# ---------------------------------------------------------------------------- # Copyright (c) 2016-2023, 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, Int, Range, Str, Choices, Bool, Float, List, TypeMatch, Metadata) from q2_types.tree import Phylogeny, Unrooted, Rooted from q2_types.feature_data import FeatureData, AlignedSequence, Sequence from q2_types.feature_table import (FeatureTable, Frequency, RelativeFrequency, PresenceAbsence, Composition) from q2_types.distance_matrix import DistanceMatrix import q2_phylogeny import q2_phylogeny._examples as ex _RAXML_MODEL_OPT = ['GTRGAMMA', 'GTRGAMMAI', 'GTRCAT', 'GTRCATI'] _RAXML_VERSION_OPT = ['Standard', 'SSE3', 'AVX2'] _IQTREE_DNA_MODELS = ['JC', 'JC+I', 'JC+G', 'JC+I+G', 'JC+R2', 'JC+R3', 'JC+R4', 'JC+R5', 'JC+R6', 'JC+R7', 'JC+R8', 'JC+R9', 'JC+R10', 'F81', 'F81+I', 'F81+G', 'F81+I+G', 'F81+R2', 'F81+R3', 'F81+R4', 'F81+R5', 'F81+R6', 'F81+R7', 'F81+R8', 'F81+R9', 'F81+R10', 'K80', 'K80+I', 'K80+G', 'K80+I+G', 'K80+R2', 'K80+R3', 'K80+R4', 'K80+R5', 'K80+R6', 'K80+R7', 'K80+R8', 'K80+R9', 'K80+R10', 'HKY', 'HKY+I', 'HKY+G', 'HKY+I+G', 'HKY+R2', 'HKY+R3', 'HKY+R4', 'HKY+R5', 'HKY+R6', 'HKY+R7', 'HKY+R8', 'HKY+R9', 'HKY+R10', 'TNe', 'TNe+I', 'TNe+G', 'TNe+I+G', 'TNe+R2', 'TNe+R3', 'TNe+R4', 'TNe+R5', 'TNe+R6', 'TNe+R7', 'TNe+R8', 'TNe+R9', 'TNe+R10', 'TN', 'TN+I', 'TN+G', 'TN+I+G', 'TN+R2', 'TN+R3', 'TN+R4', 'TN+R5', 'TN+R6', 'TN+R7', 'TN+R8', 'TN+R9', 'TN+R10', 'K81', 'K81+I', 'K81+G', 'K81+I+G', 'K81+R2', 'K81+R3', 'K81+R4', 'K81+R5', 'K81+R6', 'K81+R7', 'K81+R8', 'K81+R9', 'K81+R10', 'K81u', 'K81u+I', 'K81u+G', 'K81u+I+G', 'K81u+R2', 'K81u+R3', 'K81u+R4', 'K81u+R5', 'K81u+R6', 'K81u+R7', 'K81u+R8', 'K81u+R9', 'K81u+R10', 'TPM2', 'TPM2+I', 'TPM2+G', 'TPM2+I+G', 'TPM2+R2', 'TPM2+R3', 'TPM2+R4', 'TPM2+R5', 'TPM2+R6', 'TPM2+R7', 'TPM2+R8', 'TPM2+R9', 'TPM2+R10', 'TPM2u', 'TPM2u+I', 'TPM2u+G', 'TPM2u+I+G', 'TPM2u+R2', 'TPM2u+R3', 'TPM2u+R4', 'TPM2u+R5', 'TPM2u+R6', 'TPM2u+R7', 'TPM2u+R8', 'TPM2u+R9', 'TPM2u+R10', 'TPM3', 'TPM3+I', 'TPM3+G', 'TPM3+I+G', 'TPM3+R2', 'TPM3+R3', 'TPM3+R4', 'TPM3+R5', 'TPM3+R6', 'TPM3+R7', 'TPM3+R8', 'TPM3+R9', 'TPM3+R10', 'TPM3u', 'TPM3u+I', 'TPM3u+G', 'TPM3u+I+G', 'TPM3u+R2', 'TPM3u+R3', 'TPM3u+R4', 'TPM3u+R5', 'TPM3u+R6', 'TPM3u+R7', 'TPM3u+R8', 'TPM3u+R9', 'TPM3u+R10', 'TIMe', 'TIMe+I', 'TIMe+G', 'TIMe+I+G', 'TIMe+R2', 'TIMe+R3', 'TIMe+R4', 'TIMe+R5', 'TIMe+R6', 'TIMe+R7', 'TIMe+R8', 'TIMe+R9', 'TIMe+R10', 'TIM', 'TIM+I', 'TIM+G', 'TIM+I+G', 'TIM+R2', 'TIM+R3', 'TIM+R4', 'TIM+R5', 'TIM+R6', 'TIM+R7', 'TIM+R8', 'TIM+R9', 'TIM+R10', 'TIM2e', 'TIM2e+I', 'TIM2e+G', 'TIM2e+I+G', 'TIM2e+R2', 'TIM2e+R3', 'TIM2e+R4', 'TIM2e+R5', 'TIM2e+R6', 'TIM2e+R7', 'TIM2e+R8', 'TIM2e+R9', 'TIM2e+R10', 'TIM2', 'TIM2+I', 'TIM2+G', 'TIM2+I+G', 'TIM2+R2', 'TIM2+R3', 'TIM2+R4', 'TIM2+R5', 'TIM2+R6', 'TIM2+R7', 'TIM2+R8', 'TIM2+R9', 'TIM2+R10', 'TIM3e', 'TIM3e+I', 'TIM3e+G', 'TIM3e+I+G', 'TIM3e+R2', 'TIM3e+R3', 'TIM3e+R4', 'TIM3e+R5', 'TIM3e+R6', '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])], input_descriptions={'tree': 'The phylogenetic tree to be rooted.'}, parameter_descriptions={}, output_descriptions={'rooted_tree': 'The rooted phylogenetic tree.'}, name='Midpoint root an unrooted phylogenetic tree.', description=("Midpoint root an unrooted phylogenetic tree.") ) plugin.methods.register_function( function=q2_phylogeny.fasttree, inputs={'alignment': FeatureData[AlignedSequence]}, parameters={'n_threads': Int % Range(1, None) | Str % Choices(['auto'])}, outputs=[('tree', Phylogeny[Unrooted])], input_descriptions={ 'alignment': ('Aligned sequences to be used for phylogenetic ' 'reconstruction.') }, parameter_descriptions={ 'n_threads': 'The number of threads. Using more than one thread ' 'runs the non-deterministic variant of `FastTree` ' '(`FastTreeMP`), and may result in a different tree than ' 'single-threading. See ' 'http://www.microbesonline.org/fasttree/#OpenMP for ' 'details. (Use `auto` to automatically use all available ' 'cores)' }, output_descriptions={'tree': 'The resulting phylogenetic tree.'}, name='Construct a phylogenetic tree with FastTree.', description=("Construct a phylogenetic tree with FastTree."), citations=[citations['price2010fasttree']] ) plugin.methods.register_function( function=q2_phylogeny.raxml, inputs={ 'alignment': FeatureData[AlignedSequence]}, parameters={ 'seed': Int, 'n_searches': Int % Range(1, None), 'n_threads': Int % Range(1, None), 'substitution_model': Str % Choices(_RAXML_MODEL_OPT), 'raxml_version': Str % Choices(_RAXML_VERSION_OPT)}, outputs=[('tree', Phylogeny[Unrooted])], input_descriptions={ 'alignment': ('Aligned sequences to be used for phylogenetic ' 'reconstruction.'), }, parameter_descriptions={ 'n_searches': ('The number of independent maximum likelihood ' 'searches to perform. The single best scoring ' 'tree is returned.'), 'n_threads': ('The number of threads to use for multithreaded ' 'processing. Using more than one thread ' 'will enable the PTHREADS version of RAxML.'), 'raxml_version': ('Select a specific CPU optimization of RAxML to ' 'use. The SSE3 versions will run approximately 40% ' 'faster than the standard version. The AVX2 ' 'version will run 10-30% faster than the ' 'SSE3 version.'), 'substitution_model': ('Model of Nucleotide Substitution.'), 'seed': ('Random number seed for the parsimony starting tree. ' 'This allows you to reproduce tree results. ' 'If not supplied then one will be randomly chosen.')}, output_descriptions={'tree': 'The resulting phylogenetic tree.'}, name='Construct a phylogenetic tree with RAxML.', description=('Construct a phylogenetic tree with RAxML. See: ' 'https://sco.h-its.org/exelixis/web/software/raxml/'), citations=[citations['Stamatakis2014raxml']] ) plugin.methods.register_function( function=q2_phylogeny.raxml_rapid_bootstrap, inputs={ 'alignment': FeatureData[AlignedSequence]}, parameters={ 'seed': Int, 'rapid_bootstrap_seed': Int, 'bootstrap_replicates': Int % Range(10, None), 'n_threads': Int % Range(1, None), 'substitution_model': Str % Choices(_RAXML_MODEL_OPT), 'raxml_version': Str % Choices(_RAXML_VERSION_OPT)}, outputs=[('tree', Phylogeny[Unrooted])], input_descriptions={ 'alignment': ('Aligned sequences to be used for phylogenetic ' 'reconstruction.'), }, parameter_descriptions={ 'n_threads': ('The number of threads to use for multithreaded ' 'processing. Using more than one thread ' 'will enable the PTHREADS version of RAxML.'), 'raxml_version': ('Select a specific CPU optimization of RAxML to ' 'use. The SSE3 versions will run approximately 40% ' 'faster than the standard version. The AVX2 ' 'version will run 10-30% faster than the ' 'SSE3 version.'), 'substitution_model': ('Model of Nucleotide Substitution'), 'seed': ('Random number seed for the parsimony starting tree. ' 'This allows you to reproduce tree results. ' 'If not supplied then one will be randomly chosen.'), 'rapid_bootstrap_seed': ('Specify a random seed for rapid ' 'bootstrapping. This allows you to reproduce ' 'rapid bootstrap results. If not supplied ' 'then one will be randomly chosen.'), 'bootstrap_replicates': ('The number of bootstrap searches to ' 'perform.')}, output_descriptions={'tree': 'The resulting phylogenetic tree.'}, name='Construct a phylogenetic tree with bootstrap supports using RAxML.', description=('Construct a phylogenetic tree with RAxML with the addition ' 'of rapid bootstrapping support values. See: ' 'https://sco.h-its.org/exelixis/web/software/raxml/'), citations=[citations['Stamatakis2014raxml'], citations['Stamatakis2008raxml']] ) plugin.methods.register_function( function=q2_phylogeny.iqtree, inputs={'alignment': FeatureData[AlignedSequence]}, parameters={ 'seed': Int, 'n_cores': Int % Range(1, None) | Str % Choices(['auto']), 'n_cores_max': Int % Range(2, None), 'n_runs': Int % Range(1, None), 'substitution_model': Str % Choices(_IQTREE_DNA_MODELS), 'n_init_pars_trees': Int % Range(1, None), 'n_top_init_trees': Int % Range(1, None), 'n_best_retain_trees': Int % Range(1, None), 'n_iter': Int % Range(1, None), 'stop_iter': Int % Range(1, None), 'perturb_nni_strength': Float % Range(0.01, 1.0), 'spr_radius': Int % Range(1, None), 'fast': Bool, 'alrt': Int % Range(1000, None), 'abayes': Bool, 'lbp': Int % Range(1000, None), 'allnni': Bool, 'safe': Bool}, outputs=[('tree', Phylogeny[Unrooted])], input_descriptions={ 'alignment': ('Aligned sequences to be used for phylogenetic ' 'reconstruction.'), }, parameter_descriptions={ 'n_cores': ('The number of cores to use for parallel ' 'processing. Use `auto` to let IQ-TREE automatically ' 'determine the optimal number of cores to use.'), 'n_cores_max': ('Limits the maximum number of cores to be used ' 'when \'n_cores\' is set to \'auto\'.'), 'n_runs': ('Number of indepedent runs. Multiple independent runs ' '(e.g. 10) can outperform a single run in terms of ' 'likelihood maximisation.'), 'substitution_model': ('Model of Nucleotide Substitution. ' 'If not provided, IQ-TREE will determine the ' 'best fit substitution model automatically.'), 'seed': ('Random number seed. If not set, program defaults will be ' 'used. See IQ-TREE manual for details.'), 'n_init_pars_trees': ('Number of initial parsimony trees. If not ' 'set, program defaults will be used. See ' 'IQ-TREE manual for details.'), 'n_top_init_trees': ('Number of top initial trees. If not set, ' 'program defaults will be used. See IQ-TREE ' 'manual for details.'), 'n_best_retain_trees': ('Number of best trees retained during ' 'search. If not set, program defaults will ' 'be used. See IQ-TREE manual for details.'), 'n_iter': ('Fix number of iterations to stop. If not set, program ' 'defaults will be used. See IQ-TREE manual for details.'), 'stop_iter': ('Number of unsuccessful iterations to stop. If not ' 'set, program defaults will be used. See IQ-TREE ' 'manual for details.'), 'perturb_nni_strength': ('Perturbation strength for randomized NNI. ' 'If not set, program defaults will be used. ' 'See IQ-TREE manual for details.'), 'spr_radius': ('Radius for parsimony SPR search. If not set, ' 'program defaults will be used. See IQ-TREE manual ' 'for details.'), 'fast': ('Fast search to resemble FastTree.'), 'allnni': ('Perform more thorough NNI search.'), 'alrt': ('Single branch test method. Number of bootstrap replicates ' 'to perform an SH-like approximate likelihood ratio test ' '(SH-aLRT). Minimum of 1000 replicates is required. Can ' 'be used with other \'single branch test methods\'. Values ' 'reported in the order of: alrt, lbp, abayes.'), 'abayes': ('Single branch test method. Approximate Bayes test. ' 'Can be used with other \'single branch test methods\'. ' 'Values reported in the order of: alrt, lbp, abayes.'), 'lbp': ('Single branch test method. Number of bootstrap replicates ' 'to perform a fast local bootstrap probability method. ' 'Minimum of 1000 replicates is required. Can be used with ' 'other \'single branch test methods\'. Values reported in ' 'the order of: alrt, lbp, abayes.'), 'safe': ('Safe likelihood kernel to avoid numerical underflow.')}, output_descriptions={'tree': 'The resulting phylogenetic tree.'}, name='Construct a phylogenetic tree with IQ-TREE.', description=('Construct a phylogenetic tree using IQ-TREE ' '(http://www.iqtree.org/) with automatic model selection.'), citations=[citations['Minh2020iqtree'], citations['Kalyaanamoorthy2017modelfinder']], ) plugin.methods.register_function( function=q2_phylogeny.iqtree_ultrafast_bootstrap, inputs={'alignment': FeatureData[AlignedSequence]}, parameters={ 'seed': Int, 'n_cores': Int % Range(1, None) | Str % Choices(['auto']), 'n_cores_max': Int % Range(2, None), 'n_runs': Int % Range(1, None), 'substitution_model': Str % Choices(_IQTREE_DNA_MODELS), 'n_init_pars_trees': Int % Range(1, None), 'n_top_init_trees': Int % Range(1, None), 'n_best_retain_trees': Int % Range(1, None), 'stop_iter': Int % Range(1, None), 'perturb_nni_strength': Float % Range(0.01, 1.0), 'spr_radius': Int % Range(1, None), 'bootstrap_replicates': Int % Range(1000, None), 'n_max_ufboot_iter': Int % Range(1, None), 'n_ufboot_steps': Int % Range(1, None), 'min_cor_ufboot': Float % Range(0.51, 0.99), 'ep_break_ufboot': Float % Range(0.01, 0.99), 'alrt': Int % Range(1000, None), 'abayes': Bool, 'lbp': Int % Range(1000, None), 'bnni': Bool, 'allnni': Bool, 'safe': Bool}, outputs=[('tree', Phylogeny[Unrooted])], input_descriptions={ 'alignment': ('Aligned sequences to be used for phylogenetic ' 'reconstruction.'), }, parameter_descriptions={ 'n_cores': ('The number of cores to use for parallel ' 'processing. Use `auto` to let IQ-TREE automatically ' 'determine the optimal number of cores to use.'), 'n_cores_max': ('Limits the maximum number of cores to be used ' 'when \'n_cores\' is set to \'auto\'.'), 'n_runs': ('Number of indepedent runs. Multiple independent runs ' '(e.g. 10) can outperform a single run in terms of ' 'likelihood maximisation.'), 'substitution_model': ('Model of Nucleotide Substitution.' 'If not provided, IQ-TREE will determine the ' 'best fit substitution model automatically. '), 'seed': ('Random number seed. If not set, program defaults will be ' 'used. See IQ-TREE manual for details.'), 'bootstrap_replicates': ('The number of bootstrap searches to ' 'perform. Minimum of 1000 recomended. '), 'n_init_pars_trees': ('Number of initial parsimony trees. If not ' 'set, program defaults will be used. See ' 'IQ-TREE manual for details.'), 'n_top_init_trees': ('Number of top initial trees. If not set, ' 'program defaults will be used. See IQ-TREE ' 'manual for details.'), 'n_best_retain_trees': ('Number of best trees retained during ' 'search. If not set, program defaults will ' 'be used. See IQ-TREE manual for details.'), 'stop_iter': ('Number of unsuccessful iterations to stop. If not ' 'set, program defaults will be used. See IQ-TREE ' 'manual for details.'), 'perturb_nni_strength': ('Perturbation strength for randomized NNI. ' 'If not set, program defaults will be used. ' 'See IQ-TREE manual for details.'), 'spr_radius': ('Radius for parsimony SPR search. If not set, ' 'program defaults will be used. See IQ-TREE manual ' 'for details.'), 'n_max_ufboot_iter': ('Maximum number of iterations. If not set, ' 'program defaults will be used. See IQ-TREE ' 'manual for details.'), 'n_ufboot_steps': ('Number of iterations for UFBoot stopping rule. ' 'If not set, program defaults will be used.' 'See IQ-TREE manual for details.'), 'min_cor_ufboot': ('Minimum correlation coefficient. ' 'If not set, program defaults will be used.' 'See IQ-TREE manual for details.'), 'ep_break_ufboot': ('Epsilon value to break tie. If not set, program ' 'defaults will be used. See IQ-TREE manual for ' 'details.'), 'bnni': ('Optimize UFBoot trees by NNI on bootstrap alignment. ' 'This option reduces the risk of overestimating branch ' 'supports with UFBoot due to severe model violations.'), 'allnni': ('Perform more thorough NNI search.'), 'alrt': ('Single branch test method. Number of bootstrap replicates ' 'to perform an SH-like approximate likelihood ratio test ' '(SH-aLRT). Minimum of 1000 replicates is required. Can ' 'be used with other \'single branch test methods\'. Values ' 'reported in the order of: alrt, lbp, abayes.'), 'abayes': ('Single branch test method. Performs an ' 'approximate Bayes test. Can be used with other ' '\'single branch test methods\' and ultrafast bootstrap. ' 'Values reported in the order of: alrt, lbp, abayes, ' 'ufboot.'), 'lbp': ('Single branch test method. Number of bootstrap replicates ' 'to perform a fast local bootstrap probability method. ' 'Minimum of 1000 replicates is required. Can be used with ' 'other \'single branch test methods\'. Values reported in ' 'the order of: alrt, lbp, abayes, ufboot.'), 'safe': ('Safe likelihood kernel to avoid numerical underflow.')}, output_descriptions={'tree': 'The resulting phylogenetic tree.'}, name=('Construct a phylogenetic tree with IQ-TREE with bootstrap ' 'supports.'), description=('Construct a phylogenetic tree using IQ-TREE ' '(http://www.iqtree.org/) with automatic ' 'model selection and bootstrap supports.'), citations=[citations['Minh2020iqtree'], citations['Kalyaanamoorthy2017modelfinder'], citations['Minh2013ultrafastbootstrap'], citations['Hoang2017ultrafastbootstrap2']], ) T1 = TypeMatch([Frequency, RelativeFrequency, PresenceAbsence]) plugin.methods.register_function( function=q2_phylogeny.filter_table, inputs={'table': FeatureTable[T1], 'tree': Phylogeny[Rooted | Unrooted]}, parameters={}, outputs=[('filtered_table', FeatureTable[T1])], input_descriptions={ 'table': 'Feature table that features should be filtered from.', 'tree': ('Tree where tip identifiers are the feature identifiers that ' 'should be retained in the table.') }, parameter_descriptions={}, output_descriptions={'filtered_table': 'The resulting feature table.'}, name="Remove features from table if they're not present in tree.", description=("Remove features from a feature table if their identifiers " "are not tip identifiers in tree.") ) T2 = TypeMatch([Rooted, Unrooted]) T3 = (Frequency | RelativeFrequency | PresenceAbsence | Composition) plugin.methods.register_function( function=q2_phylogeny.filter_tree, inputs={'tree': Phylogeny[T2], 'table': FeatureTable[T3], }, parameters={'metadata': Metadata, 'where': Str }, outputs=[('filtered_tree', Phylogeny[T2])], input_descriptions={ 'tree': ('Tree that should be filtered'), 'table': ('Feature table which contains the identifier that should be' ' retained in the tree'), }, parameter_descriptions={ 'metadata': ("Feature metadata to use with the 'where' statement or " "to select tips to be retained. Metadata objects could " "also include FeatureData[Sequence] data types, if, for" "instance, you want to filter to match represenative " "sequencces."), 'where': ('SQLite WHERE clause specifying sample metadata criteria ' 'that must be met to be included in the filtered feature ' 'table. If not provided, all samples in `metadata` that' ' are also in the feature table will be retained.'), }, output_descriptions={'filtered_tree': 'The resulting phylogenetic tree.'}, name="Remove features from tree based on metadata", description=("Remove tips from a tree if their identifiers based on a " "set of provided identifiers.") ) plugin.methods.register_function( function=q2_phylogeny.robinson_foulds, inputs={'trees': List[Phylogeny[Rooted | Unrooted]]}, parameters={ 'labels': List[Str], 'missing_tips': Str % Choices('error', 'intersect-all') }, outputs=[('distance_matrix', DistanceMatrix)], input_descriptions={ 'trees': 'Phylogenetic trees to compare with Robinson-Foulds. Rooting' ' information and branch lengths are ignored by this metric.' }, parameter_descriptions={ 'labels': 'Labels to use for the tree names in the distance matrix.' ' If ommited, labels will be "tree_n" where "n" ranges from' ' 1..N. The number of labels must match the number of' ' trees.', 'missing_tips': 'How to handle tips that are not shared between trees.' ' "error" will raise an error if the set of tips is' ' not identical between all input trees.' ' "intersect-all" will remove tips that are not shared' ' between all trees before computing distances beteen' ' trees.' }, output_descriptions={ 'distance_matrix': 'The distances between trees as a symmetric matrix.' }, name="Calculate Robinson-Foulds distance between phylogenetic trees.", description="Calculate the Robinson-Foulds symmetric difference metric" " between two or more phylogenetic trees.", citations=[citations['robinson1981comparison']] ) plugin.pipelines.register_function( function=q2_phylogeny.align_to_tree_mafft_fasttree, inputs={ 'sequences': FeatureData[Sequence], }, parameters={ 'n_threads': Int % Range(1, None) | Str % Choices(['auto']), 'mask_max_gap_frequency': Float % Range(0, 1, inclusive_end=True), 'mask_min_conservation': Float % Range(0, 1, inclusive_end=True), 'parttree': Bool, }, outputs=[ ('alignment', FeatureData[AlignedSequence]), ('masked_alignment', FeatureData[AlignedSequence]), ('tree', Phylogeny[Unrooted]), ('rooted_tree', Phylogeny[Rooted]), ], input_descriptions={ 'sequences': 'The sequences to be used for creating a ' 'fasttree based rooted phylogenetic tree.' }, parameter_descriptions={ 'n_threads': 'The number of threads. (Use `auto` to automatically use ' 'all available cores) ' 'This value is used when aligning the sequences and ' 'creating the tree with fasttree.', 'mask_max_gap_frequency': 'The maximum relative frequency of gap ' 'characters in a column for the column ' 'to be retained. This relative frequency ' 'must be a number between 0.0 and 1.0 ' '(inclusive), where 0.0 retains only those ' 'columns without gap characters, and 1.0 ' 'retains all columns regardless of gap ' 'character frequency. This value is used ' 'when masking the aligned sequences.', 'mask_min_conservation': 'The minimum relative frequency ' 'of at least one non-gap character in a ' 'column for that column to be retained. ' 'This relative frequency must be a number ' 'between 0.0 and 1.0 (inclusive). For ' 'example, if a value of 0.4 is provided, a ' 'column will only be retained if it ' 'contains at least one character that is ' 'present in at least 40% of the sequences. ' 'This value is used when masking the ' 'aligned sequences.', 'parttree': 'This flag is required if the number of sequences being ' 'aligned are larger than 1000000. Disabled by default.', }, output_descriptions={ 'alignment': 'The aligned sequences.', 'masked_alignment': 'The masked alignment.', 'tree': 'The unrooted phylogenetic tree.', 'rooted_tree': 'The rooted phylogenetic tree.', }, name='Build a phylogenetic tree using fasttree and mafft alignment', description=('This pipeline will start by creating a sequence alignment ' 'using MAFFT, after which any alignment columns that are ' 'phylogenetically uninformative or ambiguously aligned will ' 'be removed (masked). The resulting masked alignment will be ' 'used to infer a phylogenetic tree and then subsequently ' 'rooted at its midpoint. Output files from each step of the ' 'pipeline will be saved. This includes both the unmasked and ' 'masked MAFFT alignment from q2-alignment methods, and both ' 'the rooted and unrooted phylogenies from q2-phylogeny ' 'methods.' ), examples={ 'align_to_tree_mafft_fasttree': ex.phylogeny_align_to_tree_mafft_fasttree, } ) plugin.pipelines.register_function( function=q2_phylogeny.align_to_tree_mafft_iqtree, inputs={ 'sequences': FeatureData[Sequence], }, parameters={ 'n_threads': Int % Range(1, None) | Str % Choices(['auto']), 'mask_max_gap_frequency': Float % Range(0, 1, inclusive_end=True), 'mask_min_conservation': Float % Range(0, 1, inclusive_end=True), 'seed': Int, 'substitution_model': Str % Choices(_IQTREE_DNA_MODELS), 'stop_iter': Int % Range(1, None), 'perturb_nni_strength': Float % Range(0.01, 1.0), 'fast': Bool, 'alrt': Int % Range(1000, None), }, outputs=[ ('alignment', FeatureData[AlignedSequence]), ('masked_alignment', FeatureData[AlignedSequence]), ('tree', Phylogeny[Unrooted]), ('rooted_tree', Phylogeny[Rooted]), ], input_descriptions={ 'sequences': 'The sequences to be used for creating a ' 'iqtree based rooted phylogenetic tree.' }, parameter_descriptions={ 'n_threads': 'The number of threads. (Use 0 to automatically use all ' 'available cores ' 'This value is used when aligning the sequences and ' 'creating the tree with iqtree.', 'mask_max_gap_frequency': 'The maximum relative frequency of gap ' 'characters in a column for the column ' 'to be retained. This relative frequency ' 'must be a number between 0.0 and 1.0 ' '(inclusive), where 0.0 retains only those ' 'columns without gap characters, and 1.0 ' 'retains all columns regardless of gap ' 'character frequency. This value is used ' 'when masking the aligned sequences.', 'mask_min_conservation': 'The minimum relative frequency ' 'of at least one non-gap character in a ' 'column for that column to be retained. ' 'This relative frequency must be a number ' 'between 0.0 and 1.0 (inclusive). For ' 'example, if a value of 0.4 is provided, a ' 'column will only be retained if it ' 'contains at least one character that is ' 'present in at least 40% of the sequences. ' 'This value is used when masking the ' 'aligned sequences.', 'seed': 'Random number seed for the iqtree parsimony starting tree. ' 'This allows you to reproduce tree results. ' 'If not supplied then one will be randomly chosen.', 'substitution_model': 'Model of Nucleotide Substitution. ' 'If not provided, IQ-TREE will determine the ' 'best fit substitution model automatically.', 'stop_iter': 'Number of unsuccessful iterations to stop. If not ' 'set, program defaults will be used. See IQ-TREE ' 'manual for details.', 'perturb_nni_strength': 'Perturbation strength for randomized NNI. ' 'If not set, program defaults will be used. ' 'See IQ-TREE manual for details.', 'fast': 'Fast search to resemble FastTree.', 'alrt': 'Single branch test method. Number of bootstrap replicates ' 'to perform an SH-like approximate likelihood ratio test ' '(SH-aLRT). Minimum of 1000 replicates is required.' }, output_descriptions={ 'alignment': 'The aligned sequences.', 'masked_alignment': 'The masked alignment.', 'tree': 'The unrooted phylogenetic tree.', 'rooted_tree': 'The rooted phylogenetic tree.', }, name='Build a phylogenetic tree using iqtree and mafft alignment.', description=('This pipeline will start by creating a sequence alignment ' 'using MAFFT, after which any alignment columns that are ' 'phylogenetically uninformative or ambiguously aligned will ' 'be removed (masked). The resulting masked alignment will be ' 'used to infer a phylogenetic tree using IQ-TREE. By default ' 'the best fit substitution model will be determined by ' 'ModelFinder prior to phylogenetic inference. The resulting ' 'tree will be subsequently rooted at its midpoint. Output ' 'files from each step of the pipeline will be saved. This ' 'includes both the unmasked and masked MAFFT alignment from ' 'q2-alignment methods, and both the rooted and unrooted ' 'phylogenies from q2-phylogeny methods.' ), ) plugin.pipelines.register_function( function=q2_phylogeny.align_to_tree_mafft_raxml, inputs={ 'sequences': FeatureData[Sequence], }, parameters={ 'n_threads': Int % Range(1, None) | Str % Choices(['auto']), 'mask_max_gap_frequency': Float % Range(0, 1, inclusive_end=True), 'mask_min_conservation': Float % Range(0, 1, inclusive_end=True), 'parttree': Bool, 'seed': Int, 'substitution_model': Str % Choices(_RAXML_MODEL_OPT), 'raxml_version': Str % Choices(_RAXML_VERSION_OPT), }, outputs=[ ('alignment', FeatureData[AlignedSequence]), ('masked_alignment', FeatureData[AlignedSequence]), ('tree', Phylogeny[Unrooted]), ('rooted_tree', Phylogeny[Rooted]), ], input_descriptions={ 'sequences': 'The sequences to be used for creating a ' 'iqtree based rooted phylogenetic tree.' }, parameter_descriptions={ 'n_threads': 'The number of threads. (Use `all` to automatically use ' 'all available cores. This value is used when aligning ' 'the sequences and creating the tree with iqtree.', 'mask_max_gap_frequency': 'The maximum relative frequency of gap ' 'characters in a column for the column ' 'to be retained. This relative frequency ' 'must be a number between 0.0 and 1.0 ' '(inclusive), where 0.0 retains only those ' 'columns without gap characters, and 1.0 ' 'retains all columns regardless of gap ' 'character frequency. This value is used ' 'when masking the aligned sequences.', 'mask_min_conservation': 'The minimum relative frequency ' 'of at least one non-gap character in a ' 'column for that column to be retained. ' 'This relative frequency must be a number ' 'between 0.0 and 1.0 (inclusive). For ' 'example, if a value of 0.4 is provided, a ' 'column will only be retained if it ' 'contains at least one character that is ' 'present in at least 40% of the sequences. ' 'This value is used when masking the ' 'aligned sequences.', 'parttree': 'This flag is required if the number of sequences being ' 'aligned are larger than 1000000. Disabled by default. ' 'NOTE: if using this option, it is recomended that only ' 'the CAT-based substitution models of RAxML be ' 'considered for this pipeline.', 'seed': 'Random number seed for the parsimony starting tree. ' 'This allows you to reproduce tree results. ' 'If not supplied then one will be randomly chosen.', 'raxml_version': ('Select a specific CPU optimization of RAxML to ' 'use. The SSE3 versions will run approximately 40% ' 'faster than the standard version. The AVX2 ' 'version will run 10-30% faster than the ' 'SSE3 version.'), 'substitution_model': ('Model of Nucleotide Substitution.'), }, output_descriptions={ 'alignment': 'The aligned sequences.', 'masked_alignment': 'The masked alignment.', 'tree': 'The unrooted phylogenetic tree.', 'rooted_tree': 'The rooted phylogenetic tree.', }, name='Build a phylogenetic tree using raxml and mafft alignment.', description=('This pipeline will start by creating a sequence alignment ' 'using MAFFT, after which any alignment columns that are ' 'phylogenetically uninformative or ambiguously aligned will ' 'be removed (masked). The resulting masked alignment will be ' 'used to infer a phylogenetic tree using RAxML, under the ' 'specified substitution model, and then subsequently ' 'rooted at its midpoint. Output files from each step of the ' 'pipeline will be saved. This includes both the unmasked and ' 'masked MAFFT alignment from q2-alignment methods, and both ' 'the rooted and unrooted phylogenies from q2-phylogeny ' 'methods.' ) )