anndata file</option> </param> <when value="no_h5ad"> </when> <when value="add_h5ad"> <param name="anndata" type="data" format="h5ad" label="Select the anndata file" /> <conditional name="scatterplot_embeddings"> <param name="embedding" type="select" label="Select an embedding algorithm for scatterplot"> <option value="umap" selected="true">UMAP</option> <option value="tsne">tSNE</option> <option value="pca">PCA</option> </param> <when value="umap"> <section name="options" title="Advance Options for neighbor search"> <param argument="n_neighbors" type="integer" value="30" label="The size of local neighborhood used for manifold approximation" /> <param argument="n_pcs" type="integer" value="10" label="Number of PCs" /> <param argument="knn" type="boolean" checked="true" label="Whether to use knn graph" help="If false, use a Gaussian Kernel to assign low weights to neighbors more distant than the n_neighbors nearest neighbor." /> <param argument="random_state" type="integer" value="0" optional="true" label="Randomness seed" /> </section> </when> <when value="tsne"> <section name="options" title="Advance Options for computing tSNE"> <param argument="n_pcs" type="integer" value="10" label="Number of PCs" /> <param argument="learning_rate" type="float" value="1000" label="Learning rate" help="Should be 100-1000." /> <param argument="random_state" type="integer" value="0" optional="true" label="Randomness seed" /> </section> </when> <when value="pca"> <section name="options" title="Advance Options for computing PCA"> <param argument="n_comps" type="integer" value="" optional="true" label="Number of principal components to compute" help="Defaults to 50, or 1 - minimum dimension size of selected representation." /> <param argument="zero_center" type="boolean" checked="true" label="Whether to compute standard PCA from covariance matrix" help="If False, omit zero-centering variables (uses TruncatedSVD)" /> <param argument="svd_solver" type="select" label="Select the SVD solver"> <option value="arpack" selected="true">arpack</option> <option value="randomized">randomized</option> <option value="auto">auto</option> <option value="lobpcg">lobpcg</option> </param> <param argument="random_state" type="integer" value="0" optional="true" label="Randomness seed" /> </section> </when> </conditional> <conditional name="phenotype_factory"> <param name="phenotype_mode" type="select" label="Input the anndata key to display"> <option value="choices" selected="true">Multiple choices</option> <option value="type_in">Type in</option> </param> <when value="choices"> <param name="phenotypes" type="select" multiple="true" display="checkboxes" label="Select the key(s)" > <option value="phenotype" selected="true">'phenotype' (via scimap phenotyping)</option> <option value="kmeans">'kmeans' (via clustering)</option> <option value="leiden">'leiden' (via clustering)</option> <option value="phenograph">'phenograph' (via clustering)</option> <option value="parc">'parc' (via clustering)</option> </param> </when> <when value="type_in"> <param name="phenotypes" type="text" value="" label="Type in the keys storing phenotypes" help="Comma delimited for multiple keys."/> </when> </conditional> </when> </conditional> </inputs> <outputs> <data format="html" name="output" /> </outputs> <tests> <test> <param name="image" value="cropped_reactive_core.ome.tiff" ftype="ome.tiff" /> <conditional name="do_phenotyping"> <param name="phenotyping_choice" value="add_h5ad" /> <param name="anndata" value="cropped_tutorial_data_pheno.h5ad" ftype="h5ad" /> <conditional name="phenotype_factory"> <param name="phenotype_mode" value="type_in" /> <param name="phenotypes" value="leiden" /> </conditional> </conditional> <output name="output" file="tutorial_vitessce.html" compare="sim_size" delta="20" /> </test> <test> <param name="image" value="cropped_reactive_core.ome.tiff" ftype="ome.tiff" /> <conditional name="do_phenotyping"> <param name="phenotyping_choice" value="add_h5ad" /> <param name="anndata" value="cropped_tutorial_data_pheno.h5ad" ftype="h5ad" /> <conditional name="scatterplot_embeddings"> <param name="embedding" value="pca" /> </conditional> <conditional name="phenotype_factory"> <param name="phenotype_mode" value="type_in" /> <param name="phenotypes" value="leiden" /> </conditional> </conditional> <output name="output" file="tutorial_vitessce.html" compare="sim_size" delta="20" /> </test> <test> <param name="image" value="cropped_reactive_core.ome.tiff" ftype="ome.tiff" /> <conditional name="do_phenotyping"> <param name="phenotyping_choice" value="no_h5ad" /> </conditional> <output name="output" file="tutorial_vitessce.html" compare="sim_size" delta="20" /> </test> </tests> <help> <![CDATA[ **What it does** This tools provides web-based, interactive and scalable visualizations of single cell data. **Input** OME-TIFF image. Segmentation masks (optional). AnnData with marker intensities. **Output** An HTML file with Vitessce component. ]]> </help> <citations> <citation type="doi">10.31219/osf.io/y8thv</citation> </citations> </tool>