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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit 6497f5415b57bedd849b876883574b3f0050741a"
author | iuc |
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date | Thu, 07 Jan 2021 23:26:43 +0000 |
parents | 70f5f1fee692 |
children | 688357ad5e61 |
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<tool id="anndata_inspect" name="Inspect AnnData" version="@VERSION@+@GALAXY_VERSION@"> <description>object</description> <macros> <import>macros.xml</import> </macros> <expand macro="requirements"/> <expand macro="version_command"/> <command detect_errors="exit_code"><![CDATA[ @CMD@ ]]></command> <configfiles> <configfile name="script_file"><![CDATA[ @CMD_imports@ import pandas as pd from scipy import io pd.options.display.precision = 15 adata = ad.read('$input') #if $inspect.info == 'general' with open('$general', 'w', encoding="utf-8") as f: print(adata, file=f) #else if $inspect.info == 'X' adata.to_df().to_csv('$X', sep='\t') #else if $inspect.info == 'obs' adata.obs.to_csv('$obs', sep='\t') #else if $inspect.info == 'var' adata.var.to_csv('$var', sep='\t') #else if $inspect.info == 'chunk_X' #if $inspect.chunk.info == 'random' X = adata.chunk_X(select=$inspect.chunk.size, replace=$inspect.chunk.replace) #else #set $select = [int(x.strip()) for x in str($inspect.chunk.list).split(',')] X = adata.chunk_X(select=$select) #end if pd.DataFrame(X).to_csv('$chunk_X', sep='\t') #else if $inspect.info == 'uns' #if $inspect.uns_info == 'neighbors' io.mmwrite('uns_neighbors_connectivities.mtx', adata.uns['neighbors']['connectivities']) io.mmwrite('uns_neighbors_distances.mtx', adata.uns['neighbors']['distances']) #else if $inspect.uns_info == 'paga' io.mmwrite('uns_paga_connectivities.mtx', adata.uns['paga']['connectivities']) io.mmwrite('uns_paga_connectivities_tree.mtx', adata.uns['paga']['connectivities_tree']) #else if $inspect.uns_info == 'pca' pd.DataFrame(adata.uns['pca']['variance']).to_csv("$uns_pca_variance", sep="\t", index = False) pd.DataFrame(adata.uns['pca']['variance_ratio']).to_csv("$uns_pca_variance_ratio", sep="\t", index = False) #else if $inspect.uns_info == 'rank_genes_groups' pd.DataFrame(adata.uns['rank_genes_groups']['logfoldchanges']).to_csv("$uns_rank_genes_groups_logfoldchanges", sep="\t", index = False) pd.DataFrame(adata.uns['rank_genes_groups']['names']).to_csv("$uns_rank_genes_groups_names", sep="\t", index = False) pd.DataFrame(adata.uns['rank_genes_groups']['pvals']).to_csv("$uns_rank_genes_groups_pvals", sep="\t", index = False) pd.DataFrame(adata.uns['rank_genes_groups']['pvals_adj']).to_csv("$uns_rank_genes_groups_pvals_adj", sep="\t", index = False) pd.DataFrame(adata.uns['rank_genes_groups']['scores']).to_csv("$uns_rank_genes_groups_scores", sep="\t", index = False) #end if #else if $inspect.info == 'obsm' #if $inspect.obsm_info == 'X_pca' pd.DataFrame(adata.obsm['X_pca']).to_csv("$obsm_X_pca", sep="\t", index = False) #else if $inspect.obsm_info == 'X_umap' pd.DataFrame(adata.obsm['X_umap']).to_csv("$obsm_X_umap", sep="\t", index = False) #else if $inspect.obsm_info == 'X_tsne' pd.DataFrame(adata.obsm['X_tsne']).to_csv("$obsm_X_tsne", sep="\t", index = False) #else if $inspect.obsm_info == 'X_draw_graph' for key in adata.obsm.keys(): if key.startswith('X_draw_graph'): pd.DataFrame(adata.obsm[key]).to_csv(key, sep="\t", index = False) #else if $inspect.obsm_info == 'X_diffmap' pd.DataFrame(adata.obsm['X_diffmap']).to_csv("$obsm_X_diffmap", sep="\t", index = False) #end if #else if $inspect.info == 'varm' #if $inspect.varm_info == 'PCs' pd.DataFrame(adata.varm['PCs']).to_csv("$varm_PCs", sep="\t", index = False) #end if #end if ]]></configfile> </configfiles> <inputs> <param name="input" type="data" format="h5ad" label="Annotated data matrix"/> <conditional name="inspect"> <param name="info" type="select" label="What to inspect?"> <option value="general">General information about the object</option> <option value="X">The full data matrix</option> <option value="chunk_X">A chunk of the data matrix</option> <option value="obs">Key-indexed observations annotation (obs)</option> <option value="var">Key-indexed annotation of variables/features (var)</option> <option value="uns">Unstructured annotation (uns)</option> <option value="obsm">Multi-dimensional observations annotation (obsm)</option> <option value="varm">Multi-dimensional variables annotation (varm)</option> </param> <when value="general"/> <when value="X"/> <when value="chunk_X"> <expand macro="params_chunk_X"/> </when> <when value="obs"/> <when value="var"/> <when value="uns"> <param name="uns_info" type="select" label="What to inspect in uns?"> <option value="neighbors">Neighbors</option> <option value="paga">PAGA</option> <option value="pca">PCA</option> <option value="rank_genes_groups">Rank gene groups (rank_genes_groups)</option> </param> </when> <when value="obsm"> <param name="obsm_info" type="select" label="Which annotation to inspect for the observations?"> <option value="X_pca">PCA coordinates (X_pca)</option> <option value="X_umap">UMAP coordinates (X_umap)</option> <option value="X_tsne">tSNE coordinates (X_tsne)</option> <option value="X_draw_graph">Coordinates of graph layout (X_draw_graph)</option> <option value="X_diffmap">Diffusion map representation of data (X_diffmap)</option> </param> </when> <when value="varm"> <param name="varm_info" type="select" label="Which annotation to inspect for the variables?"> <option value="PCs">Principal components containing the loadings</option> </param> </when> </conditional> </inputs> <outputs> <data name="general" format="txt" label="${tool.name} on ${on_string}: General information"> <filter>inspect['info'] == 'general'</filter> </data> <data name="X" format="tabular" label="${tool.name} on ${on_string}: Key-indexed observations annotation (X)"> <filter>inspect['info'] == 'X'</filter> </data> <data name="obs" format="tabular" label="${tool.name} on ${on_string}: Key-indexed observations annotation (obs)"> <filter>inspect['info'] == 'obs'</filter> </data> <data name="var" format="tabular" label="${tool.name} on ${on_string}: Key-indexed annotation of variables/features (var)"> <filter>inspect['info'] == 'var'</filter> </data> <data name="chunk_X" format="tabular" label="${tool.name} on ${on_string}: Observations annotation"> <filter>inspect['info'] == 'chunk_X'</filter> </data> <data name="uns_neighbors_connectivities" format="mtx" from_work_dir="uns_neighbors_connectivities.mtx" label="${tool.name} on ${on_string}: Weighted adjacency matrix of the neighborhood graph of data points"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'neighbors'</filter> </data> <data name="uns_neighbors_distances" format="mtx" from_work_dir="uns_neighbors_distances.mtx" label="${tool.name} on ${on_string}: Distances for each pair of neighbors"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'neighbors'</filter> </data> <data name="uns_paga_connectivities" format="mtx" from_work_dir="uns_paga_connectivities.mtx" label="${tool.name} on ${on_string}: Full adjacency matrix of the abstracted graph"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'paga'</filter> </data> <data name="uns_paga_connectivities_tree" format="mtx" from_work_dir="uns_paga_connectivities_tree.mtx" label="${tool.name} on ${on_string}: Adjacency matrix of the tree-like subgraph"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'paga'</filter> </data> <data name="uns_pca_variance" format="tabular" label="${tool.name} on ${on_string}: Ratio of explained variance for PCA"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'pca'</filter> </data> <data name="uns_pca_variance_ratio" format="tabular" label="${tool.name} on ${on_string}: Explained variance, equivalent to the eigenvalues of the covariance matrix, for PCA"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'pca'</filter> </data> <data name="uns_rank_genes_groups_names" format="tabular" label="${tool.name} on ${on_string}: Names for rank genes"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'rank_genes_groups'</filter> </data> <data name="uns_rank_genes_groups_scores" format="tabular" label="${tool.name} on ${on_string}: Z-scores for rank genes"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'rank_genes_groups'</filter> </data> <data name="uns_rank_genes_groups_logfoldchanges" format="tabular" label="${tool.name} on ${on_string}: Log2 fold changes for rank genes"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'rank_genes_groups'</filter> </data> <data name="uns_rank_genes_groups_pvals" format="tabular" label="${tool.name} on ${on_string}: P-values for rank genes"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'rank_genes_groups'</filter> </data> <data name="uns_rank_genes_groups_pvals_adj" format="tabular" label="${tool.name} on ${on_string}: Adjusted p-values for rank genes"> <filter>inspect['info'] == 'uns' and inspect['uns_info'] == 'rank_genes_groups'</filter> </data> <data name="obsm_X_pca" format="tabular" label="${tool.name} on ${on_string}: PCA coordinates for observations"> <filter>inspect['info'] == 'obsm' and inspect['obsm_info'] == 'X_pca'</filter> </data> <data name="obsm_X_umap" format="tabular" label="${tool.name} on ${on_string}: UMAP coordinates for observations"> <filter>inspect['info'] == 'obsm' and inspect['obsm_info'] == 'X_umap'</filter> </data> <data name="obsm_X_tsne" format="tabular" label="${tool.name} on ${on_string}: tSNE coordinates for observations"> <filter>inspect['info'] == 'obsm' and inspect['obsm_info'] == 'X_tsne'</filter> </data> <collection name="obsm_X_draw_graph" type="list" label="${tool.name} on ${on_string}: Coordinates of graph layout"> <discover_datasets pattern="X_draw_graph_(?P<designation>.*)" format="tabular"/> <filter>inspect['info'] == 'obsm' and inspect['obsm_info'] == 'X_draw_graph'</filter> </collection> <data name="obsm_X_diffmap" format="tabular" label="${tool.name} on ${on_string}: Diffusion map representation for observations"> <filter>inspect['info'] == 'obsm' and inspect['obsm_info'] == 'X_diffmap'</filter> </data> <data name="varm_PCs" format="tabular" label="${tool.name} on ${on_string}: Principal components containing the loadings for variables"> <filter>inspect['info'] == 'varm' and inspect['varm_info'] == 'PCs'</filter> </data> </outputs> <tests> <test> <!-- test 1: general info --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="general"/> </conditional> <output name="general" value="inspect.general.txt"/> </test> <test> <!-- test 2: X --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="X"/> </conditional> <assert_stdout> <has_text_matching expression="adata.to_df\(\).to_csv"/> </assert_stdout> <output name="X" value="inspect.X.tabular" ftype="tabular"/> </test> <test> <!-- test 3: obs --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="obs"/> </conditional> <assert_stdout> <has_text_matching expression="adata.obs.to_csv"/> </assert_stdout> <output name="obs" value="inspect.obs.tabular" ftype="tabular"/> </test> <test> <!-- test 4: var --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="var"/> </conditional> <assert_stdout> <has_text_matching expression="adata.var.to_csv"/> </assert_stdout> <output name="var" value="inspect.var.tabular" ftype="tabular"/> </test> <test> <!-- test 5: chunk_X, specified --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="chunk_X"/> <conditional name="chunk"> <param name="info" value="specified"/> <param name="list" value="3,5,8"/> </conditional> </conditional> <assert_stdout> <has_text_matching expression="adata.chunk_X"/> <has_text_matching expression="select=\[3, 5, 8\]"/> </assert_stdout> <output name="chunk_X" value="inspect.chunk_X.specified.tabular" ftype="tabular"/> </test> <test> <!-- test 6: chunk_X, random --> <param name="input" value="krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="chunk_X"/> <conditional name="chunk"> <param name="info" value="random"/> <param name="list" value="10"/> <param name="replace" value="true"/> </conditional> </conditional> <assert_stdout> <has_text_matching expression="adata.chunk_X"/> <has_text_matching expression="select=10"/> <has_text_matching expression="replace=True"/> </assert_stdout> <output name="chunk_X"> <assert_contents> <has_text_matching expression="0\t1\t2\t3\t4\t5\t6\t7\t8\t9\t10"/> </assert_contents> </output> </test> <test> <!-- test 7: uns, neighbors --> <param name="input" value="pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad"/> <conditional name="inspect"> <param name="info" value="uns"/> <param name="uns_info" value="neighbors"/> </conditional> <output name="uns_neighbors_connectivities" ftype="mtx"> <assert_contents> <has_text_matching expression="100 100 1248" /> <has_text_matching expression="4.880" /> </assert_contents> </output> <output name="uns_neighbors_distances" ftype="mtx"> <assert_contents> <has_text_matching expression="100 100 1400" /> <has_text_matching expression="4.973" /> <has_text_matching expression="4.877" /> </assert_contents> </output> </test> <test> <!-- test 8: uns, paga --> <param name="input" value="tl.paga.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad"/> <conditional name="inspect"> <param name="info" value="uns"/> <param name="uns_info" value="paga"/> </conditional> <output name="uns_paga_connectivities" ftype="mtx"> <assert_contents> <has_text_matching expression="16 16 97" /> <has_text_matching expression="1.000" /> <has_text_matching expression="8.839" /> </assert_contents> </output> <output name="uns_paga_connectivities_tree" ftype="mtx"> <assert_contents> <has_text_matching expression="16 16 15" /> <has_text_matching expression="1.000" /> </assert_contents> </output> </test> <test> <!-- test 9: uns, pca --> <param name="input" value="pp.pca.krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="uns"/> <param name="uns_info" value="pca"/> </conditional> <output name="uns_pca_variance"> <assert_contents> <has_text_matching expression="0.75409454" /> <has_text_matching expression="3.2818672e-05" /> <has_n_columns n="1" /> </assert_contents> </output> <output name="uns_pca_variance_ratio"> <assert_contents> <has_text_matching expression="0.039053127" /> <has_text_matching expression="0.00013167" /> <has_n_columns n="1" /> </assert_contents> </output> </test> <test> <!-- test 10: uns, rank_gene_groups --> <param name="input" value="tl.rank_genes_groups.krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="uns"/> <param name="uns_info" value="rank_genes_groups"/> </conditional> <output name="uns_rank_genes_groups_names"> <assert_contents> <has_n_columns n="5" /> <has_text_matching expression="Ery\tMk\tMo\tNeu\tprogenitor"/> <has_text_matching expression="Gata1\tFog1\tCebpa\tFli1\tGata2"/> <has_text_matching expression="EgrNab\tEgrNab\tSCL\tSCL\tGfi1"/> </assert_contents> </output> <output name="uns_rank_genes_groups_scores"> <assert_contents> <has_n_columns n="5" /> <has_text_matching expression="Ery\tMk\tMo\tNeu\tprogenitor"/> <has_text_matching expression="18.86\d{4}"/> <has_text_matching expression="17.85\d{4}"/> <has_text_matching expression="-2.63\d{4}"/> <has_text_matching expression="-2.98\d{4}"/> <has_text_matching expression="-6.41\d{4}"/> </assert_contents> </output> <output name="uns_rank_genes_groups_logfoldchanges"> <assert_contents> <has_n_columns n="5" /> </assert_contents> </output> <output name="uns_rank_genes_groups_pvals"> <assert_contents> <has_n_columns n="5" /> <has_text_matching expression="1.8000"/> </assert_contents> </output> <output name="uns_rank_genes_groups_pvals_adj"> <assert_contents> <has_n_columns n="5" /> <has_text_matching expression="1.98004"/> </assert_contents> </output> </test> <test> <!-- test 11: obsm, X_pca --> <param name="input" value="pp.pca.krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="obsm"/> <param name="obsm_info" value="X_pca"/> </conditional> <output name="obsm_X_pca"> <assert_contents> <has_text_matching expression="0.00030471283" /> <has_text_matching expression="3.4109413e-05" /> <has_text_matching expression="-0.6401007" /> <has_n_columns n="10" /> </assert_contents> </output> </test> <test> <!-- test 12: obsm_info, X_umap --> <param name="input" value="tl.umap.h5ad"/> <conditional name="inspect"> <param name="info" value="obsm"/> <param name="obsm_info" value="X_umap"/> </conditional> <output name="obsm_X_umap"> <assert_contents> <has_text text="1.664" /> <has_text text="5.425" /> <has_text text="-1.748" /> <has_text text="-9.714" /> <has_n_columns n="2" /> </assert_contents> </output> </test> <test> <!-- test 13: obsm_info, X_tsne --> <param name="input" value="tl.tsne.h5ad"/> <conditional name="inspect"> <param name="info" value="obsm"/> <param name="obsm_info" value="X_tsne"/> </conditional> <output name="obsm_X_tsne"> <assert_contents> <has_text text="14.301989" /> <has_text text="-19.447426" /> <has_n_columns n="2" /> </assert_contents> </output> </test> <test> <!-- test 14: obsm_info, X_draw_graph --> <param name="input" value="tl.draw_graph.h5ad"/> <conditional name="inspect"> <param name="info" value="obsm"/> <param name="obsm_info" value="X_draw_graph"/> </conditional> <output_collection name="obsm_X_draw_graph"> <element name="fr"> <assert_contents> <has_text text="-39.77" /> <has_text text="-24.83" /> <has_text text="-34.34" /> <has_text text="-22.34" /> <has_n_columns n="2" /> </assert_contents> </element> </output_collection> </test> <test> <!-- test 15: obsm_info, X_diffmap --> <param name="input" value="tl.diffmap.h5ad"/> <conditional name="inspect"> <param name="info" value="obsm"/> <param name="obsm_info" value="X_diffmap"/> </conditional> <output name="obsm_X_diffmap"> <assert_contents> <has_text text="0.1006" /> <has_text text="-0.0619" /> <has_n_columns n="15" /> </assert_contents> </output> </test> <test> <!-- test 16: varm_info, PCs --> <param name="input" value="pp.pca.krumsiek11.h5ad"/> <conditional name="inspect"> <param name="info" value="varm"/> <param name="varm_info" value="PCs"/> </conditional> <output name="varm_PCs"> <assert_contents> <has_text_matching expression="0.2352" /> <has_text_matching expression="-0.0492" /> <has_n_columns n="10" /> </assert_contents> </output> </test> </tests> <help><![CDATA[ **What it does** This tool inspects a AnnData dataset and returns: - General information about the object as text - The full data matrix (`X`) as a Tabular - A chunk of the data matrix as a Tabular, using the `chunk_X method <https://anndata.readthedocs.io/en/latest/anndata.AnnData.chunk_X.html>`__ - Key-indexed observations annotation (`obs`) as a Tabular - Key-indexed annotation of variables/features (`var`) as a Tabular @HELP@ ]]></help> <expand macro="citations"/> </tool>