Mercurial > repos > florianbegusch > qiime2_suite
diff qiime2/qiime_sample-classifier_metatable.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_sample-classifier_metatable.xml Thu Sep 03 09:46:00 2020 +0000 +++ b/qiime2/qiime_sample-classifier_metatable.xml Thu Sep 03 09:51:29 2020 +0000 @@ -1,68 +1,79 @@ <?xml version="1.0" ?> -<tool id="qiime_sample-classifier_metatable" name="qiime sample-classifier metatable" version="2019.7"> - <description> - Convert (and merge) positive numeric metadata (in)to feature table.</description> - <requirements> - <requirement type="package" version="2019.7">qiime2</requirement> - </requirements> - <command><![CDATA[ +<tool id="qiime_sample-classifier_metatable" name="qiime sample-classifier metatable" + version="2020.8"> + <description>Convert (and merge) positive numeric metadata (in)to feature table.</description> + <requirements> + <requirement type="package" version="2020.8">qiime2</requirement> + </requirements> + <command><![CDATA[ qiime sample-classifier metatable - #if str($itable) != 'None': - --i-table=$itable +--i-table=$itable #end if +# 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($input_files_mmetadatafile) +# end if #if str($pmissingsamples) != 'None': - --p-missing-samples=$pmissingsamples +--p-missing-samples=$pmissingsamples #end if #if str($pmissingvalues) != 'None': - --p-missing-values=$pmissingvalues +--p-missing-values=$pmissingvalues +#end if + +#if $pdropallunique: + --p-drop-all-unique #end if +--o-converted-table=oconvertedtable -#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($input_files_mmetadatafile) +#if str($examples) != 'None': +--examples=$examples #end if - ---o-converted-table=oconvertedtable ; cp oconvertedtable.qza $oconvertedtable - ]]></command> - <inputs> - <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [optional]" name="itable" optional="True" type="data"/> - <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="--p-missing-values: " name="pmissingvalues" optional="True" type="select"> - <option selected="True" value="None">Selection is Optional</option> - <option value="drop_samples">drop_samples</option> - <option value="drop_features">drop_features</option> - <option value="error">error</option> - <option value="fill">fill</option> - </param> - <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file"> - <param label="--m-metadata-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [optional]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" /> - </repeat> + ]]></command> + <inputs> + <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [optional]" name="itable" 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 Metadata file to convert to feature table. arguments will be merged) [required]" name="additional_input" optional="False" type="data" /> + </repeat> + <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="--p-missing-values: " name="pmissingvalues" optional="True" type="select"> + <option selected="True" value="None">Selection is Optional</option> + <option value="drop_samples">drop_samples</option> + <option value="drop_features">drop_features</option> + <option value="error">error</option> + <option value="fill">fill</option> + </param> + <param label="--p-drop-all-unique: --p-drop-all-unique: / --p-no-drop-all-unique If True, columns that contain a unique value for every ID will be dropped. [default: False]" name="pdropallunique" selected="False" type="boolean" /> + <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> + + </inputs> - </inputs> - <outputs> - <data format="qza" label="${tool.name} on ${on_string}: convertedtable.qza" name="oconvertedtable"/> - </outputs> - <help><![CDATA[ + <outputs> + <data format="qza" label="${tool.name} on ${on_string}: convertedtable.qza" name="oconvertedtable" /> + + </outputs> + + <help><![CDATA[ Convert (and merge) positive numeric metadata (in)to feature table. -################################################################### +############################################################### Convert numeric sample metadata from TSV file into a feature table. Optionally merge with an existing feature table. Only numeric metadata will @@ -72,11 +83,10 @@ missing_samples="error" to raise an error if samples found in the table are missing from the metadata file. The metadata file can always contain a superset of samples. Note that columns will be dropped if they are non- -numeric, contain only unique values, contain no unique values (zero -variance), contain only empty cells, or contain negative values. This -method currently only converts postive numeric metadata into feature data. -Tip: convert categorical columns to dummy variables to include them in the -output feature table. +numeric, contain no unique values (zero variance), contain only empty +cells, or contain negative values. This method currently only converts +postive numeric metadata into feature data. Tip: convert categorical +columns to dummy variables to include them in the output feature table. Parameters ---------- @@ -94,14 +104,17 @@ How to handle missing values (nans) in metadata. Either "drop_samples" with missing values, "drop_features" with missing values, "fill" missing values with zeros, or "error" if any missing values are found. +drop_all_unique : Bool, optional + If True, columns that contain a unique value for every ID will be + dropped. Returns ------- converted_table : FeatureTable[Frequency] Converted feature table - ]]></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