<?xml version="1.0" ?>
<tool id="qiime_quality-control_evaluate-composition" name="qiime quality-control evaluate-composition" version="2019.4">
	<description> - Evaluate expected vs. observed taxonomic composition of samples</description>
	<requirements>
		<requirement type="package" version="2019.4">qiime2</requirement>
	</requirements>
	<command><![CDATA[
qiime quality-control evaluate-composition

--i-expected-features=$iexpectedfeatures
--i-observed-features=$iobservedfeatures


#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 $pdepth:
 --p-depth=$pdepth
#end if

#if str($ppalette) != 'None':
 --p-palette=$ppalette
#end if

#if $pplottar:
 --p-plot-tar
#end if

#if $pplottdr:
 --p-plot-tdr
#end if

#if $pplotrvalue:
 --p-plot-r-value
#end if

#if $pnoplotrsquared:
 --p-no-plot-r-squared
#end if

#if $pplotbraycurtis:
 --p-plot-bray-curtis
#end if

#if $pplotjaccard:
 --p-plot-jaccard
#end if

#if $pplotobservedfeatures:
 --p-plot-observed-features
#end if

#if $pplotobservedfeaturesratio:
 --p-plot-observed-features-ratio
#end if

#if str($mmetadatacolumn):
 --m-metadata-column="$mmetadatacolumn"
#end if

--o-visualization=ovisualization
;
qiime tools export --input-path 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-expected-features: ARTIFACT FeatureTable[RelativeFrequency] Expected feature compositions                [required]" name="iexpectedfeatures" optional="False" type="data"/>
		<param format="qza,no_unzip.zip" label="--i-observed-features: ARTIFACT FeatureTable[RelativeFrequency] Observed feature compositions                [required]" name="iobservedfeatures" optional="False" type="data"/>
		<param label="--p-depth: INTEGER    Maximum depth of semicolon-delimited taxonomic ranks to test (e.g., 1 = root, 7 = species for the greengenes reference sequence database).              [default: 7]" name="pdepth" optional="True" type="integer" value="7"/>
		<param label="--p-palette: " name="ppalette" optional="True" type="select">
			<option selected="True" value="None">Selection is Optional</option>
			<option value="Set1">Set1</option>
			<option value="Set2">Set2</option>
			<option value="Set3">Set3</option>
			<option value="Pastel1">Pastel1</option>
			<option value="Pastel2">Pastel2</option>
			<option value="Paired">Paired</option>
			<option value="Accent">Accent</option>
			<option value="Dark2">Dark2</option>
			<option value="tab10">tab10</option>
			<option value="tab20">tab20</option>
			<option value="tab20b">tab20b</option>
			<option value="tab20c">tab20c</option>
			<option value="viridis">viridis</option>
			<option value="plasma">plasma</option>
			<option value="inferno">inferno</option>
			<option value="magma">magma</option>
			<option value="terrain">terrain</option>
			<option value="rainbow">rainbow</option>
		</param>
		<param label="--p-plot-tar: --p-no-plot-tar Plot taxon accuracy rate (TAR) on score plot. TAR is the number of true positive features divided by the total number of observed features (TAR = true positives " name="pplottar" selected="False" type="boolean"/>
		<param label="--p-plot-tdr: --p-no-plot-tdr Plot taxon detection rate (TDR) on score plot. TDR is the number of true positive features divided by the total number of expected features (TDR = true positives " name="pplottdr" selected="False" type="boolean"/>
		<param label="--p-plot-r-value: --p-no-plot-r-value Plot expected vs. observed linear regression r value on score plot.                         [default: False]" name="pplotrvalue" selected="False" type="boolean"/>
		<param label="--p-no-plot-r-squared: Do not plot expected vs. observed linear regression r-squared value on score plot.                    [default: False]" name="pnoplotrsquared" selected="False" type="boolean"/>
		<param label="--p-plot-bray-curtis: --p-no-plot-bray-curtis Plot expected vs. observed Bray-Curtis dissimilarity scores on score plot.                  [default: False]" name="pplotbraycurtis" selected="False" type="boolean"/>
		<param label="--p-plot-jaccard: --p-no-plot-jaccard Plot expected vs. observed Jaccard distances scores on score plot.                            [default: False]" name="pplotjaccard" selected="False" type="boolean"/>
		<param label="--p-plot-observed-features: --p-no-plot-observed-features Plot observed features count on score plot. [default: False]" name="pplotobservedfeatures" selected="False" type="boolean"/>
		<param label="--p-no-plot-observed-features-ratio: Do not plot ratio of observed:expected features on score plot.                                   [default: False]" name="pnoplotobservedfeaturesratio" selected="False" type="boolean"/>
		<param label="--m-metadata-column: COLUMN  MetadataColumn[Categorical] Optional sample metadata that maps observed-features sample IDs to expected-features sample IDs.  [optional]" name="mmetadatacolumn" optional="True" type="text"/>

		<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>

	</inputs>
	<outputs>
		<data format="html" label="${tool.name} on ${on_string}: visualization.qzv" name="ovisualization"/>
	</outputs>
	<help><![CDATA[
Evaluate expected vs. observed taxonomic composition of samples
###############################################################

This visualizer compares the feature composition of pairs of observed and
expected samples containing the same sample ID in two separate feature
tables. Typically, feature composition will consist of taxonomy
classifications or other semicolon-delimited feature annotations. Taxon
accuracy rate, taxon detection rate, and linear regression scores between
expected and observed observations are calculated at each semicolon-
delimited rank, and plots of per-level accuracy and observation
correlations are plotted. A histogram of distance between false positive
observations and the nearest expected feature is also generated, where
distance equals the number of rank differences between the observed feature
and the nearest common lineage in the expected feature. This visualizer is
most suitable for testing per-run data quality on sequencing runs that
contain mock communities or other samples with known composition. Also
suitable for sanity checks of bioinformatics pipeline performance.

Parameters
----------
expected_features : FeatureTable[RelativeFrequency]
    Expected feature compositions
observed_features : FeatureTable[RelativeFrequency]
    Observed feature compositions
depth : Int, optional
    Maximum depth of semicolon-delimited taxonomic ranks to test (e.g., 1 =
    root, 7 = species for the greengenes reference sequence database).
palette : Str % Choices('Set1', 'Set2', 'Set3', 'Pastel1', 'Pastel2', 'Paired', 'Accent', 'Dark2', 'tab10', 'tab20', 'tab20b', 'tab20c', 'viridis', 'plasma', 'inferno', 'magma', 'terrain', 'rainbow'), optional
    Color palette to utilize for plotting.
plot_tar : Bool, optional
    Plot taxon accuracy rate (TAR) on score plot. TAR is the number of true
    positive features divided by the total number of observed features (TAR
    = true positives / (true positives + false positives)).
plot_tdr : Bool, optional
    Plot taxon detection rate (TDR) on score plot. TDR is the number of
    true positive features divided by the total number of expected features
    (TDR = true positives / (true positives + false negatives)).
plot_r_value : Bool, optional
    Plot expected vs. observed linear regression r value on score plot.
plot_r_squared : Bool, optional
    Plot expected vs. observed linear regression r-squared value on score
    plot.
plot_bray_curtis : Bool, optional
    Plot expected vs. observed Bray-Curtis dissimilarity scores on score
    plot.
plot_jaccard : Bool, optional
    Plot expected vs. observed Jaccard distances scores on score plot.
plot_observed_features : Bool, optional
    Plot observed features count on score plot.
plot_observed_features_ratio : Bool, optional
    Plot ratio of observed:expected features on score plot.
metadata : MetadataColumn[Categorical], optional
    Optional sample metadata that maps observed_features sample IDs to
    expected_features sample IDs.

Returns
-------
visualization : Visualization
	]]></help>
<macros>
    <import>qiime_citation.xml</import>
</macros>
<expand macro="qiime_citation"/>
</tool>