annotate cluster_embed.xml @ 1:51dbb534fbce draft default tip

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit bb79cb8cad3bc1433bff7caf9d7b45e7993dd470
author iuc
date Sat, 22 Apr 2023 12:13:18 +0000
parents 43711b22f28b
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43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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1 <tool id="episcanpy_cluster_embed" name="Cluster, embed and annotate" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
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2 <description>with EpiScanpy</description>
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3 <macros>
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4 <import>macros.xml</import>
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5 </macros>
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6 <expand macro="bio_tools"/>
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7 <expand macro="requirements"/>
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8 <expand macro="version_command"/>
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9 <command detect_errors="exit_code"><![CDATA[
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10 @CMD@
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11 ]]></command>
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12 <configfiles>
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13 <configfile name="script_file"><![CDATA[
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14 @CMD_imports@
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15 @CMD_read_inputs@
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16 import episcanpy as esc
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17 #if $method.method == 'pp.lazy'
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18 esc.pp.lazy(
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19 adata,
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20 pp_pca=$method.lazy_pp_pca,
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21 svd_solver='$method.lazy_svd_solver',
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22 nb_pcs=$method.lazy_nb_pcs,
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23 n_neighbors=$method.lazy_n_neighbors,
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24 perplexity=$method.lazy_perplexity,
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25 method='$method.lazy_method',
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26 metric='$method.lazy_metric',
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27 min_dist=$method.lazy_min_dist,
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28 spread=$method.lazy_spread,
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29 use_highly_variable=$method.lazy_use_highly_variable,
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30 n_components=$method.lazy_n_components,
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31 )
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32
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33 #else if $method.method == 'tl.rank_features'
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34 esc.tl.rank_features(
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35 adata,
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36 omic='ATAC',
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37 groupby='$method.rank_features_groupby',
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38 use_raw=$method.rank_features_use_raw,
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39 groups='$method.rank_features_groups',
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40 reference='$method.rank_features_reference',
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41 n_features=$method.rank_features_n_features,
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42 rankby_abs=$method.rank_features_rankby_abs,
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43 key_added='$method.rank_features_key_added',
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44 copy=False,
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45 method='$method.rank_features_method',
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46 corr_method='$method.rank_features_corr_method'
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47 )
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48
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49 #else if $method.method == 'tl.get_n_clusters'
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50 esc.tl.getNClusters(
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51 adata,
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52 n_cluster=$method.get_n_clusters_n_cluster,
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53 range_min=$method.get_n_clusters_range_min,
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54 range_max=$method.get_n_clusters_range_max,
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55 max_steps=$method.get_n_clusters_max_steps,
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56 method='$method.get_n_clusters_method',
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57 key_added='$method.get_n_clusters_key_added'
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58 )
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59
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60 #else if $method.method == 'tl.kmeans'
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61 esc.tl.kmeans(
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62 adata,
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63 num_clusters=$method.kmeans_num_clusters
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64 )
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65
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66 #else if $method.method == 'tl.hc'
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67 esc.tl.hc(
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68 adata,
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69 num_clusters=$method.hc_num_clusters
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70 )
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71 #end if
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72 adata.write('anndata.h5ad')
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73 ]]></configfile>
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74 </configfiles>
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75 <inputs>
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76 <expand macro="inputs_anndata"/>
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77 <conditional name="method">
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78 <param argument="method" type="select" label="Method used for Clustering or Embedding">
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79 <option value="pp.lazy">Embedding: Automatically compute PCA coordinates, loadings and variance decomposition, a neighborhood graph of observations, t-distributed stochastic neighborhood embedding (tSNE) Uniform Manifold Approximation and Projection (UMAP), using 'pp.lazy'</option>
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80 <option value="tl.rank_features">Rank features for characterizing groups, using 'tl.rank_features'</option>
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81 <option value="tl.get_n_clusters">Clustering: Test different settings of louvain to obtain the target number of clusters, using 'tl.getNClusters'</option>
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82 <option value="tl.kmeans">Clustering: Compute kmeans clustering using X_pca fits, using 'tl.kmeans'</option>
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83 <option value="tl.hc">Clustering: Compute hierarchical clustering using X_pca fits, using 'tl.hc'</option>
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84 </param>
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85 <when value="pp.lazy">
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86 <param name="lazy_pp_pca" value="True" type="select" label="Compute PCA coordinates before the neighborhood graph" help="(pp_pca)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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87 <option value="True" selected="true">True</option>
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88 <option value="False">False</option>
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89 </param>
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iuc
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90 <param name="lazy_svd_solver" type="select" label="SVD solver to use" help="(svd_solver)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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91 <option value="arpack" selected="true">arpack (for the ARPACK wrapper in SciPy)</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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92 <option value="randomized">randomized (for the randomized algorithm due to Halko (2009)</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
iuc
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93 <option value="auto">auto (chooses automatically depending on the size of the problem)</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
iuc
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94 <option value="lobpcg">lobpcg (an alternative SciPy solver)</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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95 </param>
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96 <param name="lazy_nb_pcs" value="50" min="0" type="integer" label="Number of principal component computed for PCA (and therefore neighbors, tsne and umap)" help="(nb_pcs)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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97 <param name="lazy_n_neighbors" value="15" min="0" type="integer" label="Size of the local neighborhood (number of neighboring data points) used for manifold approximation" help="(n_neighbors)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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98 <param name="lazy_perplexity" value="30" min="0" type="integer" label="Perplexity (number of nearest neighbors used in other manifold learning algorithms)" help="(perplexity)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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99 <param name="lazy_method" type="select" label="Kernel to use for computing connectivities" help="(method)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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100 <option value="umap" selected="true">umap</option>
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101 <option value="gauss">gauss</option>
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102 </param>
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103 <param name="lazy_metric" type="select" label="Metric that returns a distance" help="(metric)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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104 <option value="euclidean" selected="true">euclidean</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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105 <option value="cityblock">cityblock</option>
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106 <option value="cosine">cosine</option>
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107 <option value="l1">l1</option>
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108 <option value="l2">l2</option>
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109 <option value="manhattan">manhattan</option>
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110 <option value="braycurtis">braycurtis</option>
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111 <option value="canberra">canberra</option>
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112 <option value="chebyshev">chebyshev</option>
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113 <option value="correlation">correlation</option>
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114 <option value="dice">dice</option>
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115 <option value="hamming">hamming</option>
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116 <option value="jaccard">jaccard</option>
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117 <option value="kulsinski">kulsinski</option>
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118 <option value="mahalanobis">mahalanobis</option>
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119 <option value="minkowski">minkowski</option>
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120 <option value="rogerstanimoto">rogerstanimoto</option>
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121 <option value="russelrao">russelrao</option>
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122 <option value="seuclidean">seuclidean</option>
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123 <option value="sokalmichener">sokalmichener</option>
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124 <option value="sokalsneath">sokalsneath</option>
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125 <option value="sqeuclidean">sqeuclidean</option>
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126 <option value="yule">yule</option>
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127 </param>
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128 <param name="lazy_min_dist" value="0.5" min="0" type="float" label="The effective minimum distance between embedded points" help="(min_dist)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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129 <param name="lazy_spread" value="1.0" type="float" label="The effective scale of embedded points" help="(spread)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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130 <param name="lazy_use_highly_variable" type="select" label="Use highly variable genes only" help="(use_highly_variable)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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131 <option value="True">True</option>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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132 <option value="False" selected="true">False</option>
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133 </param>
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134 <param name="lazy_n_components" value="2" min="0" type="integer" label="The number of dimensions of the UMAP embedding" help="(n_components)"/>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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135 </when>
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136 <when value="tl.rank_features">
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137 <param name="rank_features_groupby" value="louvain" type="text" label="The key of the observations grouping to consider" help="(groupby)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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138 <sanitizer invalid_char="">
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139 <valid initial="string.letters,string.digits">
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140 <add value="_" />
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141 <add value="-" />
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142 <add value=" " />
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143 <add value="." />
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144 </valid>
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145 </sanitizer>
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146 <validator type="regex">[0-9a-zA-Z_. -]+</validator>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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147 </param>
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148 <param name="rank_features_use_raw" type="select" label="Use raw attribute of Anndata if present" help="(use_raw)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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149 <option value="True" selected="true">True</option>
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150 <option value="False">False</option>
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151 </param>
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152 <param name="rank_features_groups" value="all" type="text" label="Subset of groups, to which comparison shall be restricted" help="(groups)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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153 <sanitizer invalid_char="">
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154 <valid initial="string.letters,string.digits">
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155 <add value="_" />
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iuc
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156 <add value="-" />
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157 <add value="." />
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158 <add value=" " />
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159 <add value="," />
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160 </valid>
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161 </sanitizer>
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162 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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163 </param>
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164 <param name="rank_features_reference" value="rest" type="text" label="Compare each group with respect to this group" help="(reference)">
43711b22f28b planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit ce8ee43d7285503a24c7b0f55c09c513be8c66f5
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165 <sanitizer invalid_char="">
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166 <valid initial="string.letters,string.digits">
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167 <add value="_" />
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168 <add value="-" />
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169 <add value="." />
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170 <add value=" " />
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171 <add value="," />
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172 </valid>
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173 </sanitizer>
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174 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
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175 </param>
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176 <param name="rank_features_n_features" value="100" min="1" type="integer" label="The number of features that appear in the returned tables" help="(n_features)"/>
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177 <param name="rank_features_rankby_abs" type="select" label="Rank genes by the absolute value of the score, not by the score" help="(rankby_abs)">
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178 <option value="True" >True</option>
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179 <option value="False" selected="true">False</option>
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180 </param>
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181 <param name="rank_features_key_added" value="rank_features_groups" type="text" label="The key in adata.uns information is saved to" help="(key_added)">
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182 <sanitizer invalid_char="">
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183 <valid initial="string.letters,string.digits">
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184 <add value="_" />
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185 <add value="-" />
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186 <add value="." />
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187 <add value=" " />
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188 <add value="," />
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189 </valid>
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190 </sanitizer>
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191 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
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192 </param>
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193 <param name="rank_features_method" type="select" label="Method to use" help="(method)">
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194 <option value="" selected="true">Auto select for ATAC</option>
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195 <option value="logreg">Logistic regression</option>
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196 <option value="t-test" >t-test</option>
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197 <option value="t-test_overestim_var">t-test_overestim_var</option>
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198 <option value="wilcoxon">Wilcoxon rank sum</option>
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199 </param>
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200 <param name="rank_features_corr_method" value="benjamini-hochberg" type="select" label="p-value correction method" help="(corr_method)">
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201 <option value="benjamini-hochberg">Benjamini Hochberg</option>
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202 <option value="bonferroni">Bonferroni</option>
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203 </param>
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204 </when>
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205 <when value="tl.get_n_clusters">
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206 <param name="get_n_clusters_n_cluster" value="14" min="1" type="integer" label="Number of clusters" help="(n_cluster)"/>
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207 <param name="get_n_clusters_method" type="select" label="Clustering method to use" help="(method)">
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208 <option value="leiden" selected="true">leiden</option>
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209 <option value="louvain">louvain</option>
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210 </param>
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211 <param name="get_n_clusters_range_min" value="0" min="0" type="integer" label="Range minimum" help="(range_min)"/>
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212 <param name="get_n_clusters_range_max" value="3" min="1" type="integer" label="Range maximum" help="(range_max)"/>
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213 <param name="get_n_clusters_max_steps" value="20" min="1" type="integer" label="Maximum number of steps" help="(max_steps)"/>
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214 <param name="get_n_clusters_key_added" value="None" type="text" label="Variable name in obs" help="(key_added)">
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215 <sanitizer invalid_char="">
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216 <valid initial="string.letters,string.digits">
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217 <add value="_" />
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218 <add value="-" />
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219 <add value="." />
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220 <add value=" " />
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221 <add value="," />
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222 </valid>
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223 </sanitizer>
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224 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
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225 </param>
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226 </when>
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227 <when value="tl.kmeans">
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228 <param name="kmeans_num_clusters" value="14" min="1" type="integer" label="Number of clusters" help="(num_clusters)"/>
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229 </when>
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230 <when value="tl.hc">
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231 <param name="hc_num_clusters" value="14" min="1" type="integer" label="Number of clusters" help="(num_clusters)"/>
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232 </when>
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233 </conditional>
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234 <expand macro="inputs_common_advanced"/>
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235 </inputs>
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236 <outputs>
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237 <expand macro="anndata_outputs"/>
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238 </outputs>
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239 <tests>
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240 <test expect_num_outputs="2">
1
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241 <!-- pp.lazy -->
0
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242 <param name="adata" value="krumsiek11.h5ad" />
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243 <conditional name="method">
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244 <param name="method" value="pp.lazy"/>
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245 <param name="lazy_pp_pca" value="True"/>
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246 <param name="lazy_svd_solver" value="arpack"/>
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247 <param name="lazy_nb_pcs" value="5"/>
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248 <param name="lazy_pp_n_neighbors" value="15"/>
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249 <param name="lazy_pp_perplexity" value="30"/>
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250 <param name="lazy_method" value="umap"/>
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251 <param name="lazy_metric" value="euclidean"/>
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252 <param name="lazy_min_dist" value="0.5"/>
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253 <param name="lazy_spread" value="1.0"/>
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254 <param name="lazy_use_highly_variable" value="False"/>
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255 <param name="lazy_n_components" value="2"/>
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256 </conditional>
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257 <section name="advanced_common">
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258 <param name="show_log" value="true" />
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259 </section>
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260 <output name="hidden_output">
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261 <assert_contents>
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262 <has_text_matching expression="esc.pp.lazy"/>
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263 <has_text_matching expression="adata"/>
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264 <has_text_matching expression="nb_pcs=5"/>
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265 </assert_contents>
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266 </output>
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267 <output name="anndata_out" file="krumsiek11.pp.lazy.h5ad" ftype="h5ad" compare="sim_size"/>
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268 </test>
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269 <test expect_num_outputs="2">
1
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270 <!-- tl.rank_features -->
0
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271 <param name="adata" value="krumsiek11.pp.lazy.tl.louvain.h5ad" />
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272 <conditional name="method">
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273 <param name="method" value="tl.rank_features"/>
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274 <param name="rank_features_groupby" value="louvain"/>
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275 <param name="rank_features_use_raw" value="False"/>
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276 <param name="rank_features_groups" value="all"/>
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277 <param name="rank_features_reference" value="rest"/>
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278 <param name="rank_features_n_features" value="100"/>
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279 <param name="rank_features_rankby_abs" value="False"/>
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280 <param name="rank_features_key_added" value="rank_features_groups"/>
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281 <param name="rank_features_method" value=""/>
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282 <param name="rank_features_corr_method" value="benjamini-hochberg"/>
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283 </conditional>
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284 <section name="advanced_common">
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285 <param name="show_log" value="true" />
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286 </section>
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287 <output name="anndata_out" file="krumsiek11.tl.rank_features.h5ad" ftype="h5ad">
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288 <assert_contents>
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289 <has_h5_keys keys="obs, uns, obsm, varm, obsp" />
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290 </assert_contents>
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291 </output>
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292 </test>
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293 <test expect_num_outputs="2">
1
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294 <!-- tl.get_n_clusters -->
0
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295 <param name="adata" value="krumsiek11.pp.lazy.tl.louvain.h5ad" />
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296 <conditional name="method">
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297 <param name="method" value="tl.get_n_clusters"/>
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298 <param name="get_n_clusters_n_clusters" value="3"/>
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299 <param name="get_n_clusters_method" value="louvain"/>
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300 <param name="get_n_clusters_range_min" value="0"/>
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301 <param name="get_n_clusters_range_max" value="3"/>
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302 <param name="get_n_clusters_max_steps" value="20"/>
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303 <conditional name="get_n_clusters_obs_key">
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304 <param name="get_n_clusters_key_added" value="None"/>
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305 </conditional>
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306 </conditional>
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307 <section name="advanced_common">
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308 <param name="show_log" value="true" />
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309 </section>
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310 <output name="anndata_out" file="krumsiek11.tl.get_n_clusters.h5ad" ftype="h5ad"/>
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311 </test>
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312 <test expect_num_outputs="2">
1
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313 <!-- tl.kmeans -->
0
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314 <param name="adata" value="krumsiek11.pp.lazy.h5ad" />
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315 <conditional name="method">
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316 <param name="method" value="tl.kmeans"/>
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317 <param name="kmeans_num_clusters" value="14"/>
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318 </conditional>
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319 <section name="advanced_common">
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320 <param name="show_log" value="true" />
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321 </section>
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322 <output name="anndata_out" file="krumsiek11.tl.kmeans.h5ad" ftype="h5ad"/>
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323 </test>
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324 <test expect_num_outputs="2">
1
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325 <!-- tl.hc -->
0
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326 <param name="adata" value="krumsiek11.pp.lazy.h5ad" />
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327 <conditional name="method">
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328 <param name="method" value="tl.hc"/>
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329 <param name="hc_num_clusters" value="14"/>
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330 </conditional>
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331 <section name="advanced_common">
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332 <param name="show_log" value="true" />
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333 </section>
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334 <output name="anndata_out" file="krumsiek11.tl.hc.h5ad" ftype="h5ad"/>
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335 </test>
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336 </tests>
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337 <help><![CDATA[
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338
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339 Automatically compute PCA coordinates (`pp.lazy`)
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340 ========================================================================================
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341 This function automatically computes PCA coordinates, loadings and variance decomposition, a neighborhood graph of
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342 observations, t-distributed stochastic neighborhood embedding (tSNE) Uniform Manifold Approximation and Projection (UMAP).
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343
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344 More details on the `episcanpy documentation
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345 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.lazy.html>`__
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346
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347 Automatically obtain target number of clusters (`tl.getNClusters`)
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348 ========================================================================================
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349 This function will test different settings of louvain to obtain the target number of clusters.
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350
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351 More details on the `episcanpy documentation
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352 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.tl.getNClusters.html>`__
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353
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354 Perform kmeans clustering (`tl.kmeans`)
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355 ========================================================================================
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356 This function will perform kmeans clustering using X_pca fits.
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357
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358 More details on the `episcanpy documentation
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359 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.tl.kmeans.html>`__
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360
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361 Compute hierarchical clustering using X_pca fits (`tl.hc`)
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362 ===================================================================
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363
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364 This function computes heirarchical clustering using X_pca fits using random_state=2019.
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365
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366 More details on the `episcanpy documentation
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367 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.tl.hc.html>`__
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368 ]]></help>
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369 <expand macro="citations"/>
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370 </tool>