Mercurial > repos > iuc > hyphy_gard

annotate hyphy_gard.xml @ 23:a0731e81e0c2 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ commit 2742ee3b4e90f65352845265d2f85c4263e0eabb"
author iuc
date Tue, 20 Apr 2021 10:25:18 +0000
parents 42efcb0955e6
children 1fb98a84e86d
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1 <?xml version="1.0"?>
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2 <tool id="hyphy_gard" name="HyPhy-GARD" version="@VERSION@+galaxy0" profile="19.09">
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3 <description>Genetic Algorithm for Recombination Detection</description>
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4 <macros>
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5 <import>macros.xml</import>
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6 <token name="@OPERATION@">GARD</token>
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7 <token name="@operation@">gard</token>
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8 </macros>
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9 <expand macro="requirements"/>
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10 <command detect_errors="exit_code"><![CDATA[
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11 ln -s '$input_file' input.$input_file.extension &&
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12 #set $input_file = 'input.%s' % $input_file.extension
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13 @HYPHYMPI@ gard
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14 --alignment ./$input_file
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15 --type '$datatype.value'
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16 #if str($datatype.value) == 'codon':
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17 --code '$datatype.gencodeid'
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18 #elif str($datatype.value) == 'amino-acid':
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19 --model '$datatype.model'
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20 #end if
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21 #if str($rate_cond.rate):
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22 --rv '$rate_cond.rate'
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23 --rate-classes '$rate_classes'
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24 #end if
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25 --output '$translated'
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26 --output-lf '$gard_output'
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27 > '$gard_log'
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28 ;
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29 @CATCH_ERROR@
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30 ]]></command>
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31 <inputs>
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32 <param name="input_file" type="data" format="fasta,fasta.gz,nex" label="Input FASTA or NEXUS file" />
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33 <conditional name="datatype">
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34 <param argument="--type" name="value" type="select" label="Alignment kind">
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35 <option value="nucleotide">Nucleotide</option>
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36 <option value="amino-acid">Amino acid</option>
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37 <option value="codon">Codon</option>
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38 </param>
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39 <when value="nucleotide"/>
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40 <when value="amino-acid">
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41 <expand macro="substitution" />
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42 </when>
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43 <when value="codon">
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44 <expand macro="gencode" />
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45 </when>
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46 </conditional>
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47 <conditional name="rate_cond">
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48 <param argument="--rv" name="rate" type="select" label="Rate variation">
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49 <option value="">None</option>
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50 <option value="GDD">General Discrete</option>
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51 <option value="Gamma">Beta-Gamma</option>
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52 </param>
5
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53 <when value=""/>
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54 <when value="GDD">
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55 <param argument="--rate-classes" name="rate_classes" type="integer" value="2" min="2" max="6" label="Rate classes" />
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56 </when>
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57 <when value="Gamma">
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58 <param argument="--rate-classes" name="rate_classes" type="integer" value="2" min="2" max="6" label="Rate classes" />
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59 </when>
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60 </conditional>
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61 </inputs>
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62 <outputs>
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63 <data name="gard_log" format="txt"/>
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64 <data name="gard_output" format="nex" />
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65 <data name="translated" format="hyphy_results.json" />
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66 </outputs>
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67 <tests>
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68 <test>
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69 <param name="input_file" ftype="fasta" value="gard-in1.fa"/>
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70 <output name="gard_output" file="gard-out1.nex" compare="sim_size"/>
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71 </test>
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72 </tests>
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73 <help><![CDATA[
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74
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75 GARD : Genetic Algorithms for Recombination Detection.
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76 ======================================================
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77
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78 What does this do?
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79 ------------------
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80
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81 This tools screens an alignment of sequences for evidence of recombination in one or more sequences.
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82 The main idea is that if sufficient recombination has occurred, then no single phylogenetic tree will
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83 properly fit the entire length of the alignment and instead a separate tree will be preferred for each *nonrecombinant* segment.
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84
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85 Brief description
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86 -----------------
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87
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88 This analysis implements a heuristic approach to screening alignments of sequences for
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89 recombination, by using the CHC genetic algorithm (GA) to search for
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90 phylogenetic incongruence among different partitions of the data. The
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91 number of partitions is determined using a step-up procedure, while the
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92 placement of breakpoints is searched for with the GA. The best fitting
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93 model (based on c-AIC) is returned; and additional post-hoc tests run to
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94 distinguish topological incongruence from rate-variation.
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95
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96 For each identified breakpoint, the support for its placement is calculated, and for each
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97 non-recombinant fragment, a phylogenetic tree is inferred (using neighbor joining) and returned.
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98
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99 Input
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100 -----
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101
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102 A *FASTA* sequence alignment
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103
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104 Output
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105 ------
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106
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107 A JSON file with analysis results (http://hyphy.org/resources/json-fields.pdf).
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108
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109 A custom visualization module for viewing these results is available (see http://vision.hyphy.org/GARD for an example)
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110
1
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111
5
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112 Tool options
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113 ------------
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114 ::
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115
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116
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117 --type type of alignment to screen
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118 Nucleotide [default].
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119 Assumes aligned nucleotide data and screens the alignment using
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120 the general time reversible model of sequence evolution.
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121 This is the fastest option
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122 Protein
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123 Assumes aligned aminoacid sequences. One of several protein
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124 substitution models may be used to screen the alignment.
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125 Codon
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126 Assumes an in-frame coding sequence alignment.
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127 The Muse-Gaut 94 (GTR) model will be used to screen the alignment.
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128 Selecting this option will dramatically increase run times.
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129
1
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130
5
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131 --code Genetic code/translation table to use (for codon alignments).
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132 Default value: Universal
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133
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134 --model The substitution model to use (for protein alignments).
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135 default value: JTT
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136
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137 --rv The discrete distribution to use for modeling site to site rate variation.
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138
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139 None [default]
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140 No rate variation. This is the fastest option in terms of run time, but
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141 using it can result in false positives if there is significant site-to-site
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142 rate variation
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143 GDD
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144 Use the general discrete distribution on N bins
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145 Beta-Gamma
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146 Use a discretized gamma with weights partitioned by a discretized beta
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147 (see doi.org/10.1093/molbev/msi009)
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148
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149 --rate-classes How many site rate classes to use (if GDD or Beta-Gamma are selected)
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150 default value: 4
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151
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152
0
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153 ]]></help>
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154 <expand macro="citations">
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155 <citation type="doi">10.1093/molbev/msl051</citation>
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156 </expand>
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157 </tool>