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annotate squidpy_spatial.xml @ 4:11ea000ad53f draft default tip

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author goeckslab
date Tue, 02 Jul 2024 19:54:29 +0000
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1 <tool id="squidpy_spatial" name="Analyze and visualize spatial multi-omics data" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
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2 <description>with Squidpy</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
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6 <edam_operations>
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7 <edam_operation>operation_3443</edam_operation>
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8 </edam_operations>
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9 <expand macro="squidpy_requirements"/>
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10 <expand macro="macro_stdio" />
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11 <version_command>echo "@TOOL_VERSION@"</version_command>
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12 <command detect_errors="aggressive">
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13 <![CDATA[
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14 export TQDM_DISABLE=True &&
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15 python '$__tool_directory__/squidpy_spatial.py'
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16 --inputs '$inputs'
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17 --anndata '$anndata'
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18 --output '$output'
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19 #if $analyses.selected_tool in ['nhood_enrichment', 'centrality_scores', 'interaction_matrix', 'ligrec', 'ripley', 'co_occurrence']:
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20 --output_plot image.png
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21 #end if
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22 ]]>
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23 </command>
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24 <configfiles>
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25 <inputs name="inputs" data_style="paths"/>
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26 </configfiles>
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27 <inputs>
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28 <param name="anndata" type="data" format="h5ad" label="Select the input anndata" />
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29 <conditional name="analyses">
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30 <param name="selected_tool" type="select" label="Select an analysis">
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31 <option value="spatial_neighbors" selected="true">Spatial neighbors -- Create a graph from spatial coordinates</option>
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32 <option value="nhood_enrichment">nhood_enrichment -- Compute neighborhood enrichment by permutation test.</option>
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33 <option value="co_occurrence" >co_occurrence -- Compute co-occurrence probability of clusters</option>
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34 <option value="centrality_scores">centrality_scores -- Compute centrality scores per cluster or cell type</option>
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35 <option value="interaction_matrix">interaction_matrix -- Compute interaction matrix for clusters</option>
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36 <option value="ripley">ripley -- Calculate various Ripley’s statistics for point processes</option>
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37 <option value="ligrec">ligrec -- Perform the permutation test as described in [Efremova et al., 2020]</option>
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38 <option value="spatial_autocorr">spatial_autocorr -- Calculate Global Autocorrelation Statistic (Moran’s I or Geary’s C)</option>
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39 <option value="sepal">sepal -- Identify spatially variable genes with Sepal</option>
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40 </param>
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41 <when value="spatial_neighbors">
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42 <expand macro="squidpy_spatial_options">
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43 <param argument="spatial_key" type="text" value="spatial" optional="false" label="The Key where spatial coordinates are stored" help="Key in `anndata.AnnData.obsm`." />
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44 <param argument="coord_type" type="select" label="Type of coordinate system">
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45 <option value="grid" selected="true">grid</option>
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46 <option value="generic">generic</option>
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47 <option value="none">None - use `grid` when `spatial_key` is in `anndata.AnnData.uns with `n_neighs` = 6 (Visium), otherwise `generic`</option>
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48 </param>
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49 <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." />
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50 <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." />
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51 <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'." />
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52 <param argument="n_rings" type="integer" value="1" label="Number of rings of neighbors for grid data" help="Only used when coord_type = 'grid'." />
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53 <param argument="transform" type="select" label="Type of adjacency matrix transform">
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54 <option value="none" selected="true">None</option>
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55 <option value="spectral">spectral</option>
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56 <option value="cosine">cosine</option>
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57 </param>
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58 <param argument="set_diag" type="boolean" checked="false" label="Whether to set the diagonal of the spatial connectivities to 1.0" />
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59 <param argument="key_added" type="text" value="spatial" label="The column name used in anndata to store the returned data" />
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60 </expand>
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61 </when>
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62 <when value="nhood_enrichment">
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63 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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64 <expand macro="squidpy_spatial_options">
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65 <param argument="connectivity_key" type="text" value="" optional="true" label="Key in anndata.AnnData.obsp where spatial connectivities are stored" />
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66 <param argument="n_perms" type="integer" value="1000" label="Number of permutations for the permutation test" />
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67 <param argument="seed" type="integer" value="" optional="true" label="Randomness seed" />
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68 </expand>
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69 <expand macro="squidpy_plotting_options_more">
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70 <param argument="mode" type="select" label="Choose one result from gr.nhood_enrichment to plot">
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71 <option value="zscore" selected="true">zscore</option>
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72 <option value="count">count</option>
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73 </param>
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74 </expand>
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75 </when>
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76 <when value="co_occurrence">
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77 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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78 <expand macro="squidpy_spatial_options">
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79 <param argument="spatial_key" type="text" value="spatial" optional="false" label="The Key where spatial coordinates are stored" help="Key in `anndata.AnnData.obsm`." />
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80 <param argument="interval" type="integer" value="50" label="Number of distance thresholds at which co-occurrence is computed" />
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81 <param argument="n_splits" type="integer" value="" optional="true" label="Number of splits in which to divide the spatial coordinates" help="In anndata.AnnData.obsm ['{spatial_key}']." />
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82 </expand>
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83 <expand macro="squidpy_plotting_options">
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84 <expand macro="squidpy_plotting_option_palette" />
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85 </expand>
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86 </when>
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87 <when value="centrality_scores">
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88 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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89 <expand macro="squidpy_spatial_options">
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90 <param argument="score" type="select" label="Centrality measures as described in networkx.algorithms.centrality" help="Refer to [Hagberg et al., 2008]." >
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91 <option value="none" selected="true">None</option>
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92 <option value="closeness_centrality">closeness_centrality -- measure of how close the group is to other nodes</option>
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93 <option value="average_clustering">average_clustering -- measure of the degree to which nodes cluster together</option>
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94 <option value="degree_centrality">degree_centrality -- fraction of non-group members connected to group members</option>
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95 </param>
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96 <param argument="connectivity_key" type="text" value="" optional="true" label="Key in anndata.AnnData.obsp where spatial connectivities are stored" />
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97 </expand>
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98 <expand macro="squidpy_plotting_options">
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99 <param argument="score" type="text" value="" optional="true" label="The scores to plot" help="Comma delimited for multiple. If None, plot all scores." />
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100 <expand macro="squidpy_plotting_option_palette" />
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101 </expand>
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102 </when>
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103 <when value="interaction_matrix">
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104 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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105 <expand macro="squidpy_spatial_options">
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106 <param argument="connectivity_key" type="text" value="" optional="true" label="Key in anndata.AnnData.obsp where spatial connectivities are stored" />
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107 <param argument="normalized" type="boolean" checked="false" label="Whether to normalize the sum of each row to 1" />
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108 <param argument="weights" type="boolean" checked="false" label="Whether to use edge weights or binarize" />
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109 </expand>
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110 <expand macro="squidpy_plotting_options_more"/>
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111 </when>
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112 <when value="ripley">
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113 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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114 <expand macro="squidpy_spatial_options">
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115 <param argument="mode" type="select" label="Which Ripley’s statistic to compute">
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116 <option value="F" selected="true">F</option>
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117 <option value="G">G</option>
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118 <option value="L">L</option>
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119 </param>
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120 <param argument="spatial_key" type="text" value="spatial" optional="false" label="The Key where spatial coordinates are stored" help="Key in `anndata.AnnData.obsm`." />
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121 <param argument="metric" type="select" label="Which metric to use for computing distances" help="Refer to `sklearn.neighbors.DistanceMetric`." >
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122 <option value="euclidean" selected="true">euclidean</option>
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123 <option value="manhattan">manhattan</option>
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124 <option value="chebyshev">chebyshev</option>
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125 <option value="minkowski">minkowski</option>
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126 <option value="wminkowski">wminkowski</option>
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127 <option value="seuclidean">seuclidean</option>
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128 <option value="mahalanobis">mahalanobis</option>
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129 <option value="haversine">haversine</option>
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130 <option value="hamming">hamming</option>
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131 <option value="canberra">canberra</option>
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132 <option value="braycurtis">braycurtis</option>
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133 </param>
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134 <param argument="n_neigh" type="integer" value="2" label="Number of neighbors to consider for the KNN graph" />
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135 <param argument="n_simulations" type="integer" value="100" label="Number of simulations to run for computing p-values" />
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136 <param argument="n_observations" type="integer" value="1000" label="Number of observations to generate for the Spatial Poisson Point Process" />
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137 <param argument="max_dist" type="float" value="" optional="true" label="Maximum distances for the support" help="If None, max_dist is the square root of area/2."/>
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138 <param argument="n_steps" type="integer" value="50" label="Number of steps for the support" />
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139 <param argument="seed" type="integer" value="" optional="true" label="Randomness seed" />
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140 </expand>
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141 <expand macro="squidpy_plotting_options">
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142 <param argument="mode" type="select" label="Ripley’s statistics to be plotted">
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143 <option value="F" selected="true">F</option>
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144 <option value="G">G</option>
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145 <option value="L">L</option>
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146 </param>
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147 <param argument="plot_sims" type="boolean" checked="true" label="Whether to overlay simulations in the plot" />
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148 <expand macro="squidpy_plotting_option_palette" />
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149 </expand>
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150 </when>
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151 <when value="ligrec">
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152 <param argument="cluster_key" type="text" value="" optional="false" label="Key in anndata.AnnData.obs where clustering is stored" />
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153 <expand macro="squidpy_spatial_options">
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154 <param argument="use_raw" type="boolean" checked="true" label="Whether to access anndata.AnnData.raw" />
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155 <param argument="interactions" type="data" format="tabular" optional="true" label="Select the dataset containing interaction to test" help="Must contain at least 2 columns named ‘source’ and ‘target’. Can be null, a condition under which the interactions are extracted from omnipath." />
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156 <param argument="complex_policy" type="select" label="Policy on how to handle complexes">
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157 <option value="min" selected="true">min -- select gene with the minimum average expression</option>
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158 <option value="all">all -- select all possible combinations between ‘source’ and ‘target’ complexes</option>
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159 </param>
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160 <param argument="n_perms" type="integer" value="" optional="true" label="Number of permutations for the permutation test." />
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161 <param argument="threshold" type="float" value="0.01" label="Do not perform permutation test if any of the interacting components is being expressed in less than threshold percent of cells within a given cluster" />
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162 <param argument="corr_method" type="select" label="Correction method for multiple testing">
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163 <option value="none" selected="true">None</option>
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164 <option value="bonferroni">bonferroni</option>
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165 <option value="sidak">sidak</option>
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166 <option value="holm-sidak">holm-sidak</option>
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167 <option value="holm">holm</option>
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168 <option value="simes-hochberg">simes-hochberg</option>
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169 <option value="hommel">hommel</option>
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170 <option value="fdr_bh">fdr_bh</option>
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171 <option value="fdr_by">fdr_by</option>
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172 <option value="fdr_tsbh">fdr_tsbh</option>
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173 <option value="fdr_tsbky">fdr_tsbky</option>
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174 </param>
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175 <param argument="corr_axis" type="select" label="Axis over which to perform the FDR correction" help="Only used when corr_method != None.">
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176 <option value="clusters" selected="true">clusters -- correct clusters by performing FDR correction across the interactions</option>
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177 <option value="interactions">interactions -- correct interactions by performing FDR correction across the clusters</option>
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178 </param>
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179 <param argument="key_added" type="text" value="" optional="true" label="Key in anndata to store the result" help="In `anndata.AnnData.uns`. If None, '{cluster_key}_ligrec' will be used." />
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180 <param argument="gene_symbols" type="text" value="" optional="true" label="Key in anndata.AnnData.var to use instead of anndata.AnnData.var_names" help="Optional." />
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181 <param argument="seed" type="integer" value="" label="Randomness seed" />
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182 </expand>
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183 <expand macro="squidpy_plotting_options">
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184 <param argument="source_groups" type="text" value="" optional="true" label="Source interaction clusters" help="Comma delimited. If None, select all clusters." />
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185 <param argument="target_groups" type="text" value="" optional="true" label="Target interaction clusters" help="Comma delimited. If None, select all clusters." />
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186 <param argument="means_range" type="text" value="(-inf, inf)" label="Only show interactions whose means are within this closed interval" help="Tuple of floats. e.g.: (-10, 10)." />
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187 <param argument="pvalue_threshold" type="float" value="1.0" label="Only show interactions with p-value less than this threshold" />
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188 <param argument="remove_empty_interactions" type="boolean" checked="true" label="Whether to remove rows and columns that only contain interactions with NaN values?" />
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189 <param argument="remove_nonsig_interactions" type="boolean" checked="false" label="Whether to remove rows and columns that only contain interactions that are larger than `alpha`? " />
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190 <param argument="dendrogram" type="select" label="How to cluster based on the p-values?">
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191 <option value="none" selected="true">None</option>
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192 <option value="interacting_molecules">interacting_molecules</option>
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193 <option value="interacting_clusters">interacting_clusters</option>
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194 <option value="both">both</option>
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195 </param>
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196 <param argument="alpha" type="float" value="0.001" label="Significance threshold" help="All elements with p-values less than alpha will be marked by tori instead of dots." />
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197 <param argument="swap_axes" type="boolean" checked="false" label="Whether to show the cluster combinations as rows and the interacting pairs as columns" />
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198 </expand>
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199 </when>
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200 <when value="spatial_autocorr">
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201 <expand macro="squidpy_spatial_options">
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202 <param argument="connectivity_key" type="text" value="spatial_connectivities" label="Key in anndata.AnnData.obsp where spatial connectivities are stored" />
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203 <param argument="genes" type="text" value="" optional="true" label="List of gene names, as stored in anndata.AnnData.var_names" help="Comma delitimited. Used to compute global spatial autocorrelation statistic. If None, it’s computed anndata.AnnData.var ['highly_variable']." />
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204 <param argument="mode" type="select">
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205 <option value="moran" selected="true">moran</option>
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206 <option value="geary">geary</option>
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207 </param>
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208 <param argument="transformation" type="boolean" checked="true" label="Whether to perform row-normalization on weights in anndata.AnnData.obsp ['spatial_connectivities']" />
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209 <param argument="n_perms" type="integer" value="" optional="true" label="Number of permutations for the permutation test." help="If None, only p-values under normality assumption are computed"/>
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210 <param argument="two_tailed" type="boolean" checked="false" label="Are the p-values two-tailed?" help="One-tailed, if False." />
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211 <param argument="corr_method" type="select" label="Correction method for multiple testing">
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212 <option value="none" selected="true">None</option>
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213 <option value="bonferroni">bonferroni</option>
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214 <option value="sidak">sidak</option>
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215 <option value="holm-sidak">holm-sidak</option>
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216 <option value="holm">holm</option>
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217 <option value="simes-hochberg">simes-hochberg</option>
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218 <option value="hommel">hommel</option>
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219 <option value="fdr_bh">fdr_bh</option>
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220 <option value="fdr_by">fdr_by</option>
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221 <option value="fdr_tsbh">fdr_tsbh</option>
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222 <option value="fdr_tsbky">fdr_tsbky</option>
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223 </param>
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224 <param argument="layer" type="text" value="" optional="true" label="Layer in anndata.AnnData.layers to use" help="If None, use anndata.AnnData.X." />
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225 <param argument="seed" type="integer" value="" optional="true" label="Randomness seed" />
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226 </expand>
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227 </when>
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228 <when value="sepal">
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229 <expand macro="squidpy_spatial_options">
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230 <param argument="max_neighs" type="select" label="Maximum number of neighbors of a node in the graph">
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231 <option value="4" selected="true">4 -- for a square-grid (ST, Dbit-seq)</option>
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232 <option value="6">6 -- for a hexagonal-grid (Visium)</option>
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233 </param>
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234 <param argument="genes" type="text" value="" optional="true" label="List of gene names, as stored in anndata.AnnData.var_names" help="Comma delitimited. Used to compute global spatial autocorrelation statistic. If None, it’s computed anndata.AnnData.var ['highly_variable']." />
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235 <param argument="n_iter" type="integer" value="30000" optional="true" label="Maximum number of iterations for the diffusion simulation" />
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236 <param argument="dt" type="float" value="0.001" label="Time step in diffusion simulation" />
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237 <param argument="thresh" type="float" value="1e-8" label="Entropy threshold for convergence of diffusion simulation" />
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238 <param argument="spatial_key" type="text" value="spatial" optional="false" label="The Key where spatial coordinates are stored" help="Key in `anndata.AnnData.obsm`." />
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239 <param argument="connectivity_key" type="text" value="spatial_connectivities" label="Key in anndata.AnnData.obsp where spatial connectivities are stored" />
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240 <param argument="layer" type="text" value="" optional="true" label="Layer in anndata.AnnData.layers to use" help="If None, use anndata.AnnData.X." />
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241 <param argument="use_raw" type="boolean" checked="true" label="Whether to access anndata.AnnData.raw" />
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242 </expand>
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243 </when>
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244 </conditional>
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245 </inputs>
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246 <outputs>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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247 <data format="h5ad" name="output" label="Squidpy.gr.${analyses.selected_tool} on ${on_string}" />
4
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248 <data from_work_dir="figures/image.png" format="png" name="output_plot" label="Squidpy.pl.${analyses.selected_tool} on ${on_string}" >
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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249 <filter>analyses['selected_tool'] in ['nhood_enrichment', 'centrality_scores', 'interaction_matrix', 'ligrec', 'ripley', 'co_occurrence']</filter>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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250 </data>
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251 </outputs>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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252 <tests>
1
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253 <test expect_num_outputs="1">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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254 <param name="anndata" value="imc.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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255 <param name="selected_tool" value="spatial_neighbors" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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256 <output name="output">
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257 <assert_contents>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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258 <has_h5_keys keys="uns/spatial_neighbors" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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259 </assert_contents>
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260 </output>
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261 </test>
1
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262 <test expect_num_outputs="2">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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263 <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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264 <param name="selected_tool" value="nhood_enrichment" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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265 <param name="cluster_key" value="cell type" />
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266 <output name="output">
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267 <assert_contents>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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268 <has_h5_keys keys="uns/cell type_nhood_enrichment" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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269 </assert_contents>
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270 </output>
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271 <output name="output_plot" file="imc_nhood_enrichment.png" compare="sim_size" delta="2000" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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272 </test>
1
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273 <test expect_num_outputs="2">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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274 <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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275 <param name="selected_tool" value="co_occurrence" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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276 <param name="cluster_key" value="cell type" />
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277 <output name="output">
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278 <assert_contents>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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279 <has_h5_keys keys="uns/cell type_co_occurrence" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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280 </assert_contents>
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281 </output>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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282 <output name="output_plot" file="imc_co_occurrence.png" compare="sim_size" delta="2000" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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283 </test>
1
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284 <test expect_num_outputs="2">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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285 <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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286 <param name="selected_tool" value="centrality_scores" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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287 <param name="cluster_key" value="cell type" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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288 <output name="output">
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289 <assert_contents>
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290 <has_h5_keys keys="uns/cell type_centrality_scores" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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291 </assert_contents>
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292 </output>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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293 <output name="output_plot" file="imc_centrality_scores.png" compare="sim_size" delta="2000" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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294 </test>
1
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295 <test expect_num_outputs="2">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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296 <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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297 <param name="selected_tool" value="interaction_matrix" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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298 <param name="cluster_key" value="cell type" />
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299 <output name="output">
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300 <assert_contents>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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301 <has_h5_keys keys="uns/cell type_interactions" />
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302 </assert_contents>
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303 </output>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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304 <output name="output_plot" file="imc_interaction_matrix.png" compare="sim_size" delta="2000" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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305 </test>
1
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306 <test expect_num_outputs="2">
0
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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307 <param name="anndata" value="imc_sn.h5ad" ftype="h5ad" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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308 <param name="selected_tool" value="ripley" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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309 <param name="cluster_key" value="cell type" />
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310 <output name="output">
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311 <assert_contents>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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312 <has_h5_keys keys="uns/cell type_ripley_F" />
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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313 </assert_contents>
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314 </output>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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315 <output name="output_plot" file="imc_ripley.png" compare="sim_size" delta="2000" />
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316 </test>
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317 </tests>
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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318 <help>
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319 <![CDATA[
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320 **What it does**
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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321
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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322 This tool includes various of single cell spatial analysis utils provided by Squidpy.
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323
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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324 **Input**
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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325
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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326 *AnnData*
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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327
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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328 **Output**
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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329
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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330 *Anndata*
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331
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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332 *Plotting (PNG) if applicable*
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333
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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334
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335 ]]>
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336 </help>
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337 <expand macro="citations" />
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338 </tool>