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view qiime2/qiime_longitudinal_plot-feature-volatility.xml @ 29:3ba9833030c1 draft
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author | florianbegusch |
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date | Fri, 04 Sep 2020 13:12:49 +0000 |
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<?xml version="1.0" ?> <tool id="qiime_longitudinal_plot-feature-volatility" name="qiime longitudinal plot-feature-volatility" version="2020.8"> <description>Plot longitudinal feature volatility and importances</description> <requirements> <requirement type="package" version="2020.8">qiime2</requirement> </requirements> <command><![CDATA[ qiime longitudinal plot-feature-volatility --i-table=$itable --i-importances=$iimportances # if $input_files_mmetadatafile: # def list_dict_to_string(list_dict): # set $file_list = list_dict[0]['additional_input'].__getattr__('file_name') # for d in list_dict[1:]: # set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name') # end for # return $file_list # end def --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile) # end if #if '__ob__' in str($pstatecolumn): #set $pstatecolumn_temp = $pstatecolumn.replace('__ob__', '[') #set $pstatecolumn = $pstatecolumn_temp #end if #if '__cb__' in str($pstatecolumn): #set $pstatecolumn_temp = $pstatecolumn.replace('__cb__', ']') #set $pstatecolumn = $pstatecolumn_temp #end if #if 'X' in str($pstatecolumn): #set $pstatecolumn_temp = $pstatecolumn.replace('X', '\\') #set $pstatecolumn = $pstatecolumn_temp #end if #if '__sq__' in str($pstatecolumn): #set $pstatecolumn_temp = $pstatecolumn.replace('__sq__', "'") #set $pstatecolumn = $pstatecolumn_temp #end if #if '__db__' in str($pstatecolumn): #set $pstatecolumn_temp = $pstatecolumn.replace('__db__', '"') #set $pstatecolumn = $pstatecolumn_temp #end if --p-state-column=$pstatecolumn #if '__ob__' in str($pindividualidcolumn): #set $pindividualidcolumn_temp = $pindividualidcolumn.replace('__ob__', '[') #set $pindividualidcolumn = $pindividualidcolumn_temp #end if #if '__cb__' in str($pindividualidcolumn): #set $pindividualidcolumn_temp = $pindividualidcolumn.replace('__cb__', ']') #set $pindividualidcolumn = $pindividualidcolumn_temp #end if #if 'X' in str($pindividualidcolumn): #set $pindividualidcolumn_temp = $pindividualidcolumn.replace('X', '\\') #set $pindividualidcolumn = $pindividualidcolumn_temp #end if #if '__sq__' in str($pindividualidcolumn): #set $pindividualidcolumn_temp = $pindividualidcolumn.replace('__sq__', "'") #set $pindividualidcolumn = $pindividualidcolumn_temp #end if #if '__db__' in str($pindividualidcolumn): #set $pindividualidcolumn_temp = $pindividualidcolumn.replace('__db__', '"') #set $pindividualidcolumn = $pindividualidcolumn_temp #end if #if str($pindividualidcolumn): --p-individual-id-column=$pindividualidcolumn #end if #if '__ob__' in str($pdefaultgroupcolumn): #set $pdefaultgroupcolumn_temp = $pdefaultgroupcolumn.replace('__ob__', '[') #set $pdefaultgroupcolumn = $pdefaultgroupcolumn_temp #end if #if '__cb__' in str($pdefaultgroupcolumn): #set $pdefaultgroupcolumn_temp = $pdefaultgroupcolumn.replace('__cb__', ']') #set $pdefaultgroupcolumn = $pdefaultgroupcolumn_temp #end if #if 'X' in str($pdefaultgroupcolumn): #set $pdefaultgroupcolumn_temp = $pdefaultgroupcolumn.replace('X', '\\') #set $pdefaultgroupcolumn = $pdefaultgroupcolumn_temp #end if #if '__sq__' in str($pdefaultgroupcolumn): #set $pdefaultgroupcolumn_temp = $pdefaultgroupcolumn.replace('__sq__', "'") #set $pdefaultgroupcolumn = $pdefaultgroupcolumn_temp #end if #if '__db__' in str($pdefaultgroupcolumn): #set $pdefaultgroupcolumn_temp = $pdefaultgroupcolumn.replace('__db__', '"') #set $pdefaultgroupcolumn = $pdefaultgroupcolumn_temp #end if #if str($pdefaultgroupcolumn): --p-default-group-column=$pdefaultgroupcolumn #end if #if str($pyscale) != 'None': --p-yscale=$pyscale #end if #if str($pimportancethreshold) != 'None': --p-importance-threshold=$pimportancethreshold #end if #if str($pfeaturecount) != 'None': --p-feature-count=$pfeaturecount #end if #if str($pmissingsamples) != 'None': --p-missing-samples=$pmissingsamples #end if --o-visualization=ovisualization #if str($examples) != 'None': --examples=$examples #end if ; cp odistancematrix.qza $odistancematrix ; qiime tools export ovisualization.qzv --output-path out && mkdir -p '$ovisualization.files_path' && cp -r out/* '$ovisualization.files_path' && mv '$ovisualization.files_path/index.html' '$ovisualization' ; qiime tools export ovisualization.qzv --output-path out && mkdir -p '$ovisualization.files_path' && cp -r out/* '$ovisualization.files_path' && mv '$ovisualization.files_path/index.html' '$ovisualization' ; qiime tools export ovisualization.qzv --output-path out && mkdir -p '$ovisualization.files_path' && cp -r out/* '$ovisualization.files_path' && mv '$ovisualization.files_path/index.html' '$ovisualization' ]]></command> <inputs> <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[RelativeFrequency] Feature table containing features found in importances. [required]" name="itable" optional="False" type="data" /> <param format="qza,no_unzip.zip" label="--i-importances: ARTIFACT FeatureData[Importance] Feature importance scores. [required]" name="iimportances" optional="False" type="data" /> <repeat name="input_files_mmetadatafile" optional="False" title="--m-metadata-file"> <param format="tabular,qza,no_unzip.zip" label="--m-metadata-file: METADATA... (multiple Sample metadata file containing arguments will be individual-id-column. merged) [required]" name="additional_input" optional="False" type="data" /> </repeat> <param label="--p-state-column: TEXT Metadata column containing state (time) variable information. [required]" name="pstatecolumn" optional="False" type="text" /> <param label="--p-individual-id-column: TEXT Metadata column containing IDs for individual subjects. [optional]" name="pindividualidcolumn" optional="False" type="text" /> <param label="--p-default-group-column: TEXT The default metadata column on which to separate groups for comparison (all categorical metadata columns will be available in the visualization). [optional]" name="pdefaultgroupcolumn" optional="False" type="text" /> <param label="--p-yscale: " name="pyscale" optional="True" type="select"> <option selected="True" value="None">Selection is Optional</option> <option value="linear">linear</option> <option value="pow">pow</option> <option value="sqrt">sqrt</option> <option value="log">log</option> </param> <param label="--p-importance-threshold: " name="pimportancethreshold" optional="True" type="select"> <option selected="True" value="None">Selection is Optional</option> <option value="Float % Range(0">Float % Range(0</option> <option value="None">None</option> <option value="inclusive_start=False">inclusive_start=False</option> </param> <param label="--p-feature-count: " name="pfeaturecount" optional="True" type="select"> <option selected="True" value="None">Selection is Optional</option> <option value="Int % Range(1">Int % Range(1</option> <option value="None">None</option> </param> <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select"> <option selected="True" value="None">Selection is Optional</option> <option value="error">error</option> <option value="ignore">ignore</option> </param> <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> </inputs> <outputs> <data format="html" label="${tool.name} on ${on_string}: visualization.html" name="ovisualization" /> </outputs> <help><![CDATA[ Plot longitudinal feature volatility and importances ############################################################### Plots an interactive control chart of feature abundances (y-axis) in each sample across time (or state; x-axis). Feature importance scores and descriptive statistics for each feature are plotted in interactive bar charts below the control chart, facilitating exploration of longitudinal feature data. This visualization is intended for use with the feature- volatility pipeline; use that pipeline to access this visualization. Parameters ---------- table : FeatureTable[RelativeFrequency] Feature table containing features found in importances. importances : FeatureData[Importance] Feature importance scores. metadata : Metadata Sample metadata file containing individual_id_column. state_column : Str Metadata column containing state (time) variable information. individual_id_column : Str, optional Metadata column containing IDs for individual subjects. default_group_column : Str, optional The default metadata column on which to separate groups for comparison (all categorical metadata columns will be available in the visualization). yscale : Str % Choices('linear', 'pow', 'sqrt', 'log'), optional y-axis scaling strategy to apply. importance_threshold : Float % Range(0, None, inclusive_start=False) | Str % Choices('q1', 'q2', 'q3'), optional Filter feature table to exclude any features with an importance score less than this threshold. Set to "q1", "q2", or "q3" to select the first, second, or third quartile of values. Set to "None" to disable this filter. feature_count : Int % Range(1, None) | Str % Choices('all'), optional Filter feature table to include top N most important features. Set to "all" to include all features. missing_samples : Str % Choices('error', 'ignore'), optional How to handle missing samples in metadata. "error" will fail if missing samples are detected. "ignore" will cause the feature table and metadata to be filtered, so that only samples found in both files are retained. Returns ------- visualization : Visualization ]]></help> <macros> <import>qiime_citation.xml</import> </macros> <expand macro="qiime_citation"/> </tool>