annotate clustering.xml @ 0:59bc96331073 draft default tip

planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
author frogs
date Thu, 28 Feb 2019 10:14:49 -0500
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59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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1 <?xml version="1.0"?>
59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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2 <!--
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3 # Copyright (C) 2015 INRA
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4 #
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5 # This program is free software: you can redistribute it and/or modify
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6 # it under the terms of the GNU General Public License as published by
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7 # the Free Software Foundation, either version 3 of the License, or
59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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8 # (at your option) any later version.
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9 #
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10 # This program is distributed in the hope that it will be useful,
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11 # but WITHOUT ANY WARRANTY; without even the implied warranty of
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12 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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13 # GNU General Public License for more details.
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14 #
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15 # You should have received a copy of the GNU General Public License
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16 # along with this program. If not, see <http://www.gnu.org/licenses/>.
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17 -->
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18 <tool id="FROGS_clustering" name="FROGS Clustering swarm" version="3.1">
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19 <description>Single-linkage clustering on sequences</description>
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20 <requirements>
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21 <requirement type="package" version="3.1.0">frogs</requirement>
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22 </requirements>
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23 <stdio>
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24 <exit_code range="1:" />
59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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25 <exit_code range=":-1" />
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26 </stdio>
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27 <command>
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28 clustering.py
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29 --nb-cpus \${GALAXY_SLOTS:-1}
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30 --distance $maximal_distance
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31 --input-fasta $sequence_file
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32 --input-count $count_file
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33 --output-biom $abundance_biom
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34 --output-fasta $seed_file
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35 --output-compo $swarms_composition
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36 $denoising
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37 </command>
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38 <inputs>
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39 <!-- Files -->
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40 <param format="fasta" name="sequence_file" type="data" label="Sequences file" help="The sequences file (format: fasta)." optional="false" />
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41 <param format="tabular" name="count_file" type="data" label="Count file" help="It contains the count by sample for each sequence (format: TSV)." optional="false" />
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42 <!-- Parameters -->
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43 <param name="maximal_distance" type="integer" label="Aggregation distance" help="Maximum number of differences between sequences in each aggregation step." value="3" min="1" max="15" optional="false" />
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44 <param name="denoising" type="boolean" checked="true" truevalue="--denoising" falsevalue="" label="Performe denoising clustering step?" help="If checked, clustering will be perform in two steps, first with distance = 1 and then with your input distance"/>
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45 </inputs>
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46 <outputs>
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47 <data format="fasta" name="seed_file" label="${tool.name}: seed_sequences.fasta" from_work_dir="seeds.fasta"/>
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48 <data format="biom1" name="abundance_biom" label="${tool.name}: abundance.biom" from_work_dir="abundance.biom" />
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49 <data format="tabular" name="swarms_composition" label="${tool.name}: swarms_composition.tsv" from_work_dir="swarms.tsv"/>
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50 </outputs>
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51 <tests>
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52 <test>
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53 <param name="sequence_file" value="references/01-prepro-vsearch.fasta"/>
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54 <param name="count_file" value="references/01-prepro-vsearch.tsv"/>
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55 <param name="maximal_distance" value="3"/>
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56 <param name="denoising" value="true"/>
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57 <output name="seed_file" file="references/02-clustering.fasta" compare="sim_size" delta="0" />
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58 <!-- output name="abundance_biom" file="references/02-clustering.biom" -->
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59 <!-- Voila deux autres facon de comparer: (Mais ca ne marche pas dans ce cas car les fichiers générés par planemo sont vraiments différents comparé à nos test manuels (cf. /tmp/frogs-test-result-olivier /tmp/frogs-test-result-olivier2) -->
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60 <!-- cf. https://docs.galaxyproject.org/en/latest/dev/schema.html#tool-tests-test-output -->
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61 <!--output name="abundance_biom" file="references/02-clustering.biom" compare="sim_size" delta="10"/-->
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62 <!--output name="abundance_biom" file="references/02-clustering.biom" compare="diff" lines_diff="1"/-->
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63 <output name="swarms_composition" file="references/02-clustering_compo.tsv" compare="sim_size" delta="0" />
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64 </test>
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65 </tests>
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66 <help>
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67
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68 .. image:: static/images/frogs_images/FROGS_logo.png
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69 :height: 144
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70 :width: 110
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71
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72
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73 .. class:: infomark page-header h2
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74
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75 What it does
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76
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77 Single-linkage clustering on sequences.
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78
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79
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80 .. class:: infomark page-header h2
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81
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82 Inputs/Outputs
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83
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84 .. class:: h3
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85
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86 Inputs
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87
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88 **Sequences file**:
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89
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90 The sequence file with all samples sequences (format `FASTA &lt;https://en.wikipedia.org/wiki/FASTA_format&gt;`_). These sequences are dereplicated: strictly identical sequence are represented only one and the initial count is kept in count file.
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91
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92 The sequence ID must be "sequenceID;size=X" with X equal to the total abundance among all samples.
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93
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94 *It corresponds to one output of FROGS Pre-process tools.*
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95
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96 **Count file**:
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97
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98 This file contains the count of all uniq sequences in each sample (format `TSV &lt;https://en.wikipedia.org/wiki/Tab-separated_values&gt;`_).
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99
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100 Example::
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101
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102 #id splA splB
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103 seq1 1289 2901
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104 seq2 3415 0
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105
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106
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107 .. class:: h3
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108
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109 Outputs
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110
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111 **Abundance file** (abundance.biom):
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112
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113 The abundance of each cluster in each sample (format `BIOM &lt;http://biom-format.org/&gt;`_). This format is widely used in metagenomic softwares.
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114
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115
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116 **Clusters seeds** (seed_sequences.fasta):
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117
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118 The clusters representative sequences (format `FASTA &lt;https://en.wikipedia.org/wiki/FASTA_format&gt;`_).
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119
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120
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121 **Clusters composition** (swarms_composition.tsv):
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122
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123 A text file representing the read composition of each cluster (format txt). Each line represents one cluster and is composed of read identifier separated by space.
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124
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125
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126 .. class:: infomark page-header h2
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127
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128 How it works
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129
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130 .. csv-table::
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131 :header: "Steps", "With denoising", "Without denoising"
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132 :widths: 5, 150, 150
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133 :class: table table-striped
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134
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135 "1", "Sorting the reads by their abundance", "Sorting the reads by their abundance"
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136 "2", "Clusters the reads (`Swarm &lt;https://github.com/torognes/swarm&gt;`_). The distance parameter is 1", "/"
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137 "3", "Sorting the pre-clusters by their abundance", "/"
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138 "4", "Clusters the pre-clusters (`Swarm &lt;https://github.com/torognes/swarm&gt;`_) with the distance you specify", "Clusters the reads (`Swarm &lt;https://github.com/torognes/swarm&gt;`_) with the distance you specify"
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139
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140 **Swarm focus**
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141
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142 Swarm use an iterative growth process and the use of sequence abundance values to delineate OTUs.
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143
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144 .. image:: static/images/frogs_images/FROGS_cluster_swarm.png
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145 :height: 223
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146 :width: 666
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147
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148 In each groth step the sequence of the previous step is used to find the others sequences with a number of differences inferior or equal to the "Aggregation distance".
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149
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150 After agregation Swarm refines the clusters by looking at the abundancies along the connections. Theoritically the abundances must decrease when you are going away from the seed (which is often the most abundant sequence). If this abundance raises again it means that two different clusters are connected by some poorly abundant sequences, so swarm cut the connection.
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151
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152
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153 .. class:: infomark page-header h2
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154
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155 Advices
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156
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157 The denoising step allows to build very fine clusters with minimal differences. In this case, the number of differences is equal at 1 between sequences of each crowns. This first clustering is extremly quick. After the denoising, a second swarm is run with an aggregation distance >1 as you have configured, between seeds from this first clustering.
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158
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159 To have some metrics on your clusters, you can use the tool **FROGS Clusters Stat**.
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160
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161
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162 ----
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163
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164 **Contact**
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165
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166 Contacts: frogs@inra.fr
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167
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168 Repository: https://github.com/geraldinepascal/FROGS
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169 website: http://frogs.toulouse.inra.fr/
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170
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171 Please cite the **FROGS article**: *Escudie F., et al. Bioinformatics, 2018. FROGS: Find, Rapidly, OTUs with Galaxy Solution.*
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172
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173 </help>
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174 <citations>
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175 <citation type="doi">10.1093/bioinformatics/btx791</citation>
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176 </citations>
59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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59bc96331073 planemo upload for repository https://github.com/geraldinepascal/FROGS-wrappers/tree/v3.1.0 commit 08296fc88e3e938c482c631bd515b3b7a0499647
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178 </tool>