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)},