| Next changeset 1:2a5036c29889 (2024-10-31) |
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Commit message:
planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit 721eaced787aa3b04d96ad91f6b4540f26b23949 |
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added:
main_macros.xml squidpy_scatter.py squidpy_spatial.py squidpy_spatial.xml test-data/imc.h5ad test-data/imc_centrality_scores.png test-data/imc_co_occurrence.png test-data/imc_interaction_matrix.png test-data/imc_kmeans.h5ad test-data/imc_nhood_enrichment.png test-data/imc_ripley.png test-data/imc_sn.h5ad test-data/scatter_image.png |
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| diff -r 000000000000 -r 5b17a47d1ade main_macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/main_macros.xml Thu Jul 11 22:22:41 2024 +0000 |
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| @@ -0,0 +1,64 @@ +<macros> + <token name="@TOOL_VERSION@">1.5.0</token> + <token name="@PROFILE@">20.01</token> + <token name="@VERSION_SUFFIX@">1</token> + + <xml name="macro_stdio"> + <stdio> + <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error" /> + </stdio> + </xml> + + <xml name="squidpy_requirements"> + <requirements> + <requirement type="package" version="@TOOL_VERSION@">squidpy</requirement> + </requirements> + </xml> + + <xml name="citations"> + <citations> + <citation type="doi">10.1038/s41592-021-01358-2</citation> + </citations> + </xml> + + <xml name="squidpy_spatial_options"> + <section name="options" title="Advanced Graph Options" expanded="false"> + <yield/> + <!-- <param argument="copy" type="hidden" value="false" help="If True, return the result, otherwise save it to the adata object." /> --> + </section> + </xml> + + <xml name="squidpy_plotting_options"> + <section name="plotting_options" title="Plotting Options" expanded="false"> + <yield /> + <!-- <param argument="legend_kwargs" type="text" value="" optional="true" label="Keyword arguments for matplotlib.pyplot.legend()" /> --> + <param argument="figsize" type="text" value="" optional="true" label="Size of the figure in inches" help="Optional. e.g.: (12, 12)." /> + <param argument="dpi" type="integer" value="" optional="true" label="Dots per inch" help="Optional" /> + </section> + </xml> + + <xml name="squidpy_plotting_option_palette"> + <param argument="palette" type="text" value="" optional="true" label="Categorical colormap for the clusters" help="Comma delimited for multiple. If None, use anndata.AnnData.uns ['{cluster_key}_colors'], if available." /> + </xml> + + <xml name="squidpy_plotting_options_more"> + <expand macro="squidpy_plotting_options"> + <yield /> + <param argument="annotate" type="boolean" checked="false" label="Whether to annotate the cells of the heatmap?" /> + <param argument="method" type="select" label="The linkage method to be used for dendrogram/clustering" help="see scipy.cluster.hierarchy.linkage()."> + <option value="none" selected="true">None</option> + <option value="single">single</option> + <option value="complete">complete</option> + <option value="average">average</option> + <option value="weighted">weighted</option> + <option value="centroid">centroid</option> + <option value="median">median</option> + <option value="ward">ward</option> + </param> + <param argument="title" type="text" value="" optional="true" label="The title of the plot" help="Optional." /> + <param argument="cmap" type="text" value="viridis" label="Continuous colormap to use" help="Refer to `matplotlib.pyplot.cmap`." /> + <!-- <param argument="cbar_kwargs" type="text" value="" label="Keyword arguments for matplotlib.figure.Figure.colorbar()" /> --> + <expand macro="squidpy_plotting_option_palette" /> + </expand> + </xml> +</macros> |
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| diff -r 000000000000 -r 5b17a47d1ade squidpy_scatter.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/squidpy_scatter.py Thu Jul 11 22:22:41 2024 +0000 |
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| @@ -0,0 +1,87 @@ +import argparse +import ast +import json +import warnings + +import squidpy as sq +from anndata import read_h5ad + + +def main(inputs, output_plot): + + """ + inputs : str + File path to galaxy tool JSON inputs config file + output_plot: str + File path to save the plotting image + """ + warnings.simplefilter('ignore') + + # read inputs JSON + with open(inputs, 'r') as param_handler: + params = json.load(param_handler) + + # collapse param dict hierarchy, parse inputs + plot_opts = params.pop('plot_opts') + legend_opts = params.pop('legend_opts') + aes_opts = params.pop('aesthetic_opts') + options = {**params, **plot_opts, **legend_opts, **aes_opts} + + # read input anndata file + adata_fh = options.pop('anndata') + adata = read_h5ad(adata_fh) + + # ensure spatial coords in anndata.obsm['spatial'] + # if not, populate with user provided X/Y coord column names + x, y = options.pop('x_coord'), options.pop('y_coord') + if 'spatial' not in adata.obsm: + try: + adata.obsm['spatial'] = adata.obs[[x, y]].values + except Exception as e: + print(e) + + # scan thru tool params, + # replace None values, and reformat specific parameters + for k, v in options.items(): + if not isinstance(v, str): + continue + + if v in ('', 'none'): + options[k] = None + continue + + if k == 'groups': + options[k] = [e.strip() for e in v.split(',')] + + elif k == 'crop_coord': + # split str on commas into tuple of coords + # then nest in list (expected by squidpy function) + options[k] = [tuple([int(e.strip()) for e in v.split(',')])] + + elif k == 'figsize': + options[k] = ast.literal_eval(v) + + # not exposing this parameter for now. Only useful to change for ST data + # and can otherwise just be problematic. + # Explicitly setting to None is necessary to avoid an error + options['shape'] = None + + # call squidpy spatial scatter function, unpack tool params + sq.pl.spatial_scatter( + adata=adata, + save='image.png', + **options + ) + + +if __name__ == '__main__': + + aparser = argparse.ArgumentParser() + aparser.add_argument( + "-i", "--inputs", dest="inputs", required=True) + aparser.add_argument( + "-p", "--output_plot", dest="output_plot", required=False) + + args = aparser.parse_args() + + main(args.inputs, args.output_plot) |
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| diff -r 000000000000 -r 5b17a47d1ade squidpy_spatial.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/squidpy_spatial.py Thu Jul 11 22:22:41 2024 +0000 |
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| @@ -0,0 +1,105 @@ +import argparse +import ast +import json +import warnings + +import pandas as pd +import squidpy as sq +from anndata import read_h5ad + + +def main(inputs, anndata, output, output_plot): + """ + Parameter + --------- + inputs : str + File path to galaxy tool parameter. + anndata : str + File path to anndata containing phenotyping info. + output : str + File path to output. + output_plot: str or None + File path to save the plotting image. + """ + warnings.simplefilter('ignore') + + with open(inputs, 'r') as param_handler: + params = json.load(param_handler) + + adata = read_h5ad(anndata) + + if 'spatial' not in adata.obsm: + try: + adata.obsm['spatial'] = adata.obs[['X_centroid', 'Y_centroid']].values + except Exception as e: + print(e) + + tool = params['analyses']['selected_tool'] + tool_func = getattr(sq.gr, tool) + + options = params['analyses']['options'] + + for k, v in options.items(): + if not isinstance(v, str): + continue + + if v in ('', 'none'): + options[k] = None + continue + + if k == 'genes': # for spatial_autocorr and sepal + options[k] = [e.strip() for e in v.split(',')] + elif k == 'radius': # for spatial_neighbors + options[k] = ast.literal_eval(v) + elif k == 'interactions': # for ligrec + options[k] = pd.read_csv(v, sep="\t") + elif k == 'max_neighs': + options[k] = int(v) # for sepal + + cluster_key = params['analyses'].get('cluster_key') + if cluster_key: + tool_func(adata, cluster_key, **options) + else: + tool_func(adata, **options) + + if output_plot: + plotting_options = params['analyses']['plotting_options'] + for k, v in plotting_options.items(): + if not isinstance(v, str): + continue + + if v in ('', 'none'): + plotting_options[k] = None + continue + + if k == 'figsize': + options[k] = ast.literal_eval(v) + elif k in ('palette', 'score', 'source_groups', 'target_groups'): + options[k] = [e.strip() for e in v.split(',')] + elif k == 'means_range': # ligrec + v = v.strip() + if v[0] == '(': + v = v[1:] + if v[-1] == ')': + v = v[:-1] + options[k] = tuple([float(e.strip()) for e in v.split(',', 1)]) + + plotting_func = getattr(sq.pl, tool) + if cluster_key: + plotting_func(adata, cluster_key, save=output_plot, **plotting_options) + else: # TODO Remove this, since all plottings need cluster key + plotting_func(adata, save=output_plot, **plotting_options) + + adata.write(output) + + +if __name__ == '__main__': + aparser = argparse.ArgumentParser() + aparser.add_argument("-i", "--inputs", dest="inputs", required=True) + aparser.add_argument("-e", "--output", dest="output", required=True) + aparser.add_argument("-a", "--anndata", dest="anndata", required=True) + aparser.add_argument("-p", "--output_plot", dest="output_plot", required=False) + + args = aparser.parse_args() + + main(args.inputs, args.anndata, args.output, args.output_plot) |
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| diff -r 000000000000 -r 5b17a47d1ade squidpy_spatial.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/squidpy_spatial.xml Thu Jul 11 22:22:41 2024 +0000 |
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| b'@@ -0,0 +1,338 @@\n+<tool id="squidpy_spatial" name="Analyze and visualize spatial multi-omics data" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">\n+ <description>with Squidpy</description>\n+ <macros>\n+ <import>main_macros.xml</import>\n+ </macros>\n+ <edam_operations>\n+ <edam_operation>operation_3443</edam_operation>\n+ </edam_operations>\n+ <expand macro="squidpy_requirements"/>\n+ <expand macro="macro_stdio" />\n+ <version_command>echo "@TOOL_VERSION@"</version_command>\n+ <command detect_errors="aggressive">\n+ <![CDATA[\n+ export TQDM_DISABLE=True &&\n+ python \'$__tool_directory__/squidpy_spatial.py\'\n+ --inputs \'$inputs\'\n+ --anndata \'$anndata\'\n+ --output \'$output\'\n+ #if $analyses.selected_tool in [\'nhood_enrichment\', \'centrality_scores\', \'interaction_matrix\', \'ligrec\', \'ripley\', \'co_occurrence\']:\n+ --output_plot image.png\n+ #end if\n+ ]]>\n+ </command>\n+ <configfiles>\n+ <inputs name="inputs" data_style="paths"/>\n+ </configfiles>\n+ <inputs>\n+ <param name="anndata" type="data" format="h5ad" label="Select the input anndata" />\n+ <conditional name="analyses">\n+ <param name="selected_tool" type="select" label="Select an analysis">\n+ <option value="spatial_neighbors" selected="true">Spatial neighbors -- Create a graph from spatial coordinates</option>\n+ <option value="nhood_enrichment">nhood_enrichment -- Compute neighborhood enrichment by permutation test.</option>\n+ <option value="co_occurrence" >co_occurrence -- Compute co-occurrence probability of clusters</option>\n+ <option value="centrality_scores">centrality_scores -- Compute centrality scores per cluster or cell type</option>\n+ <option value="interaction_matrix">interaction_matrix -- Compute interaction matrix for clusters</option>\n+ <option value="ripley">ripley -- Calculate various Ripley\xe2\x80\x99s statistics for point processes</option>\n+ <option value="ligrec">ligrec -- Perform the permutation test as described in [Efremova et al., 2020]</option>\n+ <option value="spatial_autocorr">spatial_autocorr -- Calculate Global Autocorrelation Statistic (Moran\xe2\x80\x99s I or Geary\xe2\x80\x99s C)</option>\n+ <option value="sepal">sepal -- Identify spatially variable genes with Sepal</option>\n+ </param>\n+ <when value="spatial_neighbors">\n+ <expand macro="squidpy_spatial_options">\n+ <param argument="spatial_key" type="text" value="spatial" optional="false" label="The Key where spatial coordinates are stored" help="Key in `anndata.AnnData.obsm`." />\n+ <param argument="coord_type" type="select" label="Type of coordinate system">\n+ <option value="grid" selected="true">grid</option>\n+ <option value="generic">generic</option>\n+ <option value="none">None - use `grid` when `spatial_key` is in `anndata.AnnData.uns with `n_neighs` = 6 (Visium), otherwise `generic`</option>\n+ </param>\n+ <param argument="n_neighs" type="integer" value="6" label="Number of neighboring tiles" help="When the `coord_type` is generic, this\'s number of neighborhoods for non-grid data and only used when `delaunay` is False." />\n+ <param argument="radius" type="text" value="" optional="true" label="Radius" help="Only available when coord_type = \'generic\'. If float, this is the neighborhood radius to compute the graph; if tuple, this is edge range [min(radius), max(radius)] used prune the final graph." />\n+ <param argument="delaunay" type="boolean" checked="false" optional="true" label="Whether to compute the graph from Delaunay triangulation" help="Only used when coord_type = \'generic\'." />\n+ '..b'al>\n+ </inputs>\n+ <outputs>\n+ <data format="h5ad" name="output" label="Squidpy.gr.${analyses.selected_tool} on ${on_string}" />\n+ <data from_work_dir="figures/image.png" format="png" name="output_plot" label="Squidpy.pl.${analyses.selected_tool} on ${on_string}" >\n+ <filter>analyses[\'selected_tool\'] in [\'nhood_enrichment\', \'centrality_scores\', \'interaction_matrix\', \'ligrec\', \'ripley\', \'co_occurrence\']</filter>\n+ </data>\n+ </outputs>\n+ <tests>\n+ <test expect_num_outputs="1">\n+ <param name="anndata" value="imc.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="spatial_neighbors" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/spatial_neighbors" />\n+ </assert_contents>\n+ </output>\n+ </test>\n+ <test expect_num_outputs="2">\n+ <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="nhood_enrichment" />\n+ <param name="cluster_key" value="cell type" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/cell type_nhood_enrichment" />\n+ </assert_contents>\n+ </output>\n+ <output name="output_plot" file="imc_nhood_enrichment.png" compare="sim_size" delta="2000" />\n+ </test>\n+ <test expect_num_outputs="2">\n+ <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="co_occurrence" />\n+ <param name="cluster_key" value="cell type" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/cell type_co_occurrence" />\n+ </assert_contents>\n+ </output>\n+ <output name="output_plot" file="imc_co_occurrence.png" compare="sim_size" delta="2000" />\n+ </test>\n+ <test expect_num_outputs="2">\n+ <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="centrality_scores" />\n+ <param name="cluster_key" value="cell type" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/cell type_centrality_scores" />\n+ </assert_contents>\n+ </output>\n+ <output name="output_plot" file="imc_centrality_scores.png" compare="sim_size" delta="2000" />\n+ </test>\n+ <test expect_num_outputs="2">\n+ <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="interaction_matrix" />\n+ <param name="cluster_key" value="cell type" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/cell type_interactions" />\n+ </assert_contents>\n+ </output>\n+ <output name="output_plot" file="imc_interaction_matrix.png" compare="sim_size" delta="2000" />\n+ </test>\n+ <test expect_num_outputs="2">\n+ <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />\n+ <param name="selected_tool" value="ripley" />\n+ <param name="cluster_key" value="cell type" />\n+ <output name="output">\n+ <assert_contents>\n+ <has_h5_keys keys="uns/cell type_ripley_F" />\n+ </assert_contents>\n+ </output>\n+ <output name="output_plot" file="imc_ripley.png" compare="sim_size" delta="2000" />\n+ </test>\n+ </tests>\n+ <help>\n+ <![CDATA[\n+**What it does**\n+\n+This tool includes various of single cell spatial analysis utils provided by Squidpy.\n+\n+**Input**\n+\n+*AnnData*\n+\n+**Output**\n+\n+*Anndata*\n+\n+*Plotting (PNG) if applicable*\n+\n+\n+ ]]>\n+ </help>\n+ <expand macro="citations" />\n+</tool>\n' |
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