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1 <?xml version="1.0" ?>
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2 <tool id="qiime_dada2_denoise-single" name="qiime dada2 denoise-single" version="2019.4">
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3 <description> - Denoise and dereplicate single-end sequences</description>
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4 <requirements>
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5 <requirement type="package" version="2019.4">qiime2</requirement>
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6 </requirements>
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7 <command><![CDATA[
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8 qiime dada2 denoise-single
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9
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10 --i-demultiplexed-seqs=$idemultiplexedseqs
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11
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4
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12 #if str($ptrunclen):
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13 --p-trunc-len="$ptrunclen"
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14 #end if
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15
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16 #if str($ptrimleft):
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2
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17 --p-trim-left=$ptrimleft
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18 #end if
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19
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4
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20 #if str($pmaxee):
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2
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21 --p-max-ee=$pmaxee
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22 #end if
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23
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4
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24 #if str($ptruncq):
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2
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25 --p-trunc-q=$ptruncq
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26 #end if
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27
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28 #if str($pchimeramethod) != 'None':
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29 --p-chimera-method=$pchimeramethod
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30 #end if
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31
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4
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32 #if str($pminfoldparentoverabundance):
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2
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33 --p-min-fold-parent-over-abundance=$pminfoldparentoverabundance
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34 #end if
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35
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36 #set $pnthreads = '${GALAXY_SLOTS:-4}'
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37 #if str($pnthreads):
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38 --p-n-threads="$pnthreads"
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39 #end if
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40
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41
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4
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42 #if str($pnreadslearn):
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2
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43 --p-n-reads-learn=$pnreadslearn
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44 #end if
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45
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4
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46 #if str($pnohashedfeatureids):
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2
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47 --p-no-hashed-feature-ids
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48 #end if
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49
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50 --o-table=otable
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51 --o-representative-sequences=orepresentativesequences
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52 --o-denoising-stats=odenoisingstats
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53 ;
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54 cp otable.qza $otable;
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55 cp orepresentativesequences.qza $orepresentativesequences;
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56 cp odenoisingstats.qza $odenoisingstats
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57 ]]></command>
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58 <inputs>
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59 <param format="qza,no_unzip.zip" label="--i-demultiplexed-seqs: ARTIFACT SampleData[SequencesWithQuality | PairedEndSequencesWithQuality] The single-end demultiplexed sequences to be denoised. [required]" name="idemultiplexedseqs" optional="False" type="data"/>
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60 <param label="--p-trunc-len: INTEGER Position at which sequences should be truncated due to decrease in quality. This truncates the 3' end of the of the input sequences, which will be the bases that were sequenced in the last cycles. Reads that are shorter than this value will be discarded. If 0 is provided, no truncation or length filtering will be performed [required]" name="ptrunclen" optional="False" value="" type="integer"/>
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61 <param label="--p-trim-left: INTEGER Position at which sequences should be trimmed due to low quality. This trims the 5' end of the of the input sequences, which will be the bases that were sequenced in the first cycles. [default: 0]" name="ptrimleft" optional="True" type="integer" value="0"/>
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62 <param label="--p-max-ee: NUMBER Reads with number of expected errors higher than this value will be discarded. [default: 2.0]" name="pmaxee" optional="True" type="float" value="2.0"/>
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63 <param label="--p-trunc-q: INTEGER Reads are truncated at the first instance of a quality score less than or equal to this value. If the resulting read is then shorter than `trunc-len`, it is discarded. [default: 2]" name="ptruncq" optional="True" type="integer" value="2"/>
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64 <param label="--p-chimera-method: " name="pchimeramethod" optional="True" type="select">
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65 <option selected="True" value="None">Selection is Optional</option>
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66 <option value="consensus">consensus</option>
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67 <option value="pooled">pooled</option>
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68 <option value="none">none</option>
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69 </param>
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70 <param label="--p-min-fold-parent-over-abundance: NUMBER The minimum abundance of potential parents of a sequence being tested as chimeric, expressed as a fold-change versus the abundance of the sequence being tested. Values should be greater than or equal to 1 (i.e. parents should be more abundant than the sequence being tested). This parameter has no effect if chimera-method is 'none'. [default: 1.0]" name="pminfoldparentoverabundance" optional="True" type="float" value="1.0"/>
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71 <param label="--p-n-reads-learn: INTEGER The number of reads to use when training the error model. Smaller numbers will result in a shorter run time but a less reliable error model. [default: 1000000]" name="pnreadslearn" optional="True" type="integer" value="1000000"/>
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4
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72 <param label="--p-no-hashed-feature-ids: If false, the feature ids in the resulting table will be presented as hashes of the sequences defining each feature. The hash will always be the same for the same sequence so this allows feature tables to be merged across runs of this method. You should only merge tables if the exact same parameters are used for each run. [default: False]" name="pnohashedfeatureids" selected="False" type="boolean"/>
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2
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73 </inputs>
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74 <outputs>
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75 <data format="qza" label="${tool.name} on ${on_string}: table.qza" name="otable"/>
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76 <data format="qza" label="${tool.name} on ${on_string}: representativesequences.qza" name="orepresentativesequences"/>
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77 <data format="qza" label="${tool.name} on ${on_string}: denoisingstats.qza" name="odenoisingstats"/>
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78 </outputs>
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79 <help><![CDATA[
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80 Denoise and dereplicate single-end sequences
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81 ############################################
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82
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83 This method denoises single-end sequences, dereplicates them, and filters
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84 chimeras.
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85
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86 Parameters
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87 ----------
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88 demultiplexed_seqs : SampleData[SequencesWithQuality | PairedEndSequencesWithQuality]
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89 The single-end demultiplexed sequences to be denoised.
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90 trunc_len : Int
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91 Position at which sequences should be truncated due to decrease in
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92 quality. This truncates the 3' end of the of the input sequences, which
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93 will be the bases that were sequenced in the last cycles. Reads that
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94 are shorter than this value will be discarded. If 0 is provided, no
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95 truncation or length filtering will be performed
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96 trim_left : Int, optional
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97 Position at which sequences should be trimmed due to low quality. This
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98 trims the 5' end of the of the input sequences, which will be the bases
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99 that were sequenced in the first cycles.
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100 max_ee : Float, optional
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101 Reads with number of expected errors higher than this value will be
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102 discarded.
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103 trunc_q : Int, optional
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104 Reads are truncated at the first instance of a quality score less than
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105 or equal to this value. If the resulting read is then shorter than
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106 `trunc_len`, it is discarded.
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107 chimera_method : Str % Choices('consensus', 'pooled', 'none'), optional
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108 The method used to remove chimeras. "none": No chimera removal is
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109 performed. "pooled": All reads are pooled prior to chimera detection.
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110 "consensus": Chimeras are detected in samples individually, and
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111 sequences found chimeric in a sufficient fraction of samples are
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112 removed.
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113 min_fold_parent_over_abundance : Float, optional
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114 The minimum abundance of potential parents of a sequence being tested
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115 as chimeric, expressed as a fold-change versus the abundance of the
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116 sequence being tested. Values should be greater than or equal to 1
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117 (i.e. parents should be more abundant than the sequence being tested).
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118 This parameter has no effect if chimera_method is "none".
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119 n_reads_learn : Int, optional
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120 The number of reads to use when training the error model. Smaller
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121 numbers will result in a shorter run time but a less reliable error
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122 model.
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123 hashed_feature_ids : Bool, optional
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124 If true, the feature ids in the resulting table will be presented as
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125 hashes of the sequences defining each feature. The hash will always be
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126 the same for the same sequence so this allows feature tables to be
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127 merged across runs of this method. You should only merge tables if the
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128 exact same parameters are used for each run.
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129
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130 Returns
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131 -------
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132 table : FeatureTable[Frequency]
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133 The resulting feature table.
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134 representative_sequences : FeatureData[Sequence]
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135 The resulting feature sequences. Each feature in the feature table will
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136 be represented by exactly one sequence.
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137 denoising_stats : SampleData[DADA2Stats]
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138 ]]></help>
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139 <macros>
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140 <import>qiime_citation.xml</import>
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141 </macros>
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142 <expand macro="qiime_citation"/>
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143 </tool>
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