from q2_types.ordination import PCoAResults
PARAMETERS = {'metadata': Metadata, 'custom_axes': List[Str]}
PARAMETERS_DESC = {
'metadata':
'The sample metadata.',
'custom_axes': ('Numeric sample metadata columns that should be '
'included as axes in the Emperor plot.')
}
plugin = Plugin(
name='emperor',
version=q2_emperor.__version__,
website='http://emperor.microbio.me',
package='q2_emperor',
citations=Citations.load('citations.bib', package='q2_emperor'),
description=('This QIIME 2 plugin wraps Emperor and '
'supports interactive visualization of ordination '
'plots.'),
short_description='Plugin for ordination plotting with Emperor.')
plugin.visualizers.register_function(
function=plot,
inputs={'pcoa': PCoAResults},
parameters={
'metadata': Metadata,
'custom_axes': List[Str]
},
input_descriptions={
'pcoa': 'The principal coordinates matrix to be plotted.'
},
from q2_sidle import (KmerMap,
KmerMapFormat,
KmerMapDirFmt,
KmerAlignment,
KmerAlignFormat,
KmerAlignDirFmt,
SidleReconstruction,
SidleReconFormat,
SidleReconDirFormat,
ReconstructionSummary,
ReconSummaryFormat,
ReconSummaryDirFormat,
)
import q2_sidle
citations = Citations.load('citations.bib', package='q2_sidle')
plugin = Plugin(
name='sidle',
version='2020.08',
website='https://github.com/jwdebelius/q2-sidle',
package='q2_sidle',
description=('This plugin reconstructs a full 16s sequence from short '
'reads over a marker gene region using the Short MUltiple '
'Read Framework (SMURF) algorithm.'),
short_description='Plugin for kmer-based marker gene reconstruction.',
citations=[citations['Debelius2021']],
)
plugin.methods.register_function(
function=q2_sidle.prepare_extracted_region,
# ----------------------------------------------------------------------------
import importlib
import qiime2.plugin
from qiime2.plugin import Citations
from q2_types.feature_data import FeatureData, Sequence, Taxonomy
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.tree import Phylogeny, Rooted
import q2_fragment_insertion
from q2_fragment_insertion._type import Placements, SeppReferenceDatabase
from q2_fragment_insertion._format import (PlacementsFormat, PlacementsDirFmt,
SeppReferenceDirFmt,
RAxMLinfoFormat)
citations = Citations.load('citations.bib', package='q2_fragment_insertion')
plugin = qiime2.plugin.Plugin(
name='fragment-insertion',
version=q2_fragment_insertion.__version__,
website='https://github.com/qiime2/q2-fragment-insertion',
short_description='Plugin for extending phylogenies.',
package='q2_fragment_insertion',
user_support_text='https://github.com/qiime2/q2-fragment-insertion/issues',
citations=citations,
)
plugin.methods.register_function(
function=q2_fragment_insertion.sepp,
inputs={
'representative_sequences': FeatureData[Sequence],
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
import q2_quality_control
from qiime2.plugin import (Str, Plugin, Choices, Range, Float, Int, Bool,
MetadataColumn, Categorical, Citations)
from q2_types.feature_data import FeatureData, Sequence, Taxonomy
from q2_types.feature_table import FeatureTable, RelativeFrequency
from .quality_control import (exclude_seqs, evaluate_composition,
evaluate_seqs, evaluate_taxonomy)
citations = Citations.load('citations.bib', package='q2_quality_control')
plugin = Plugin(
name='quality-control',
version=q2_quality_control.__version__,
website='https://github.com/qiime2/q2-quality-control',
package='q2_quality_control',
description=(
'This QIIME 2 plugin supports methods for assessing and controlling '
'the quality of feature and sequence data.'),
short_description=(
'Plugin for quality control of feature and sequence data.')
)
seq_inputs = {'query_sequences': FeatureData[Sequence],
AlignedSequence)
from q2_types.tree import Phylogeny, Rooted
from q2_feature_classifier.classifier import (_parameter_descriptions,
_classify_parameters)
from q2_feature_classifier._taxonomic_classifier import TaxonomicClassifier
import rescript
from rescript._utilities import _rank_handles
from rescript.types._format import (
SILVATaxonomyFormat, SILVATaxonomyDirectoryFormat, SILVATaxidMapFormat,
SILVATaxidMapDirectoryFormat, RNAFASTAFormat, RNASequencesDirectoryFormat)
from rescript.types._type import SILVATaxonomy, SILVATaxidMap, RNASequence
from rescript.types.methods import reverse_transcribe
from rescript.ncbi import get_ncbi_data, _default_ranks, _allowed_ranks
citations = Citations.load('citations.bib', package='rescript')
plugin = Plugin(
name='rescript',
version=rescript.__version__,
website="https://github.com/nbokulich/RESCRIPt",
package='rescript',
description=('Reference sequence annotation and curation pipeline.'),
short_description=(
'Pipeline for reference sequence annotation and curation.'),
)
SILVA_LICENSE_NOTE = (
'NOTE: THIS ACTION ACQUIRES DATA FROM THE SILVA DATABASE. SEE '
'https://www.arb-silva.de/silva-license-information/ FOR MORE INFORMATION '
'and be aware that earlier versions may be released under a different '
# ----------------------------------------------------------------------------
# Copyright (c) 2016-2019, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import Plugin, Float, Int, Bool, Range, Citations
from q2_types.feature_data import FeatureData, Sequence, AlignedSequence
import q2_alignment
citations = Citations.load('citations.bib', package='q2_alignment')
plugin = Plugin(
name='alignment',
version=q2_alignment.__version__,
website='https://github.com/qiime2/q2-alignment',
package='q2_alignment',
description=('This QIIME 2 plugin provides support for generating '
'and manipulating sequence alignments.'),
short_description='Plugin for generating and manipulating alignments.'
)
plugin.methods.register_function(
function=q2_alignment.mafft,
inputs={'sequences': FeatureData[Sequence]},
parameters={'n_threads': Int % Range(0, None),
'parttree': Bool},
outputs=[('alignment', FeatureData[AlignedSequence])],
input_descriptions={'sequences': 'The sequences to be aligned.'},
from qiime2.plugin import (Str, Plugin, Metadata, Choices, Bool, Citations,
Int, MetadataColumn, Numeric, Range)
from .mapper import (draw_map, geodesic_distance, euclidean_distance,
draw_interactive_map)
import q2_coordinates
import importlib
from q2_types.sample_data import SampleData
from q2_types.distance_matrix import DistanceMatrix
from q2_types.tree import Phylogeny, Rooted
from ._format import (CoordinatesFormat, CoordinatesDirectoryFormat,
QuadTreeFormat, QuadTreeDirectoryFormat)
from ._type import (Coordinates, QuadTree)
from .stats import autocorr
from .qtrees import quadtree
citations = Citations.load('citations.bib', package='q2_coordinates')
plugin = Plugin(
name='coordinates',
version=q2_coordinates.__version__,
website="https://github.com/nbokulich/q2-coordinates",
package='q2_coordinates',
description=(
'This QIIME 2 plugin supports methods for geospatial analysis and map '
'building.'),
short_description=(
'Plugin for geospatial analysis and cartography.'),
)
base_parameters = {
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
import importlib
from qiime2.plugin import Plugin, List, Str, Float, Bool, Citations, Int
from q2_types.feature_table import FeatureTable, RelativeFrequency, Frequency
from q2_types.feature_data import FeatureData, Taxonomy, Sequence
from q2_feature_classifier._taxonomic_classifier import TaxonomicClassifier
import q2_clawback
citations = Citations.load('citations.bib', package='q2_clawback')
plugin = Plugin(
name='clawback',
version=q2_clawback.__version__,
website='https://github.com/BenKaehler/q2-clawback',
package='q2_clawback',
citations=[citations['bokulich2018optimizing']],
description=('This QIIME 2 plugin provides support for generating '
'generating class weights for use with the '
'feature-classifier'),
short_description='CLAss Weight Assembler plugin.')
plugin.visualizers.register_function(
function=q2_clawback.summarize_Qiita_metadata_category_and_contexts,
inputs={},
parameters={'category': Str},
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import Plugin, Citations, Float, Int, Range
from q2_types.feature_data import FeatureData, Sequence, Taxonomy
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.bowtie2 import Bowtie2Index
from ._shogun import minipipe, nobunaga
import q2_shogun
citations = Citations.load('citations.bib', package='q2_shogun')
plugin = Plugin(
name='shogun',
version=q2_shogun.__version__,
website='https://github.com/qiime2/q2-shogun',
package='q2_shogun',
description=('A QIIME 2 plugin wrapper for the SHOGUN shallow shotgun '
'sequencing taxonomy profiler.'),
short_description='Shallow shotgun sequencing taxonomy profiler.',
citations=[citations['Hillmann320986']])
plugin.methods.register_function(
function=nobunaga,
inputs={
'query': FeatureData[Sequence],
Metadata,
Citations,
Choices,
)
import importlib
import q2_mlab
from q2_mlab.learningtask import ClassificationTask, RegressionTask
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.distance_matrix import DistanceMatrix
from q2_types.sample_data import SampleData
from q2_types.tree import Phylogeny, Rooted
from q2_sample_classifier import PredictionsDirectoryFormat
from q2_mlab._type import Target, Results
from q2_mlab._format import ResultsFormat, ResultsDirectoryFormat
citations = Citations.load("citations.bib", package="q2_mlab")
sklearn_n_jobs_description = (
"The number of jobs to use for the computation. This works by breaking "
"down the pairwise matrix into n_jobs even slices and computing them in "
"parallel. 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. (Description from sklearn.metrics.pairwise_distances)")
plugin = Plugin(
name="mlab",
version=q2_mlab.__version__,
website="https://dev.qiime2.org/",
package="q2_mlab",
citations=Citations.load("citations.bib", package="q2_mlab"),
from q2_aldex2._method import aldex2, extract_differences
from q2_aldex2._visualizer import effect_plot
# TODO: will need to fix the version number
__version__ = '1.14.1'
plugin = Plugin(
name='aldex2',
version=__version__,
website='https://github.com/ggloor/q2-aldex2',
package='q2_aldex2',
description=('Analysis Of Differential Abundance Taking '
'Sample Variation Into Account'),
short_description='Plugin for differential abundance analysis.',
citations=Citations.load('citations.bib', package='q2_aldex2')
)
plugin.methods.register_function(
function=aldex2,
name=('Analysis Of Differential Abundance'),
description=('Performs log-ratio transformation and statistical testing'),
inputs={'table': FeatureTable[Frequency]},
parameters={'metadata': MetadataColumn[Categorical],
'mc_samples': Int,
'test': Str % Choices(['t', 'glm']),
'denom': Str % Choices(['all', 'iqlr'])},
outputs=[('differentials', FeatureData[Differential])],
input_descriptions={
'table': 'The feature table of abundances'
},
from qiime2.plugin import (Plugin, Str, Int, Bool, Float, Citations,
MetadataColumn, Numeric, Categorical)
from q2_types.feature_table import (FeatureTable, Frequency)
from q2_types.tree import Phylogeny, Rooted
import re
import ast
import os
from ._tada import tada, prune_features_from_phylogeny
from q2_types.feature_data import FeatureData, Sequence, Taxonomy
from ._tada._data_preprocess import cluster_features, reorder_feature_table
from ._smote.ML_over_sampling import synthetic_over_sampling
from ._TreeCluster._treeCluster import tree_cluster
from ._smote.ML_under_sampling import synthetic_under_sampling
from ._CountVectors._countVectors import count_vectors
citations = Citations.load('citations.bib', package='q2_feature_engineering')
_version_re = re.compile(r'__version__\s+=\s+(.*)')
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, '__init__.py'), 'rb') as f:
hit = _version_re.search(f.read().decode('utf-8')).group(1)
__version__ = str(ast.literal_eval(hit))
plugin = Plugin(
name='feature-engineering',
version=__version__,
website='https://github.com/tada-alg/TADA',
package='q2_feature_engineering',
short_description=('This is a QIIME 2 plugin for phylogenetic augmentation of microbiome samples to '
'enhance phenotype classification'),
# ----------------------------------------------------------------------------
from qiime2.plugin import (Plugin, Str, Properties, Choices, Int, Bool, Range,
Float, Set, Visualization, Metadata, MetadataColumn,
Categorical, Numeric, Citations)
import q2_diversity
from q2_diversity import _alpha as alpha
from q2_diversity import _beta as beta
from q2_types.feature_table import FeatureTable, Frequency, RelativeFrequency
from q2_types.distance_matrix import DistanceMatrix
from q2_types.sample_data import AlphaDiversity, SampleData
from q2_types.tree import Phylogeny, Rooted
from q2_types.ordination import PCoAResults
citations = Citations.load('citations.bib', package='q2_diversity')
sklearn_n_jobs_description = (
'The number of jobs to use for the computation. This works by breaking '
'down the pairwise matrix into n_jobs even slices and computing them in '
'parallel. 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. (Description from sklearn.metrics.pairwise_distances)'
)
plugin = Plugin(
name='diversity',
version=q2_diversity.__version__,
website='https://github.com/qiime2/q2-diversity',
package='q2_diversity',
'TIM3e+R7', 'TIM3e+R8', 'TIM3e+R9', 'TIM3e+R10', 'TIM3',
'TIM3+I', 'TIM3+G', 'TIM3+I+G', 'TIM3+R2', 'TIM3+R3',
'TIM3+R4', 'TIM3+R5', 'TIM3+R6', 'TIM3+R7', 'TIM3+R8',
'TIM3+R9', 'TIM3+R10', 'TVMe', 'TVMe+I', 'TVMe+G',
'TVMe+I+G', 'TVMe+R2', 'TVMe+R3', 'TVMe+R4', 'TVMe+R5',
'TVMe+R6', 'TVMe+R7', 'TVMe+R8', 'TVMe+R9', 'TVMe+R10',
'TVM', 'TVM+I', 'TVM+G', 'TVM+I+G', 'TVM+R2', 'TVM+R3',
'TVM+R4', 'TVM+R5', 'TVM+R6', 'TVM+R7', 'TVM+R8',
'TVM+R9', 'TVM+R10', 'SYM', 'SYM+I', 'SYM+G', 'SYM+I+G',
'SYM+R2', 'SYM+R3', 'SYM+R4', 'SYM+R5', 'SYM+R6',
'SYM+R7', 'SYM+R8', 'SYM+R9', 'SYM+R10', 'GTR', 'GTR+I',
'GTR+G', 'GTR+I+G', 'GTR+R2', 'GTR+R3', 'GTR+R4',
'GTR+R5', 'GTR+R6', 'GTR+R7', 'GTR+R8', 'GTR+R9',
'GTR+R10', 'MFP', 'TEST']
citations = Citations.load('citations.bib', package='q2_phylogeny')
plugin = Plugin(
name='phylogeny',
version=q2_phylogeny.__version__,
website='https://github.com/qiime2/q2-phylogeny',
package='q2_phylogeny',
description=('This QIIME 2 plugin supports generating and manipulating '
'phylogenetic trees.'),
short_description='Plugin for generating and manipulating phylogenies.'
)
plugin.methods.register_function(
function=q2_phylogeny.midpoint_root,
inputs={'tree': Phylogeny[Unrooted]},
parameters={},
outputs=[('rooted_tree', Phylogeny[Rooted])],
split_table, predict_classification, predict_regression,
confusion_matrix, scatterplot, summarize, metatable,
heatmap)
from .visuals import _custom_palettes
from ._format import (SampleEstimatorDirFmt, BooleanSeriesFormat,
BooleanSeriesDirectoryFormat, ImportanceFormat,
ImportanceDirectoryFormat, PredictionsFormat,
PredictionsDirectoryFormat, ProbabilitiesFormat,
ProbabilitiesDirectoryFormat)
from ._type import (ClassifierPredictions, RegressorPredictions,
SampleEstimator, BooleanSeries, Importance, Classifier,
Regressor, Probabilities)
import q2_sample_classifier
citations = Citations.load('citations.bib', package='q2_sample_classifier')
plugin = Plugin(
name='sample-classifier',
version=q2_sample_classifier.__version__,
website="https://github.com/qiime2/q2-sample-classifier",
package='q2_sample_classifier',
description=(
'This QIIME 2 plugin supports methods for supervised classification '
'and regression of sample metadata, and other supervised machine '
'learning methods.'),
short_description=(
'Plugin for machine learning prediction of sample metadata.'),
citations=[citations['Bokulich306167'], citations['pedregosa2011scikit']])
description = ('Predicts a {0} sample metadata column using a {1}. Splits '
GISAIDDNAFASTAFormat,
VCFLikeMaskFormat,
VCFLikeMaskDirFmt,
AlignmentMask,
)
from genome_sampler.sample_random import sample_random
from genome_sampler.sample_longitudinal import sample_longitudinal
from genome_sampler.sample_neighbors import sample_neighbors
from genome_sampler.sample_diversity import sample_diversity
from genome_sampler.filter import filter_seqs
from genome_sampler.combine import combine_selections
from genome_sampler.summarize import summarize_selections
from genome_sampler.label_seqs import label_seqs, label_unaligned_seqs
from genome_sampler.mask import mask
citations = Citations.load('citations.bib', package='genome_sampler')
plugin = Plugin(name='genome-sampler',
website='https://caporasolab.us/genome-sampler',
package='genome_sampler',
version=genome_sampler.__version__,
description='Tools for sampling from collections of genomes.',
short_description='Genome sampler.',
citations=[citations['genomesampler']])
plugin.register_formats(IDSelectionDirFmt)
plugin.register_formats(GISAIDDNAFASTAFormat)
plugin.register_formats(VCFLikeMaskFormat)
plugin.register_formats(VCFLikeMaskDirFmt)
plugin.register_semantic_types(Selection)
plugin.register_semantic_types(AlignmentMask)
Properties)
from q2_types.ordination import PCoAResults
PARAMETERS = {'metadata': Metadata, 'custom_axes': List[Str]}
PARAMETERS_DESC = {
'metadata': 'The sample metadata.',
'custom_axes': ('Numeric sample metadata columns that should be '
'included as axes in the Emperor plot.')
}
plugin = Plugin(
name='emperor',
version=q2_emperor.__version__,
website='http://emperor.microbio.me',
package='q2_emperor',
citations=Citations.load('citations.bib', package='q2_emperor'),
description=('This QIIME 2 plugin wraps Emperor and '
'supports interactive visualization of ordination '
'plots.'),
short_description='Plugin for ordination plotting with Emperor.'
)
plugin.visualizers.register_function(
function=plot,
inputs={'pcoa': PCoAResults},
parameters={'metadata': Metadata, 'custom_axes': List[Str]},
input_descriptions={
'pcoa': 'The principal coordinates matrix to be plotted.'
},
parameter_descriptions=PARAMETERS_DESC,
name='Visualize and Interact with Principal Coordinates Analysis Plots',
import q2_cutadapt
import q2_cutadapt._demux
import q2_cutadapt._trim
plugin = Plugin(
name='cutadapt',
version=q2_cutadapt.__version__,
website='https://github.com/qiime2/q2-cutadapt',
package='q2_cutadapt',
description='This QIIME 2 plugin uses cutadapt to work with '
'adapters (e.g. barcodes, primers) in sequence data.',
short_description='Plugin for removing adapter sequences, primers, and '
'other unwanted sequence from sequence data.',
citations=Citations.load('citations.bib', package='q2_cutadapt')
)
plugin.methods.register_function(
function=q2_cutadapt._trim.trim_single,
inputs={
'demultiplexed_sequences': SampleData[SequencesWithQuality],
},
parameters={
'cores': Int % Range(1, None),
'adapter': List[Str],
'front': List[Str],
'anywhere': List[Str],
'error_rate': Float % Range(0, 1, inclusive_start=True,
inclusive_end=True),
'indels': Bool,
from qiime2.plugin import (Plugin, Str, Choices, Int, Bool, Range, Float,
Citations)
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.feature_data import FeatureData, Sequence
from q2_types.tree import Phylogeny, Rooted
import q2_picrust2
citations = Citations.load('citations.bib', package='q2_picrust2')
HSP_METHODS = ['mp', 'emp_prob', 'pic', 'scp', 'subtree_average']
PLACEMENT_TOOLS = ['epa-ng', 'sepp']
plugin = Plugin(
name='picrust2',
version="2021.11",
website='https://github.com/gavinmdouglas/q2-picrust2',
package='q2_picrust2',
description=(
'This QIIME 2 plugin wraps the default 16S PICRUSt2 pipeline to run '
'metagenome inference based on marker gene data. Currently '
'only unstratified output is supported.'),
short_description='Predicts gene families and pathways from 16S sequences.',
citations=[citations['Douglas2020NatureBiotech']])
plugin.methods.register_function(
function=q2_picrust2.full_pipeline,
inputs={
'table': FeatureTable[Frequency],
'seq': FeatureData[Sequence]
},
# ----------------------------------------------------------------------------
# Copyright (c) 2016-2019, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import Plugin, Citations
import q2_feature_classifier
citations = Citations.load('citations.bib', package='q2_feature_classifier')
plugin = Plugin(
name='feature-classifier',
version=q2_feature_classifier.__version__,
website='https://github.com/qiime2/q2-feature-classifier',
package='q2_feature_classifier',
description=('This QIIME 2 plugin supports taxonomic '
'classification of features using a variety '
'of methods, including Naive Bayes, vsearch, '
'and BLAST+.'),
short_description='Plugin for taxonomic classification.',
citations=[citations['bokulich2018optimizing']]
)
Range, Citations, TypeMatch
)
from q2_types.sample_data import SampleData
from q2_types.per_sample_sequences import (
SequencesWithQuality, PairedEndSequencesWithQuality,
JoinedSequencesWithQuality)
import q2_demux
from ._type import (RawSequences, EMPSingleEndSequences, EMPPairedEndSequences,
ErrorCorrectionDetails)
from ._format import (EMPMultiplexedDirFmt, ErrorCorrectionDetailsDirFmt,
EMPSingleEndDirFmt, EMPSingleEndCasavaDirFmt,
EMPPairedEndDirFmt, EMPPairedEndCasavaDirFmt)
citations = Citations.load('citations.bib', package='q2_demux')
plugin = Plugin(
name='demux',
version=q2_demux.__version__,
website='https://github.com/qiime2/q2-demux',
package='q2_demux',
description=('This QIIME 2 plugin supports demultiplexing of '
'single-end and paired-end sequence reads and '
'visualization of sequence quality information.'),
short_description='Plugin for demultiplexing & viewing sequence quality.'
)
plugin.register_semantic_types(
RawSequences, EMPSingleEndSequences, EMPPairedEndSequences,
ErrorCorrectionDetails)
# ----------------------------------------------------------------------------
from qiime2.plugin import (Str, Int, Choices, Citations, MetadataColumn,
Categorical, Plugin)
from q2_types.feature_table import FeatureTable, Frequency, Composition
import q2_composition
plugin = Plugin(name='composition',
version=q2_composition.__version__,
website='https://github.com/qiime2/q2-composition',
package='q2_composition',
description=('This QIIME 2 plugin supports methods for '
'compositional data analysis.'),
short_description='Plugin for compositional data analysis.',
citations=Citations.load('citations.bib',
package='q2_composition'))
plugin.methods.register_function(
function=q2_composition.add_pseudocount,
inputs={'table': FeatureTable[Frequency]},
parameters={'pseudocount': Int},
outputs=[('composition_table', FeatureTable[Composition])],
input_descriptions={
'table': 'The feature table to which pseudocounts should be added.'
},
parameter_descriptions={
'pseudocount': 'The value to add to all counts in the feature table.'
},
output_descriptions={'composition_table': 'The resulting feature table.'},
name='Add pseudocount to table',
description="Increment all counts in table by pseudocount.")
# ----------------------------------------------------------------------------
# Copyright (c) 2019, Ben Kaehler.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import (Plugin, Int, Range, Citations, Str)
from q2_types.feature_data import FeatureData, Sequence
import q2_ipcress
citations = Citations.load('citations.bib', package='q2_ipcress')
plugin = Plugin(
name='ipcress',
version=q2_ipcress.__version__,
website='https://github.com/BenKaehler/q2-ipcress',
package='q2_ipcress',
description=('This QIIME 2 plugin provides support for generating '
'synthetic PCR reads from a set of reference sequences.'),
short_description='Wrapper for ipcress, an in-silico PCR program.')
plugin.methods.register_function(
function=q2_ipcress.ipcress,
inputs={'sequence': FeatureData[Sequence]},
parameters={
'primer_a': Str,
'primer_b': Str,
'min_product_len': Int % Range(0, None),
'max_product_len': Int % Range(0, None),
from q2_sample_classifier import (Importance, RegressorPredictions,
SampleEstimator, Regressor)
from q2_sample_classifier.plugin_setup import (
parameters, parameter_descriptions, output_descriptions,
pipeline_parameters, pipeline_parameter_descriptions,
regressor_pipeline_outputs, pipeline_output_descriptions, regressors)
from ._type import FirstDifferences
from ._format import FirstDifferencesFormat, FirstDifferencesDirectoryFormat
from ._longitudinal import (pairwise_differences, pairwise_distances,
linear_mixed_effects, volatility, nmit,
first_differences, first_distances, maturity_index,
feature_volatility, plot_feature_volatility, anova)
import q2_longitudinal
citations = Citations.load('citations.bib', package='q2_longitudinal')
plugin = Plugin(
name='longitudinal',
version=q2_longitudinal.__version__,
website="https://github.com/qiime2/q2-longitudinal",
package='q2_longitudinal',
description=(
'This QIIME 2 plugin supports methods for analysis of time series '
'data, involving either paired sample comparisons or longitudinal '
'study designs.'),
short_description='Plugin for paired sample and time series analyses.',
citations=[citations['bokulich2017q2']])
plugin.register_semantic_types(FirstDifferences)
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
import q2_ili
from ._plot import plot
from ._semantics import STLDirFmt, Model
from qiime2.plugin import Plugin, Metadata, Citations
plugin = Plugin(
name='ili',
version=q2_ili.__version__,
website='https://ili.embl.de/',
citations=Citations.load('citations.bib', package='q2_ili'),
package='q2_ili',
description=('This QIIME 2 plugin wraps `ili and '
'supports interactive visualization of 3D models'),
short_description='Plugin for spatial mapping with `ili')
# type registration
plugin.register_views(STLDirFmt)
plugin.register_semantic_types(Model)
plugin.register_semantic_type_to_format(Model, artifact_format=STLDirFmt)
plugin.visualizers.register_function(
function=plot,
inputs={'model': Model},
parameters={'metadata': Metadata},
input_descriptions={'model': 'The model where the data will be plotted.'},
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.sdk import Artifact, Visualization
from qiime2.metadata import (Metadata, MetadataColumn,
CategoricalMetadataColumn, NumericMetadataColumn)
from qiime2.plugin import Citations
from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
# "Train release" version includes <year>.<month> and excludes patch numbers
# and pre/post-release tags. All versions within a train release are expected
# to be compatible.
__release__ = '.'.join(__version__.split('.')[:2])
__citations__ = tuple(Citations.load('citations.bib', package='qiime2'))
__website__ = 'https://qiime2.org'
__all__ = [
'Artifact', 'Visualization', 'Metadata', 'MetadataColumn',
'CategoricalMetadataColumn', 'NumericMetadataColumn'
]
# Used by `jupyter serverextension enable`
def _jupyter_server_extension_paths():
return [{"module": "qiime2.jupyter"}]
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import (Plugin, Int, Float, Range, Metadata, Str, Bool,
Choices, MetadataColumn, Categorical, List,
Citations, TypeMatch, TypeMap)
import q2_feature_table
from q2_types.feature_table import (FeatureTable, Frequency, RelativeFrequency,
PresenceAbsence, Composition)
from q2_types.feature_data import (FeatureData, Sequence, Taxonomy,
AlignedSequence)
from .examples import (feature_table_merge_example,
feature_table_merge_three_tables_example)
citations = Citations.load('citations.bib', package='q2_feature_table')
plugin = Plugin(
name='feature-table',
version=q2_feature_table.__version__,
website='https://github.com/qiime2/q2-feature-table',
package='q2_feature_table',
short_description=('Plugin for working with sample by feature tables.'),
description=('This is a QIIME 2 plugin supporting operations on sample '
'by feature tables, such as filtering, merging, and '
'transforming tables.'))
plugin.methods.register_function(
function=q2_feature_table.rarefy,
inputs={'table': FeatureTable[Frequency]},
parameters={
'sampling_depth': Int % Range(1, None),
import importlib
from qiime2.plugin import (Str, Plugin, Choices, Float, Range, Bool, Citations,
Int)
from q2_types.feature_table import FeatureTable, Frequency
from q2_SCNIC._type import Network, PairwiseFeatureData, ModuleMembership
from q2_SCNIC._format import GraphModelingLanguageFormat, GraphModelingLanguageDirectoryFormat, PairwiseFeatureDataFormat, \
PairwiseFeatureDataDirectoryFormat, ModuleMembershipTSVFormat, ModuleMembershipTSVDirectoryFormat
from q2_SCNIC._SCNIC_methods import sparcc_filter, calculate_correlations, build_correlation_network_r, \
build_correlation_network_p, make_modules_on_correlations
import q2_SCNIC
citations = Citations.load('citations.bib', package='q2_SCNIC')
plugin = Plugin(
name='SCNIC',
version=q2_SCNIC.__version__,
website="https://github.com/shafferm/q2-SCNIC",
package='q2_SCNIC',
description=('This QIIME 2 plugin allows for use of the SCNIC methods '
'to build correlation networks as well as detect and '
'summarize modules of highy intercorrelated features'),
short_description='Plugin for SCNIC usage.',
citations=[citations['SciPyProceedings_11']])
plugin.register_semantic_types(Network)
plugin.register_semantic_types(PairwiseFeatureData)
plugin.register_semantic_types(ModuleMembership)
# Copyright (c) 2016-2019, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.sdk import Artifact, Visualization
from qiime2.metadata import (Metadata, MetadataColumn,
CategoricalMetadataColumn, NumericMetadataColumn)
from qiime2.plugin import Citations
from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
# "Train release" version includes <year>.<month> and excludes patch numbers
# and pre/post-release tags. All versions within a train release are expected
# to be compatible.
__release__ = '.'.join(__version__.split('.')[:2])
__citations__ = tuple(Citations.load('citations.bib', package='qiime2'))
__website__ = 'https://qiime2.org'
__all__ = ['Artifact', 'Visualization', 'Metadata', 'MetadataColumn',
'CategoricalMetadataColumn', 'NumericMetadataColumn']
# Used by `jupyter serverextension enable`
def _jupyter_server_extension_paths():
return [{"module": "qiime2.jupyter"}]
from qiime2.plugin import Plugin, Metadata, Bool, Citations, Int, Range
from q2_types.tree import Phylogeny, Rooted
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.ordination import PCoAResults
import pkg_resources
__version__ = pkg_resources.get_distribution('empress').version # noqa
plugin = Plugin(
name='empress',
version=__version__,
website='http://github.com/biocore/empress',
package='empress',
citations=Citations.load('citations.bib', package='empress'),
description=('This QIIME 2 plugin wraps Empress and '
'supports interactive visualization of phylogenetic '
'trees.'),
short_description='Plugin for visualizing phylogenies with Empress.')
plugin.visualizers.register_function(
function=plot,
inputs={
'tree': Phylogeny[Rooted],
'feature_table': FeatureTable[Frequency],
'pcoa': PCoAResults,
},
parameters={
'sample_metadata': Metadata,
'feature_metadata': Metadata,
import q2_phylogenomics
import q2_phylogenomics._prinseq
import q2_phylogenomics._filter
import q2_phylogenomics._assemble
import q2_phylogenomics._pipelines
from q2_types.bowtie2 import Bowtie2Index
from q2_types.feature_data import DNASequencesDirectoryFormat
from q2_phylogenomics._format import (GenBankFormat, GenBankDirFmt, BAMFormat,
SAMFormat, BAMFilesDirFmt,
SAMFilesDirFmt, PileUpTSVFormat,
PileUpFilesDirFmt, FASTAFilesDirFmt)
from q2_phylogenomics._types import (AlignmentMap, PileUp, ConsensusSequences,
ReferenceSequence)
citations = Citations.load('citations.bib', package='q2_phylogenomics')
plugin = Plugin(
name='phylogenomics',
version=q2_phylogenomics.__version__,
website='https://github.com/qiime2/q2-phylogenomics',
package='q2_phylogenomics',
description='A QIIME 2 plugin for phylogenomics analyses.',
short_description='A QIIME 2 plugin for phylogenomics analyses.',
)
plugin.register_formats(GenBankFormat, GenBankDirFmt, citations=[])
plugin.register_formats(BAMFormat,
SAMFormat,
BAMFilesDirFmt,
SAMFilesDirFmt,
# Gracefully fail if the user is using an old version of QIIME 2. I expect this
# will pop up a lot as people switch from 2019.4 to 2019.7. (We can remove this
# in the future if desired.)
try:
from q2_types.feature_data import FeatureData, Differential
except ImportError:
raise SystemError(
"It looks like you're using a version of QIIME 2 before 2019.7. "
"Starting with Qurro v0.3.0, Qurro only supports versions of QIIME 2 "
"of at least 2019.7. Please install a later version of QIIME 2 in "
"order to install Qurro v0.3.0. You can also uninstall Qurro in order "
"to fix the current QIIME 2 environment."
)
citations = Citations.load("citations.bib", package="qurro")
plugin = qiime2.plugin.Plugin(
name="qurro",
version=__version__,
website="https://github.com/biocore/qurro",
citations=[citations["fedarko2020"]],
short_description=(
"Plugin for visualizing feature rankings and log-ratios."
),
description=(
"This QIIME 2 plugin supports the interactive visualization of "
"feature rankings (either differentials or feature loadings -- when "
"sorted numerically these provide rankings) in tandem with feature "
"log-ratios across samples."
),
# ----------------------------------------------------------------------------
# Copyright (c) 2016-2018, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import Plugin, Float, Int, Bool, Str, Range, Citations
from q2_types.feature_data import FeatureData, Sequence, AlignedSequence
import q2_alignment
citations = Citations.load('citations.bib', package='q2_alignment')
plugin = Plugin(
name='alignment',
version=q2_alignment.__version__,
website='https://github.com/qiime2/q2-alignment',
package='q2_alignment',
description=('This QIIME 2 plugin provides support for generating '
'and manipulating sequence alignments.'),
short_description='Plugin for generating and manipulating alignments.'
)
plugin.methods.register_function(
function=q2_alignment.mafft,
inputs={'sequences': FeatureData[Sequence]},
parameters={'n_threads': Int % Range(0, None),
'parttree': Bool},
outputs=[('alignment', FeatureData[AlignedSequence])],
from ._prune_hierarchy import prune_hierarchy
from ._classyfire import get_classyfire_taxonomy
from ._semantics import (MassSpectrometryFeatures, MGFDirFmt,
SiriusFolder, SiriusDirFmt,
ZodiacFolder, ZodiacDirFmt,
CSIFolder, CSIDirFmt,
FeatureData, TSVMoleculesFormat, Molecules)
from ._plot import plot
from qiime2.plugin import (Plugin, Str, Range, Choices, Float, Int, Bool, List,
Citations)
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.tree import Phylogeny, Rooted
citations = Citations.load('citations.bib', package='q2_qemistree')
plugin = Plugin(
name='qemistree',
version=q2_qemistree.__version__,
website='https://github.com/biocore/q2-qemistree',
package='q2_qemistree',
description='Hierarchical orderings for mass spectrometry data',
short_description='Plugin for exploring chemical diversity.',
citations=citations,
)
# type registration
plugin.register_views(MGFDirFmt)
plugin.register_semantic_types(MassSpectrometryFeatures)
plugin.register_semantic_type_to_format(MassSpectrometryFeatures,
# ----------------------------------------------------------------------------
from qiime2.plugin import (Plugin, Str, Properties, Choices, Int, Bool, Range,
Float, Set, Visualization, Metadata, MetadataColumn,
Categorical, Numeric, Citations)
import q2_diversity
from q2_diversity import _alpha as alpha
from q2_diversity import _beta as beta
from q2_types.feature_table import FeatureTable, Frequency
from q2_types.distance_matrix import DistanceMatrix
from q2_types.sample_data import AlphaDiversity, SampleData
from q2_types.tree import Phylogeny, Rooted
from q2_types.ordination import PCoAResults
citations = Citations.load('citations.bib', package='q2_diversity')
sklearn_n_jobs_description = (
'The number of jobs to use for the computation. This works by breaking '
'down the pairwise matrix into n_jobs even slices and computing them in '
'parallel. 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. (Description from sklearn.metrics.pairwise_distances)')
plugin = Plugin(
name='diversity',
version=q2_diversity.__version__,
website='https://github.com/qiime2/q2-diversity',
package='q2_diversity',
description=('This QIIME 2 plugin supports metrics for calculating '
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from qiime2.plugin import (Plugin, Int, Float, Range, Metadata, Str, Bool,
Choices, MetadataColumn, Categorical, List,
Citations)
import q2_feature_table
from q2_types.feature_table import (
FeatureTable, Frequency, RelativeFrequency, PresenceAbsence)
from q2_types.feature_data import FeatureData, Sequence, Taxonomy
citations = Citations.load('citations.bib', package='q2_feature_table')
plugin = Plugin(
name='feature-table',
version=q2_feature_table.__version__,
website='https://github.com/qiime2/q2-feature-table',
package='q2_feature_table',
short_description=('Plugin for working with sample by feature tables.'),
description=('This is a QIIME 2 plugin supporting operations on sample '
'by feature tables, such as filtering, merging, and '
'transforming tables.')
)
plugin.methods.register_function(
function=q2_feature_table.rarefy,
inputs={'table': FeatureTable[Frequency]},
parameters={'sampling_depth': Int % Range(1, None)},
