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comparison qiime2-2020.8/qiime_dada2_denoise-single.xml @ 20:d93d8888f0b0 draft

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author florianbegusch
date Fri, 04 Sep 2020 12:44:24 +0000
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19:6c48f8d82424 20:d93d8888f0b0
1 <?xml version="1.0" ?>
2 <tool id="qiime_dada2_denoise-single" name="qiime dada2 denoise-single"
3 version="2020.8">
4 <description>Denoise and dereplicate single-end sequences</description>
5 <requirements>
6 <requirement type="package" version="2020.8">qiime2</requirement>
7 </requirements>
8 <command><![CDATA[
9 qiime dada2 denoise-single
10
11 --i-demultiplexed-seqs=$idemultiplexedseqs
12
13 --p-trunc-len=$ptrunclen
14
15 --p-trim-left=$ptrimleft
16
17 --p-max-ee=$pmaxee
18
19 --p-trunc-q=$ptruncq
20
21 #if str($ppoolingmethod) != 'None':
22 --p-pooling-method=$ppoolingmethod
23 #end if
24
25 #if str($pchimeramethod) != 'None':
26 --p-chimera-method=$pchimeramethod
27 #end if
28
29 --p-min-fold-parent-over-abundance=$pminfoldparentoverabundance
30
31 --p-n-threads=$pnthreads
32
33 --p-n-reads-learn=$pnreadslearn
34
35 #if $pnohashedfeatureids:
36 --p-no-hashed-feature-ids
37 #end if
38
39 --o-table=otable
40
41 --o-representative-sequences=orepresentativesequences
42
43 --o-denoising-stats=odenoisingstats
44
45 #if str($examples) != 'None':
46 --examples=$examples
47 #end if
48
49 ;
50 cp odenoisingstats.qza $odenoisingstats
51
52 ]]></command>
53 <inputs>
54 <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" />
55 <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" type="text" />
56 <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" />
57 <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" />
58 <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" />
59 <param label="--p-pooling-method: " name="ppoolingmethod" optional="True" type="select">
60 <option selected="True" value="None">Selection is Optional</option>
61 <option value="independent">independent</option>
62 <option value="pseudo">pseudo</option>
63 </param>
64 <param label="--p-chimera-method: " name="pchimeramethod" optional="True" type="select">
65 <option selected="True" value="None">Selection is Optional</option>
66 <option value="none">none</option>
67 <option value="consensus">consensus</option>
68 <option value="pooled">pooled</option>
69 </param>
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" />
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" />
72 <param label="--p-no-hashed-feature-ids: Do not if true, 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: True]" name="pnohashedfeatureids" selected="False" type="boolean" />
73 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
74
75 </inputs>
76
77 <outputs>
78 <data format="qza" label="${tool.name} on ${on_string}: table.qza" name="otable" />
79 <data format="qza" label="${tool.name} on ${on_string}: representativesequences.qza" name="orepresentativesequences" />
80 <data format="qza" label="${tool.name} on ${on_string}: denoisingstats.qza" name="odenoisingstats" />
81
82 </outputs>
83
84 <help><![CDATA[
85 Denoise and dereplicate single-end sequences
86 ###############################################################
87
88 This method denoises single-end sequences, dereplicates them, and filters
89 chimeras.
90
91 Parameters
92 ----------
93 demultiplexed_seqs : SampleData[SequencesWithQuality | PairedEndSequencesWithQuality]
94 The single-end demultiplexed sequences to be denoised.
95 trunc_len : Int
96 Position at which sequences should be truncated due to decrease in
97 quality. This truncates the 3' end of the of the input sequences, which
98 will be the bases that were sequenced in the last cycles. Reads that
99 are shorter than this value will be discarded. If 0 is provided, no
100 truncation or length filtering will be performed
101 trim_left : Int, optional
102 Position at which sequences should be trimmed due to low quality. This
103 trims the 5' end of the of the input sequences, which will be the bases
104 that were sequenced in the first cycles.
105 max_ee : Float, optional
106 Reads with number of expected errors higher than this value will be
107 discarded.
108 trunc_q : Int, optional
109 Reads are truncated at the first instance of a quality score less than
110 or equal to this value. If the resulting read is then shorter than
111 `trunc_len`, it is discarded.
112 pooling_method : Str % Choices('independent', 'pseudo'), optional
113 The method used to pool samples for denoising. "independent": Samples
114 are denoised independently. "pseudo": The pseudo-pooling method is used
115 to approximate pooling of samples. In short, samples are denoised
116 independently once, ASVs detected in at least 2 samples are recorded,
117 and samples are denoised independently a second time, but this time
118 with prior knowledge of the recorded ASVs and thus higher sensitivity
119 to those ASVs.
120 chimera_method : Str % Choices('consensus', 'none', 'pooled'), optional
121 The method used to remove chimeras. "none": No chimera removal is
122 performed. "pooled": All reads are pooled prior to chimera detection.
123 "consensus": Chimeras are detected in samples individually, and
124 sequences found chimeric in a sufficient fraction of samples are
125 removed.
126 min_fold_parent_over_abundance : Float, optional
127 The minimum abundance of potential parents of a sequence being tested
128 as chimeric, expressed as a fold-change versus the abundance of the
129 sequence being tested. Values should be greater than or equal to 1
130 (i.e. parents should be more abundant than the sequence being tested).
131 This parameter has no effect if chimera_method is "none".
132 n_threads : Int, optional
133 The number of threads to use for multithreaded processing. If 0 is
134 provided, all available cores will be used.
135 n_reads_learn : Int, optional
136 The number of reads to use when training the error model. Smaller
137 numbers will result in a shorter run time but a less reliable error
138 model.
139 hashed_feature_ids : Bool, optional
140 If true, the feature ids in the resulting table will be presented as
141 hashes of the sequences defining each feature. The hash will always be
142 the same for the same sequence so this allows feature tables to be
143 merged across runs of this method. You should only merge tables if the
144 exact same parameters are used for each run.
145
146 Returns
147 -------
148 table : FeatureTable[Frequency]
149 The resulting feature table.
150 representative_sequences : FeatureData[Sequence]
151 The resulting feature sequences. Each feature in the feature table will
152 be represented by exactly one sequence.
153 denoising_stats : SampleData[DADA2Stats]
154 ]]></help>
155 <macros>
156 <import>qiime_citation.xml</import>
157 </macros>
158 <expand macro="qiime_citation"/>
159 </tool>