Mercurial > repos > florianbegusch > qiime2_suite
diff qiime2/qiime_feature-classifier_classify-sklearn.xml @ 14:a0a8d77a991c draft
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author | florianbegusch |
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date | Thu, 03 Sep 2020 09:51:29 +0000 |
parents | f190567fe3f6 |
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--- a/qiime2/qiime_feature-classifier_classify-sklearn.xml Thu Sep 03 09:46:00 2020 +0000 +++ b/qiime2/qiime_feature-classifier_classify-sklearn.xml Thu Sep 03 09:51:29 2020 +0000 @@ -1,75 +1,64 @@ <?xml version="1.0" ?> -<tool id="qiime_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn" version="2019.7"> - <description> - Pre-fitted sklearn-based taxonomy classifier</description> - <requirements> - <requirement type="package" version="2019.7">qiime2</requirement> - </requirements> - <command><![CDATA[ +<tool id="qiime_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn" + version="2020.8"> + <description>Pre-fitted sklearn-based taxonomy classifier</description> + <requirements> + <requirement type="package" version="2020.8">qiime2</requirement> + </requirements> + <command><![CDATA[ qiime feature-classifier classify-sklearn - -#if str( $id_to_classifier_fp.selector ) == 'history' -#set $classifier = $id_to_classifier_fp.classifier_fp ---i-classifier '$classifier' -#else: -#set $classifier = $id_to_classifier_fp.classifier_fp.fields.path ---i-classifier '$classifier' -#end if - - --i-reads=$ireads -#set $pnjobs = '${GALAXY_SLOTS:-4}' - -#if str($pnjobs): - --p-n-jobs="$pnjobs" -#end if +--i-classifier=$iclassifier +--p-n-jobs=$pnjobs -#if str($pconfidence) != '': - #if float($pconfidence) >= 0.0: - --p-confidence=$pconfidence - #end if +#if str($pconfidence) != 'None': +--p-confidence=$pconfidence #end if #if str($preadorientation) != 'None': - --p-read-orientation=$preadorientation +--p-read-orientation=$preadorientation #end if --o-classification=oclassification + +#if str($examples) != 'None': +--examples=$examples +#end if + ; cp oclassification.qza $oclassification - ]]></command> - <inputs> - <conditional name="id_to_classifier_fp" optional="True"> - <param name="selector" type="select" label="Reference classifier to query"> - <option value="cached">Public classifiers</option> - <option value="history">Classifiers from your history</option> - </param> - <when value="cached"> - <param name="classifier_fp" label="Reference classifier" type="select" optional="True"> - <options from_data_table="qiime_rep_set" /> - </param> - </when> - <when value="history"> - <param name="classifier_fp" type="data" format="qza,no_unzip.zip" label="Reference classifier" optional="True" /> - </when> - </conditional> - <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data"/> - <param label="--p-confidence: NUMBER Confidence threshold for limiting taxonomic depth. Provide -1 to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments. [default: 0.7]" name="pconfidence" optional="True" type="float" value="0.7"/> - <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select"> - <option selected="True" value="None">Selection is Optional</option> - <option value="same">same</option> - <option value="reverse-complement">reverse-complement</option> - </param> - </inputs> - <outputs> - <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification"/> - </outputs> - <help><![CDATA[ + ]]></command> + <inputs> + <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data" /> + <param format="qza,no_unzip.zip" label="--i-classifier: ARTIFACT TaxonomicClassifier The taxonomic classifier for classifying the reads. [required]" name="iclassifier" optional="False" type="data" /> + <param label="--p-confidence: " name="pconfidence" optional="True" type="select"> + <option selected="True" value="None">Selection is Optional</option> + <option value="Float % Range(0">Float % Range(0</option> + <option value="1">1</option> + <option value="inclusive_end=True">inclusive_end=True</option> + </param> + <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select"> + <option selected="True" value="None">Selection is Optional</option> + <option value="same">same</option> + <option value="reverse-complement">reverse-complement</option> + <option value="auto">auto</option> + </param> + <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> + + </inputs> + + <outputs> + <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification" /> + + </outputs> + + <help><![CDATA[ Pre-fitted sklearn-based taxonomy classifier -############################################ +############################################################### Classify reads by taxon using a fitted classifier. @@ -80,27 +69,33 @@ classifier : TaxonomicClassifier The taxonomic classifier for classifying the reads. reads_per_batch : Int % Range(0, None), optional - Number of reads to process in each batch. If 0, this parameter is + Number of reads to process in each batch. If "auto", this parameter is autoscaled to min( number of query sequences / n_jobs, 20000). +n_jobs : Int, optional + The maximum number of concurrently worker processes. If -1 all CPUs are + used. If 1 is given, no parallel computing code is used at all, which + is useful for debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are + used. Thus for n_jobs = -2, all CPUs but one are used. pre_dispatch : Str, optional "all" or expression, as in "3*n_jobs". The number of batches (of tasks) to be pre-dispatched. -confidence : Float, optional - Confidence threshold for limiting taxonomic depth. Provide -1 to +confidence : Float % Range(0, 1, inclusive_end=True) | Str % Choices('disable'), optional + Confidence threshold for limiting taxonomic depth. Set to "disable" to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments. -read_orientation : Str % Choices('same', 'reverse-complement'), optional +read_orientation : Str % Choices('same', 'reverse-complement', 'auto'), optional Direction of reads with respect to reference sequences. same will cause reads to be classified unchanged; reverse-complement will cause reads - to be reversed and complemented prior to classification. Default is to - autodetect based on the confidence estimates for the first 100 reads. + to be reversed and complemented prior to classification. "auto" will + autodetect orientation based on the confidence estimates for the first + 100 reads. Returns ------- classification : FeatureData[Taxonomy] - ]]></help> -<macros> + ]]></help> + <macros> <import>qiime_citation.xml</import> -</macros> -<expand macro="qiime_citation"/> -</tool> + </macros> + <expand macro="qiime_citation"/> +</tool> \ No newline at end of file