--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/qiime2/qiime_dada2_denoise-single.xml	Fri Sep 04 13:12:49 2020 +0000
@@ -0,0 +1,159 @@
+<?xml version="1.0" ?>
+<tool id="qiime_dada2_denoise-single" name="qiime dada2 denoise-single"
+      version="2020.8">
+  <description>Denoise and dereplicate single-end sequences</description>
+  <requirements>
+    <requirement type="package" version="2020.8">qiime2</requirement>
+  </requirements>
+  <command><![CDATA[
+qiime dada2 denoise-single
+
+--i-demultiplexed-seqs=$idemultiplexedseqs
+
+--p-trunc-len=$ptrunclen
+
+--p-trim-left=$ptrimleft
+
+--p-max-ee=$pmaxee
+
+--p-trunc-q=$ptruncq
+
+#if str($ppoolingmethod) != 'None':
+--p-pooling-method=$ppoolingmethod
+#end if
+
+#if str($pchimeramethod) != 'None':
+--p-chimera-method=$pchimeramethod
+#end if
+
+--p-min-fold-parent-over-abundance=$pminfoldparentoverabundance
+
+--p-n-threads=$pnthreads
+
+--p-n-reads-learn=$pnreadslearn
+
+#if $pnohashedfeatureids:
+ --p-no-hashed-feature-ids
+#end if
+
+--o-table=otable
+
+--o-representative-sequences=orepresentativesequences
+
+--o-denoising-stats=odenoisingstats
+
+#if str($examples) != 'None':
+--examples=$examples
+#end if
+
+;
+cp odenoisingstats.qza $odenoisingstats
+
+  ]]></command>
+  <inputs>
+    <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" />
+    <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" />
+    <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" />
+    <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" />
+    <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" />
+    <param label="--p-pooling-method: " name="ppoolingmethod" optional="True" type="select">
+      <option selected="True" value="None">Selection is Optional</option>
+      <option value="independent">independent</option>
+      <option value="pseudo">pseudo</option>
+    </param>
+    <param label="--p-chimera-method: " name="pchimeramethod" optional="True" type="select">
+      <option selected="True" value="None">Selection is Optional</option>
+      <option value="none">none</option>
+      <option value="consensus">consensus</option>
+      <option value="pooled">pooled</option>
+    </param>
+    <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" />
+    <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" />
+    <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" />
+    <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
+    
+  </inputs>
+
+  <outputs>
+    <data format="qza" label="${tool.name} on ${on_string}: table.qza" name="otable" />
+    <data format="qza" label="${tool.name} on ${on_string}: representativesequences.qza" name="orepresentativesequences" />
+    <data format="qza" label="${tool.name} on ${on_string}: denoisingstats.qza" name="odenoisingstats" />
+    
+  </outputs>
+
+  <help><![CDATA[
+Denoise and dereplicate single-end sequences
+###############################################################
+
+This method denoises single-end sequences, dereplicates them, and filters
+chimeras.
+
+Parameters
+----------
+demultiplexed_seqs : SampleData[SequencesWithQuality | PairedEndSequencesWithQuality]
+    The single-end demultiplexed sequences to be denoised.
+trunc_len : Int
+    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
+trim_left : Int, optional
+    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.
+max_ee : Float, optional
+    Reads with number of expected errors higher than this value will be
+    discarded.
+trunc_q : Int, optional
+    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.
+pooling_method : Str % Choices('independent', 'pseudo'), optional
+    The method used to pool samples for denoising. "independent": Samples
+    are denoised independently. "pseudo": The pseudo-pooling method is used
+    to approximate pooling of samples. In short, samples are denoised
+    independently once, ASVs detected in at least 2 samples are recorded,
+    and samples are denoised independently a second time, but this time
+    with prior knowledge of the recorded ASVs and thus higher sensitivity
+    to those ASVs.
+chimera_method : Str % Choices('consensus', 'none', 'pooled'), optional
+    The method used to remove chimeras. "none": No chimera removal is
+    performed. "pooled": All reads are pooled prior to chimera detection.
+    "consensus": Chimeras are detected in samples individually, and
+    sequences found chimeric in a sufficient fraction of samples are
+    removed.
+min_fold_parent_over_abundance : Float, optional
+    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".
+n_threads : Int, optional
+    The number of threads to use for multithreaded processing. If 0 is
+    provided, all available cores will be used.
+n_reads_learn : Int, optional
+    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.
+hashed_feature_ids : Bool, optional
+    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.
+
+Returns
+-------
+table : FeatureTable[Frequency]
+    The resulting feature table.
+representative_sequences : FeatureData[Sequence]
+    The resulting feature sequences. Each feature in the feature table will
+    be represented by exactly one sequence.
+denoising_stats : SampleData[DADA2Stats]
+  ]]></help>
+  <macros>
+    <import>qiime_citation.xml</import>
+  </macros>
+  <expand macro="qiime_citation"/>
+</tool>
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