annotate scanpy-neighbours.xml @ 12:c78c930e3263 draft

"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit 62f47287c7e8449c59a1f1f454852ddc669b1b1e-dirty"
author ebi-gxa
date Mon, 07 Sep 2020 14:02:36 +0000
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1 <?xml version="1.0" encoding="utf-8"?>
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2 <tool id="scanpy_compute_graph" name="Scanpy ComputeGraph" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
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3 <description>to derive kNN graph</description>
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4 <macros>
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5 <import>scanpy_macros2.xml</import>
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6 </macros>
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7 <expand macro="requirements"/>
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8 <command detect_errors="exit_code"><![CDATA[
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9 ln -s '${input_obj_file}' input.h5 &&
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10 PYTHONIOENCODING=utf-8 scanpy-neighbors
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11 #if $settings.default == "false"
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12 #if $settings.n_neighbors_file
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13 --n-neighbors \$( cat $settings.n_neighbors_file )
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14 #elif $settings.n_neighbors
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15 --n-neighbors '${settings.n_neighbors}'
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16 #end if
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17 --method '${settings.method}'
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18 --metric '${settings.metric}'
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19 --random-state '${settings.random_seed}'
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20 #if $settings.use_rep != "auto"
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21 --use-rep '${settings.use_rep}'
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22 #end if
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23 #if $settings.n_pcs
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24 --n-pcs '${settings.n_pcs}'
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25 #end if
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26 ${settings.knn}
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27 #end if
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28 @INPUT_OPTS@
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29 @OUTPUT_OPTS@
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30 ]]></command>
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31
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32 <inputs>
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33 <expand macro="input_object_params"/>
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34 <expand macro="output_object_params"/>
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35 <conditional name="settings">
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36 <param name="default" type="boolean" checked="true" label="Use programme defaults"/>
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37 <when value="true"/>
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38 <when value="false">
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39 <param name="n_neighbors" argument="--n-neighbors" type="integer" value="15" label="Maximum number of neighbors used"/>
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40 <param name="n_neighbors_file" argument="--n-neighbors" type="data" format="txt,tsv" optional="true"
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41 label="File with n_neighbours, use with parameter iterator. Overrides the n_neighbors setting"/>
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42 <param name="use_rep" type="select" label="Use the indicated representation">
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43 <option value="X_pca" selected="true">X_pca, use PCs</option>
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44 <option value="X">X, use normalised expression values</option>
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45 </param>
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46 <param name="n_pcs" argument="--n-pcs" type="integer" value="50" optional="true" label="Number of PCs to use"/>
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47 <param name="knn" argument="--knn" type="boolean" truevalue="" falsevalue="--no-knn" checked="true"
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48 label="Use hard threshold to restrict neighbourhood size (otherwise use a Gaussian kernel to down weight distant neighbors)"/>
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49 <param name="method" argument="--method" type="select" label="Method for calculating connectivity">
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50 <option value="umap" selected="true">UMAP</option>
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51 <option value="gauss">Gaussian</option>
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52 <option value="rapids">RAPIDS</option>
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53 </param>
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54 <param name="metric" argument="--metric" type="select" label="A known metric’s name">
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55 <option value="euclidean" selected="true">Euclidean</option>
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56 <option value="cityblock">cityblock</option>
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57 <option value="cosine">cosine</option>
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58 <option value="l1">l1</option>
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59 <option value="l2">l2</option>
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60 <option value="manhattan">manhattan</option>
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61 <option value="braycurtis">braycurtis</option>
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62 <option value="canberra">canberra</option>
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63 <option value="chebyshev">chebyshev</option>
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64 <option value="correlation">correlation</option>
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65 <option value="dice">dice</option>
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66 <option value="hamming">hamming</option>
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67 <option value="jaccard">jaccard</option>
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68 <option value="kulsinski">kulsinski</option>
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69 <option value="mahalanobis">mahalanobis</option>
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70 <option value="minkowski">minkowski</option>
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71 <option value="rogerstanimoto">rogerstanimoto</option>
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72 <option value="russelrao">russelrao</option>
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73 <option value="seuclidan">seuclidian</option>
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74 <option value="sokalmichener">sokalmichener</option>
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75 <option value="sokalsneath">sokalsneath</option>
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76 <option value="sqeuclidean">sqeuclidean</option>
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77 <option value="yule">yule</option>
0
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78 </param>
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79 <param name="random_seed" argument="--random-seed" type="integer" value="0" label="Seed for random number generator"/>
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80 </when>
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81 </conditional>
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82 </inputs>
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83
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84 <outputs>
5
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85 <expand macro="output_data_obj" description="Graph object"/>
0
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86 </outputs>
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87
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88 <tests>
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89 <test>
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90 <param name="input_obj_file" value="run_pca.h5"/>
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91 <param name="input_format" value="anndata"/>
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92 <param name="output_format" value="anndata"/>
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93 <param name="default" value="false"/>
11
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94 <param name="n_neighbors" value="15"/>
0
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95 <param name="n_pcs" value="50"/>
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96 <param name="knn" value="true"/>
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97 <param name="random_seed" value="0"/>
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98 <param name="method" value="umap"/>
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99 <output name="output_h5" file="compute_graph.h5" ftype="h5" compare="sim_size"/>
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100 </test>
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101 </tests>
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102
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103 <help><![CDATA[
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104 =============================================================
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105 Compute a neighborhood graph of observations (`pp.neighbors`)
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106 =============================================================
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107
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108 The neighbor search efficiency of this heavily relies on UMAP (McInnes et al, 2018),
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109 which also provides a method for estimating connectivities of data points -
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110 the connectivity of the manifold (`method=='umap'`). If `method=='diffmap'`,
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111 connectivities are computed according to Coifman et al (2005), in the adaption of
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112 Haghverdi et al (2016).
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113
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114 @HELP@
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115
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116 @VERSION_HISTORY@
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117 ]]></help>
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118 <expand macro="citations"/>
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119 </tool>