Adds a method to use a high performance implementation of UniFrac

q2_diversity/__init__.py

@@ -8,8 +8,9 @@
 
 from ._alpha import (alpha, alpha_phylogenetic, alpha_group_significance,
                      alpha_correlation, alpha_rarefaction)
-from ._beta import (beta, beta_phylogenetic, bioenv, beta_group_significance,
-                    beta_correlation, beta_rarefaction)
+from ._beta import (beta, beta_phylogenetic, beta_phylogenetic_hpc, bioenv,
+                    beta_group_significance, beta_correlation,
+                    beta_rarefaction)
 from ._ordination import pcoa
 from ._core_metrics import core_metrics
 from ._filter import filter_distance_matrix
@@ -19,7 +20,8 @@
 __version__ = get_versions()['version']
 del get_versions
 
-__all__ = ['beta', 'beta_phylogenetic', 'alpha', 'alpha_phylogenetic', 'pcoa',
-           'alpha_group_significance', 'bioenv', 'beta_group_significance',
-           'alpha_correlation', 'core_metrics', 'filter_distance_matrix',
-           'beta_correlation', 'alpha_rarefaction', 'beta_rarefaction']
+__all__ = ['beta', 'beta_phylogenetic', 'beta_phylogenetic_hpc', 'alpha',
+           'alpha_phylogenetic', 'pcoa', 'alpha_group_significance', 'bioenv',
+           'beta_group_significance', 'alpha_correlation', 'core_metrics',
+           'filter_distance_matrix', 'beta_correlation', 'alpha_rarefaction',
+           'beta_rarefaction']

q2_diversity/_beta/__init__.py

@@ -6,11 +6,13 @@
 # The full license is in the file LICENSE, distributed with this software.
 # ----------------------------------------------------------------------------
 
-from ._method import (beta_phylogenetic, beta, phylogenetic_metrics,
-                      non_phylogenetic_metrics, all_metrics)
+from ._method import (beta_phylogenetic, beta_phylogenetic_hpc, beta,
+                      phylogenetic_metrics, non_phylogenetic_metrics,
+                      all_metrics)
 from ._visualizer import (bioenv, beta_group_significance, beta_correlation,
                           beta_rarefaction)
 
-__all__ = ['beta_phylogenetic', 'beta', 'bioenv', 'beta_group_significance',
-           'phylogenetic_metrics', 'non_phylogenetic_metrics', 'all_metrics',
-           'beta_correlation', 'beta_rarefaction']
+__all__ = ['beta_phylogenetic', 'beta_phylogenetic_hpc', 'beta', 'bioenv',
+           'beta_group_significance', 'phylogenetic_metrics',
+           'non_phylogenetic_metrics', 'all_metrics', 'beta_correlation',
+           'beta_rarefaction']

q2_diversity/_beta/_method.py

@@ -12,6 +12,12 @@
 import skbio.diversity
 import skbio.tree
 import sklearn.metrics
+import unifrac
+
+from q2_types.feature_table import BIOMV210Format
+from q2_types.tree import NewickFormat
+
+from functools import partial
 
 
 # We should consider moving these functions to scikit-bio. They're part of
@@ -63,6 +69,27 @@ def beta_phylogenetic(table: biom.Table, phylogeny: skbio.TreeNode,
     return results
 
 
+def beta_phylogenetic_hpc(table: BIOMV210Format, phylogeny: NewickFormat,
+                          metric: str, n_jobs: int=1,
+                          variance_adjusted: bool=False,
+                          alpha=1.0,
+                          bypass_tips: bool=False) -> skbio.DistanceMatrix:
+    if metric == 'unweighted_unifrac':
+        f = unifrac.unweighted
+    elif metric == 'weighted_unnormalized_unifrac':
+        f = unifrac.weighted_unnormalized
+    elif metric == 'weighted_normalized_unifrac':
+        f = unifrac.weighted_normalized
+    elif metric == 'generalized_unifrac':
+        f = partial(unifrac.generalized, alpha=alpha)
+    else:
+        raise ValueError("Unknown metric: %s" % metric)
+
+    # unifrac processes tables and trees should be filenames
+    return f(str(table), str(phylogeny), threads=n_jobs,
+             variance_adjusted=variance_adjusted, bypass_tips=bypass_tips)
+
+
 def beta(table: biom.Table, metric: str, n_jobs: int=1)-> skbio.DistanceMatrix:
     if metric not in non_phylogenetic_metrics():
         raise ValueError("Unknown metric: %s" % metric)

q2_diversity/plugin_setup.py

@@ -7,7 +7,7 @@
 # ----------------------------------------------------------------------------
 
 from qiime2.plugin import (Plugin, Str, Properties, MetadataCategory, Choices,
-                           Metadata, Int, Bool, Range)
+                           Metadata, Int, Bool, Range, Float)
 
 import q2_diversity
 from q2_diversity import _alpha as alpha
@@ -38,7 +38,19 @@
                  'and exploring community alpha and beta diversity through '
                  'statistics and visualizations in the context of sample '
                  'metadata.'),
-    short_description='Plugin for exploring community diversity.'
+    short_description='Plugin for exploring community diversity.',
+    citation_text=('Unweighted UniFrac: '
+                   'Lozupone and Knight 2005 Appl Environ Microbiol; DOI: '
+                   '10.1128/AEM.71.12.8228-8235.2005.'
+                   'Weighted UniFrac: '
+                   'Lozupone et al. 2007 Appl Environ Microbiol; DOI: '
+                   '10.1128/AEM.01996-06.'
+                   'Variance adjusted UniFrac: '
+                   'Chang et al. BMC Bioinformatics 2011 '
+                   'https://doi.org/10.1186/1471-2105-12-118.'
+                   'Generalized UniFrac: '
+                   'Chen et al. 2012 Bioinformatics; DOI: '
+                   '10.1093/bioinformatics/bts342')
 )
 
 plugin.methods.register_function(
@@ -68,6 +80,65 @@
                  " for all pairs of samples in a feature table.")
 )
 
+
+plugin.methods.register_function(
+    function=q2_diversity.beta_phylogenetic_hpc,
+    inputs={'table': FeatureTable[Frequency],
+            'phylogeny': Phylogeny[Rooted]},
+    parameters={'metric': Str % Choices(['unweighted_unifrac',
+                                         'weighted_unnormalized_unifrac',
+                                         'weighted_normalized_unifrac',
+                                         'generalized_unifrac']),
+                'n_jobs': Int,
+                'variance_adjusted': Bool,
+                'alpha': Float, 'bypass_tips': Bool},
+    outputs=[('distance_matrix', DistanceMatrix % Properties('phylogenetic'))],
+    input_descriptions={
+        'table': ('The feature table containing the samples over which beta '
+                  'diversity should be computed.'),
+        'phylogeny': ('Phylogenetic tree containing tip identifiers that '
+                      'correspond to the feature identifiers in the table. '
+                      'This tree can contain tip ids that are not present in '
+                      'the table, but all feature ids in the table must be '
+                      'present in this tree.')
+    },
+    parameter_descriptions={
+        'metric': 'The beta diversity metric to be computed.',
+        'n_jobs': 'The number of workers to use.',
+        'variance_adjusted': ('Perform variance adjustment based on Chang et '
+                              'al. BMC Bioinformatics 2011'),
+        'alpha': ('This parameter is only used when the choice of metric is '
+                  'generalized. The value of alpha controls importance of '
+                  'sample proportions. 1.0 is weighted normalized UniFrac. '
+                  '0.0 is close to unweighted UniFrac, but only if the sample '
+                  'proportions are dichotomized.'),
+        'bypass_tips': ('Compute will be reduced by ~50% with this option '
+                        'yielding an approximate result. The option '
+                        'disregards computing UniFrac at the tips of the '
+                        'phylogeny and instead only computes it on the '
+                        'internal nodes. In a bifurcating tree, the tips '
+                        'correspond to approximately 50% of the vertices in '
+                        'the tree, which is how the compute time reduction is'
+                        ' achieved. The use of this parameter is analogous '
+                        'in concept to switching from 99% OTUs to 97% OTUs.')
+    },
+    output_descriptions={'distance_matrix': 'The resulting distance matrix.'},
+    name='Beta diversity (phylogenetic) - High Performance Computation',
+    description=("Computes a user-specified phylogenetic beta diversity metric"
+                 " for all pairs of samples in a feature table. This "
+                 "implementation is recommended for large datasets, otherwise "
+                 "the results are identical to beta_phylogenetic.\n\n"
+                 "This method is an implementation of the Strided State "
+                 "UniFrac algorithm. Multiple variants of the UniFrac metric "
+                 "are available, including Generalized UniFrac (Chen et al. "
+                 "2012), Variance Adjusted UniFrac (Chang et al. 2011), "
+                 "as well as Weighted normalized and unnormalized UniFrac "
+                 "(Lozupone et al. 2007), unweighted UniFrac "
+                 "(Lozupone et al. 2005), and metagenomic UniFrac "
+                 "(Lozupone et al. 2008).")
+)
+
+
 plugin.methods.register_function(
     function=q2_diversity.beta,
     inputs={'table': FeatureTable[Frequency]},

q2_diversity/tests/data/crawford.nwk

@@ -0,0 +1 @@
+((169901:0.39755,(100344:0.37296,((1684221:0.33084,((1136443:0.00014,4374042:0.00204):0.2205,((((263705:0.02657,376397:0.05743):0.02493,263452:0.09328):0.09446,((((229459:0.04726,1571092:0.0371):0.03291,827195:0.03981):0.16617,(((162991:0.01263,318370:0.02928):0.00873,(267689:0.0087,335952:0.01692):0.00962):0.08285,276044:0.25511):0.02402)'c__Clostridia; o__Clostridiales':0.01046,(((186521:0.09255,(((195840:0.05097,181603:0.04737):0.0487,(269378:0.05555,(((215193:0.01971,199307:0.02787):0.03584,344527:0.06642):0.01912,187790:0.06549):0.05223):0.06458):0.01861,(267041:0.06668,441494:0.29606):0.00852):0.00686):0.01105,((274438:0.08266,((268121:0.04956,(194787:0.05527,(337331:0.0305,267411:0.12086):0.00656):0.01187):0.00293,181205:0.07086):0.00228):0.00953,(4418586:0.09245,(((((((4471135:0.04783,195445:0.06353):0.00973,(172705:0.09236,2575787:0.21784):0.01157):0.00173,(269576:0.04917,(((259593:0.02332,1105328:0.012):0.00102,208571:0.01117):0.0008,(182621:0.08672,271449:0.02772):0.00713):0.01471):0.01507):0.00147,181419:0.03032)'c__Clostridia; o__Clostridiales':0.00169,(((((((191958:0.01976,((316842:0.02735,194822:0.01128):0.00721,175432:0.01301):0.01834):0.00247,343906:0.02151):0.00921,3392842:0.00869):0.00315,(351881:0.04144,346098:0.02522):0.00695):0.048,(((((191077:0.05103,351794:0.07438):0.00467,(((4364243:0.04249,261419:0.04021):0.01097,231169:0.01264):0.0132,(403497:0.04479,(261334:0.01174,340189:0.05963):0.01024):0.00256):0.00753):0.00429,(293580:0.02795,3265889:0.05414):0.00656):0.00543,292745:0.04202):0.00014,(322062:0.01797,190273:0.01058):0.04098):0.00564):0.00451,(288931:0.03379,((553395:0.05483,302407:0.0199):0.01312,(833390:0.00627,(275707:0.02319,450047:0.00348):0.01342):0.0492):0.0115):0.01294)'c__Clostridia; o__Clostridiales; f__Lachnospiraceae':0.00448,((132114:0.18434,((274422:0.21213,(314810:0.04013,422727:0.06862):0.08472)'c__Clostridia; o__Clostridiales':0.00016,(((((((((190242:0.01884,(265940:0.00636,170950:0.02803):0.03275):0.05634,187133:0.06732):0.03409,4417539:0.16601):0.01312,(267452:0.01884,231021:0.02579):0.22655)'f__Ruminococcaceae; g__Ruminococcus':0.01162,((550807:0.14219,((((((((4484382:0.03105,(((276404:0.01013,(258725:0.01776,4403349:0.01479):0.01233):0.02161,321484:0.05463):0.00374,263546:0.05758):0.04859):0.00344,196194:0.03084):0.01292,269019:0.02212):0.00207,270385:0.07485):0.02724,((182033:0.00895,263165:0.00701):0.0503,(260753:0.01819,191816:0.05696):0.0122):0.05687):0.00674,270519:0.05105):0.022,((((262677:0.00993,272953:0.00844):0.01976,(187807:0.0179,276985:0.03212):0.00809):0.0029,263106:0.01522):0.06462,176118:0.04609):0.04356)'g__Oscillospira':0.02244,(170555:0.01542,263044:0.02129):0.19443):0.02295):0.02515,(301870:0.15284,(259212:0.12329,185222:0.23345):0.03418)'f__Clostridiaceae':0.02365):0.01303):0.00843,((732128:0.0582,166099:0.08664):0.00226,4480176:0.02225):0.21389):0.0112,((179188:0.04915,194662:0.09909):0.00318,261511:0.06272):0.01032)'c__Clostridia; o__Clostridiales':0.00284,(273084:0.05892,(((((260663:0.02738,(265786:0.02702,260397:0.00524):0.00102):0.00014,275627:0.06381):0.14991,4396877:0.05675):0.01023,828435:0.05156):0.08237,((45363:0.01629,259266:0.05658):0.01623,4407703:0.06932):0.13663)'c__Erysipelotrichi':0.11955):0.00127):0.01284,262409:0.18866):0.00839):0.01056):0.00805,((262766:0.04848,(180206:0.05998,(((262869:0.07152,260655:0.03801):0.00395,(((349142:0.02154,195385:0.00634):0.00159,((176858:0.01629,263362:0.01476):0.0004,233313:0.00963):0.00408):0.00147,(((178031:0.01612,(259263:0.0181,263946:0.02447):0.07026):0.00147,268416:0.00842):0.00532,(97294:0.02181,258969:0.03813):0.00502):0.0039):0.00851):0.01331,(((187703:0.03164,259056:0.01433):0.01444,191772:0.02529):0.01041,276260:0.03673):0.0168):0.02587):0.00758):0.00603,(((184151:0.03171,176039:0.02716):0.05897,310490:0.04338):0.00551,((333053:0.04164,((((((((331965:0.08704,261409:0.01737):0.01822,185777:0.01487):0.04786,(259434:0.02291,276531:0.02123):0.01824):0.00853,303479:0.02542):0.00508,263908:0.04835):0.01457,((258522:0.02949,274021:0.05646):0.00554,181344:0.04727):0.00566):0.00176,(272454:0.03068,176850:0.06171):0.01689):0.01607,275563:0.01872):0.00741):0.00923,318563:0.06893):0.01131):0.00257):0.0081):0.0007):0.0016):0.00336,((((((312476:0.02917,174272:0.04651):0.00785,(((268755:0.01177,268581:0.02385):0.00878,(179719:0.04377,264021:0.05912):0.00417):0.00394,(260058:0.03496,(167204:0.01011,829401:0.01565):0.03983):0.00244):0.00992):0.01245,((((((((178926:0.02199,196825:0.01879):0.00883,(443945:0.02387,310748:0.00905):0.03013):0.01777,260756:0.01673):0.00669,((((233817:0.00475,259910:0.01695):0.0001,197775:0.02372):0.00786,130335:0.03254):0.00866,4365109:0.0344):0.00354):0.00157,((334365:0.03359,271766:0.03304):0.00976,(206494:0.02039,181249:0.04899):0.01657):0.00257):0.00474,(((((265828:0.01611,216403:0.03131):0.00681,180919:0.07082):0.00659,((270662:0.04106,229386:0.01722):0.04132,(187989:0.01675,164308:0.02502):0.01745):0.01998):0.00272,((307595:0.04286,178779:0.01324):0.01155,259888:0.06879):0.0098):0.01198,173417:0.03133):0.0056):0.00441,(186526:0.01221,233411:0.0164):0.06098):0.00533,(301012:0.03892,(266483:0.02079,839215:0.0076):0.02063):0.00659):0.01471):0.00433,(((((((175416:0.06589,(((181141:0.02134,197216:0.04356):0.00062,(273515:0.06915,188536:0.03918):0.0068):0.009,697874:0.0303):0.0203):0.00368,(179181:0.08572,(268923:0.11712,351859:0.05093):0.03893):0.00565):0.00429,((((185743:0.07302,274844:0.06304):0.02997,(190460:0.01175,192971:0.02492):0.0557):0.00889,270396:0.13586):0.00157,336145:0.06697):0.00809):0.00759,(((274597:0.05276,((259228:0.09494,264373:0.04067):0.00411,(((343581:0.00883,266595:0.03526):0.00128,269359:0.02279):0.00928,275150:0.04595):0.01442):0.01243):0.00596,(197790:0.07695,((274106:0.03127,260828:0.02915):0.00728,((180105:0.00572,(196777:0.02608,179063:0.02119):0.02629):0.00667,177802:0.01713):0.01597):0.00679):0.0135):0.01445,((((((275078:0.05198,271378:0.04527):0.00987,276580:0.06941):0.00745,260653:0.01951):0.00577,(259335:0.00857,269992:0.01649):0.02089):0.00607,(261606:0.01776,((260205:0.01675,837473:0.0327):0.01931,259175:0.0661):0.01057):0.03771):0.01365,(272812:0.01332,(275136:0.0504,265641:0.04142):0.01641):0.05327):0.01447):0.01207):0.01462,(180362:0.0488,214471:0.03306):0.02282):0.00489,((276663:0.07249,(1108453:0.12347,267457:0.04345):0.01011):0.00558,(174959:0.05484,185754:0.01372):0.08833):0.00679):0.00361,(181091:0.05605,(319909:0.01099,4462541:0.01663):0.05346):0.0137):0.0035):0.00421,(((((291750:0.01414,178659:0.02705):0.00913,350381:0.03212):0.01138,(((((314963:0.02373,(234121:0.00158,274018:0.01522):0.01383):0.00336,((330296:0.00877,343420:0.00828):0.00199,267388:0.05277):0.00813):0.00348,((175573:0.00729,(((274521:0.02619,191887:0.02143):0.00412,2120775:0.03204):0.0148,436341:0.01208):0.02026):0.04471,(199181:0.05741,266816:0.03119):0.01288):0.0044):0.00294,((180972:0.00911,183211:0.01607):0.01057,227886:0.01216):0.00806):0.04236,(348398:0.00318,270491:0.02772):0.02149):0.016):0.00697,(327236:0.072,182016:0.06278):0.02379):0.00015,(258250:0.03667,(275819:0.02306,275470:0.00947):0.0143):0.01639):0.00479):0.00187,((320490:0.04718,311174:0.01972):0.00144,(193463:0.0092,191398:0.04605):0.03482):0.05332):0.00971):0.00744,((354957:0.05068,183390:0.04344):0.00734,275869:0.07717):0.0236):0.03292):0.00127):0.01695):0.01217,(461524:0.11627,((265106:0.03592,(178735:0.03407,267123:0.02167):0.02808):0.01912,199403:0.02374):0.05723):0.23533):0.03382):0.06256)'p__Firmicutes':0.00964,((115186:0.01033,687185:0.04697):0.18622,(214919:0.07235,(((((4397402:0.02449,187233:0.04148):0.00016,166911:0.01405):0.01203,4338733:0.18171):0.05395,(((452823:0.00238,259372:0.01508):0.00255,239571:0.02438):0.00333,135956:0.03044):0.04831):0.05536,303652:0.15985):0.07926):0.0439):0.05025):0.04842):0.02284):0.01143,(((((((1107945:0.00015,((2137001:0.03611,4468234:0.02727):0.00026,191483:0.02217):0.03914):0.08626,353782:0.02512):0.08438,(((4346374:0.02476,184567:0.0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q2_diversity/tests/data/vaw.nwk

@@ -0,0 +1 @@
+(GG_OTU_1:1,(GG_OTU_2:1,GG_OTU_3:1):1,(GG_OTU_5:1,GG_OTU_4:1):1);