Uncharacterized
uncharacterized
Hypothetical
hypothetical
Uncaracterized
uncaracterized
Hipothetical
hipothetical
Hypotetical
hypotetical
Hipotetical
hipotetical
Ipotetical
ipotetical
Ipothetical
ipothetical
Uncharacterised
uncharacterised
Uncaracterised
uncaracterised
unknown
DUF
TIGR00011
TIGR00024
TIGR00044
TIGR00092
TIGR00106
TIGR00149
TIGR00153
TIGR00156
TIGR00159
TIGR00161
TIGR00162
TIGR00164
TIGR00186
TIGR00196
TIGR00197
TIGR00245
TIGR00247
TIGR00250
TIGR00251
TIGR00252
TIGR00253
TIGR00255
TIGR00257
TIGR00258
TIGR00264
TIGR00266
TIGR00267
TIGR00268
TIGR00269
TIGR00270
TIGR00282
TIGR00284
TIGR00288
TIGR00289
TIGR00294
TIGR00295
TIGR00296
TIGR00297
TIGR00299
TIGR00300
TIGR00303
TIGR00304
TIGR00311
TIGR00318
TIGR00323
TIGR00340
TIGR00341
TIGR00366
TIGR00367
TIGR00368
TIGR00370
TIGR00375
TIGR00376
TIGR00411
TIGR00412
TIGR00425
TIGR00427
TIGR00454
TIGR00481
TIGR00486
TIGR00488
TIGR00494
TIGR00495
TIGR00529
TIGR00537
TIGR00539
TIGR00540
TIGR00542
TIGR00645
TIGR00646
TIGR00659
TIGR00686
TIGR00688
TIGR00701
TIGR00703
TIGR00704
TIGR00725
TIGR00726
TIGR00730
TIGR00734
TIGR00736
TIGR00789
TIGR01158
TIGR01177
TIGR01209
TIGR01210
TIGR01212
TIGR01244
TIGR01303
TIGR01304
TIGR01334
TIGR01342
TIGR01370
TIGR01407
TIGR01412
TIGR01415
TIGR01437
TIGR01440
TIGR01448
TIGR01454
TIGR01456
TIGR01457
TIGR01458
TIGR01459
TIGR01475
TIGR01490
TIGR01491
TIGR01513
TIGR01542
TIGR01544
TIGR01545
TIGR01548
TIGR01555
TIGR01560
TIGR01561
TIGR01563
TIGR01577
TIGR01578
TIGR01579
TIGR01581
TIGR01616
TIGR01618
TIGR01619
TIGR01620
TIGR01621
TIGR01626
TIGR01630
TIGR01633
TIGR01657
TIGR01666
TIGR01668
TIGR01671
TIGR01672
TIGR01684
TIGR01690
TIGR01701
TIGR01705
TIGR01714
TIGR01721
TIGR01725
TIGR01739
TIGR01777
TIGR01831
TIGR01870
TIGR01878
TIGR01883
TIGR01894
TIGR01896
TIGR01897
TIGR01906
TIGR01949
TIGR01952
TIGR01956
TIGR01976
TIGR01977
TIGR01993
TIGR02003
TIGR02004
TIGR02076
TIGR02099
TIGR02117
TIGR02133
TIGR02146
TIGR02156
TIGR02157
TIGR02158
TIGR02160
TIGR02173
TIGR02178
TIGR02186
TIGR02187
TIGR02190
TIGR02192
TIGR02196
TIGR02200
TIGR02204
TIGR02206
TIGR02215
TIGR02216
TIGR02219
TIGR02220
TIGR02221
TIGR02230
TIGR02234
TIGR02245
TIGR02256
TIGR02291
TIGR02293
TIGR02300
TIGR02301
TIGR02302
TIGR02304
TIGR02327
TIGR02328
TIGR02353
TIGR02358
TIGR02366
TIGR02391
TIGR02396
TIGR02421
TIGR02442
TIGR02443
TIGR02444
TIGR02449
TIGR02450
TIGR02452
TIGR02457
TIGR02458
TIGR02459
TIGR02463
TIGR02485
TIGR02498
TIGR02501
TIGR02526
TIGR02530
TIGR02531
TIGR02535
TIGR02536
TIGR02556
TIGR02569
TIGR02574
TIGR02577
TIGR02578
TIGR02579
TIGR02581
TIGR02584
TIGR02587
TIGR02588
TIGR02591
TIGR02606
TIGR02609
TIGR02610
TIGR02611
TIGR02612
TIGR02613
TIGR02620
TIGR02635
TIGR02642
TIGR02645
TIGR02646
TIGR02647
TIGR02652
TIGR02653
TIGR02668
TIGR02674
TIGR02677
TIGR02678
TIGR02679
TIGR02680
TIGR02682
TIGR02683
TIGR02684
TIGR02687
TIGR02688
TIGR02699
TIGR02700
TIGR02710
TIGR02722
TIGR02740
TIGR02757
TIGR02808
TIGR02811
TIGR02828
TIGR02873
TIGR02921
TIGR02922
TIGR02935
TIGR02943
TIGR02945
TIGR02947
TIGR02949
TIGR02952
TIGR02954
TIGR02959
TIGR02960
TIGR02979
TIGR02988
TIGR03008
TIGR03012
TIGR03014
TIGR03015
TIGR03016
TIGR03017
TIGR03018
TIGR03019
TIGR03021
TIGR03027
TIGR03032
TIGR03054
TIGR03055
TIGR03056
TIGR03073
TIGR03076
TIGR03077
TIGR03084
TIGR03085
TIGR03086
TIGR03087
TIGR03088
TIGR03089
TIGR03097
TIGR03098
TIGR03099
TIGR03100
TIGR03101
TIGR03103
TIGR03104
TIGR03106
TIGR03108
TIGR03109
TIGR03110
TIGR03111
TIGR03112
TIGR03113
TIGR03114
TIGR03115
TIGR03116
TIGR03117
TIGR03118
TIGR03123
TIGR03143
TIGR03151
TIGR03157
TIGR03159
TIGR03165
TIGR03166
TIGR03169
TIGR03202
TIGR03212
TIGR03214
TIGR03223
TIGR03233
TIGR03252
TIGR03266
TIGR03267
TIGR03268
TIGR03270
TIGR03271
TIGR03272
TIGR03274
TIGR03275
TIGR03276
TIGR03277
TIGR03279
TIGR03280
TIGR03281
TIGR03282
TIGR03285
TIGR03286
TIGR03287
TIGR03291
TIGR03308
TIGR03309
TIGR03312
TIGR03313
TIGR03318
TIGR03320
TIGR03329
TIGR03340
TIGR03341
TIGR03347
TIGR03348
TIGR03351
TIGR03352
TIGR03353
TIGR03354
TIGR03355
TIGR03357
TIGR03358
TIGR03359
TIGR03360
TIGR03362
TIGR03363
TIGR03364
TIGR03366
TIGR03368
TIGR03373
TIGR03405
TIGR03406
TIGR03418
TIGR03424
TIGR03425
TIGR03427
TIGR03428
TIGR03432
TIGR03459
TIGR03460
TIGR03466
TIGR03467
TIGR03468
TIGR03469
TIGR03470
TIGR03471
TIGR03472
TIGR03473
TIGR03480
TIGR03481
TIGR03485
TIGR03486
TIGR03487
TIGR03489
TIGR03492
TIGR03503
TIGR03504
TIGR03526
TIGR03527
TIGR03540
TIGR03541
TIGR03543
TIGR03549
TIGR03576
TIGR03577
TIGR03578
TIGR03579
TIGR03580
TIGR03581
TIGR03582
TIGR03583
TIGR03587
TIGR03642
TIGR03643
TIGR03644
TIGR03645
TIGR03667
TIGR03668
TIGR03693
TIGR03709
TIGR03728
TIGR03734
TIGR03735
TIGR03736
TIGR03737
TIGR03738
TIGR03739
TIGR03745
TIGR03746
TIGR03747
TIGR03748
TIGR03749
TIGR03750
TIGR03751
TIGR03752
TIGR03756
TIGR03757
TIGR03758
TIGR03759
TIGR03761
TIGR03764
TIGR03766
TIGR03767
TIGR03768
TIGR03773
TIGR03789
TIGR03792
TIGR03805
TIGR03806
TIGR03809
TIGR03813
TIGR03815
TIGR03816
TIGR03817
TIGR03819
TIGR03822
TIGR03826
TIGR03829
TIGR03833
TIGR03842
TIGR03843
TIGR03850
TIGR03853
TIGR03854
TIGR03857
TIGR03858
TIGR03864
TIGR03868
TIGR03869
TIGR03873
TIGR03875
TIGR03876
TIGR03877
TIGR03878
TIGR03880
TIGR03881
TIGR03885
TIGR03886
TIGR03890
TIGR03894
TIGR03899
TIGR03900
TIGR03903
TIGR03904
TIGR03905
TIGR03913
TIGR03914
TIGR03916
TIGR03931
TIGR03936
TIGR03941
TIGR03943
TIGR03950
TIGR03959
TIGR03960
TIGR03961
TIGR03964
TIGR03965
TIGR03966
TIGR03967
TIGR03968
TIGR03970
TIGR03973
TIGR03974
TIGR03976
TIGR03977
TIGR03978
TIGR03979
TIGR03981
TIGR03982
TIGR03984
TIGR03985
TIGR03986
TIGR03987
TIGR03991
TIGR03995
TIGR03996
TIGR03997
TIGR04002
TIGR04013
TIGR04014
TIGR04018
TIGR04019
TIGR04024
TIGR04027
TIGR04028
TIGR04029
TIGR04030
TIGR04039
TIGR04040
TIGR04041
TIGR04042
TIGR04043
TIGR04044
TIGR04045
TIGR04046
TIGR04047
TIGR04049
TIGR04050
TIGR04052
TIGR04062
TIGR04063
TIGR04065
TIGR04066
TIGR04069
TIGR04072
TIGR04082
TIGR04083
TIGR04086
TIGR04097
TIGR04099
TIGR04100
TIGR04101
TIGR04102
TIGR04108
TIGR04111
TIGR04112
TIGR04113
TIGR04116
TIGR04123
TIGR04124
TIGR04127
TIGR04129
TIGR04132
TIGR04133
TIGR04134
TIGR04136
TIGR04137
TIGR04138
TIGR04142
TIGR04145
TIGR04156
TIGR04161
TIGR04165
TIGR04168
TIGR04169
TIGR04172
TIGR04175
TIGR04177
TIGR04179
TIGR04180
TIGR04181
TIGR04190
TIGR04205
TIGR04206
TIGR04211
TIGR04212
TIGR04220
TIGR04229
TIGR04249
TIGR04252
TIGR04260
TIGR04268
TIGR04276
TIGR04280
TIGR04281
TIGR04282
TIGR04283
TIGR04284
TIGR04290
TIGR04292
TIGR04293
TIGR04295
TIGR04297
TIGR04302
TIGR04303
TIGR04304
TIGR04318
TIGR04335
TIGR04336
TIGR04337
TIGR04338
TIGR04339
TIGR04340
TIGR04348
TIGR04349
TIGR04352
TIGR04355
TIGR04356
TIGR04357
TIGR04360
TIGR04369
TIGR04374
TIGR04375
TIGR04376
TIGR04385
TIGR04400
TIGR04413
TIGR04420
TIGR04421
TIGR04422
TIGR04423
TIGR04434
TIGR04435
TIGR04438
TIGR04442
TIGR04454
TIGR04455
TIGR04470
TIGR04471
TIGR04472
TIGR04477
TIGR04503
TIGR04522
TIGR04533
TIGR04535
TIGR04536
TIGR04540
TIGR04542
TIGR04548
TIGR04553
TIGR04554
TIGR04558
TIGR04559
TIGR04561
TIGR04570
PF08975
PF03752
PF09713
PF17623
PF13754
PF17615
PF01930
PF14916
PF09717
PF01982
PF05899
PF17074
PF06207
PF06210
PF06219
PF06226
PF06230
PF06231
PF06237
PF06242
PF06245
PF06250
PF06252
PF06260
PF06265
PF06267
PF06269
PF06270
PF06275
PF06279
PF06281
PF06282
PF06287
PF01954
PF06288
PF06292
PF06295
PF06299
PF06304
PF06327
PF06335
PF06341
PF06342
PF06348
PF06353
PF06356
PF06358
PF06362
PF06364
PF06370
PF06378
PF06380
PF06381
PF06382
PF06388
PF06417
PF06435
PF01958
PF06439
PF06448
PF06449
PF06454
PF06461
PF06465
PF06469
PF06476
PF06477
PF06485
PF06486
PF06493
PF06496
PF06497
PF01345
PF06500
PF06503
PF06510
PF06513
PF06518
PF06523
PF06526
PF06531
PF06532
PF01969
PF06533
PF06544
PF06545
PF06547
PF06549
PF06551
PF06557
PF06563
PF06568
PF06569
PF06570
PF06572
PF06575
PF06576
PF06577
PF06582
PF06587
PF06592
PF06599
PF06600
PF06608
PF06611
PF06612
PF06615
PF06618
PF06619
PF06620
PF06625
PF06626
PF06627
PF06631
PF06633
PF06634
PF06636
PF06643
PF01976
PF06648
PF06649
PF06651
PF06658
PF06663
PF06666
PF06671
PF06672
PF06674
PF06675
PF06676
PF06678
PF06679
PF06680
PF06681
PF06683
PF06685
PF06688
PF06690
PF06691
PF06693
PF06697
PF06698
PF06707
PF06708
PF06709
PF06711
PF06712
PF06716
PF06717
PF06718
PF06721
PF06722
PF06724
PF06727
PF06736
PF06740
PF06742
PF06746
PF06748
PF06749
PF06758
PF06760
PF06764
PF06797
PF01986
PF06799
PF06802
PF06803
PF06822
PF06823
PF06836
PF06840
PF06842
PF06844
PF06849
PF06851
PF06852
PF06853
PF06856
PF06863
PF06865
PF06866
PF06868
PF06869
PF01989
PF06880
PF06882
PF06884
PF06887
PF06889
PF06897
PF06900
PF06906
PF06908
PF06912
PF06916
PF01995
PF06918
PF06924
PF06930
PF06932
PF06935
PF06938
PF06939
PF06940
PF06945
PF06947
PF06949
PF06950
PF06961
PF06966
PF06972
PF06973
PF06974
PF06975
PF06980
PF06993
PF06998
PF07000
PF01998
PF07006
PF07011
PF07013
PF07023
PF07026
PF07027
PF07028
PF07030
PF07032
PF07038
PF07040
PF07041
PF07043
PF07044
PF07045
PF07048
PF07056
PF07059
PF07063
PF02001
PF07067
PF07075
PF07076
PF07077
PF07079
PF07080
PF07081
PF07082
PF07083
PF07087
PF07092
PF07094
PF07096
PF07097
PF07098
PF07099
PF07101
PF07102
PF07103
PF07104
PF07105
PF07112
PF07116
PF07117
PF07118
PF07119
PF07120
PF07125
PF07128
PF07129
PF07131
PF07134
PF07136
PF07138
PF07139
PF07142
PF07146
PF07150
PF07151
PF07154
PF07159
PF07165
PF07166
PF07176
PF07182
PF07183
PF07185
PF07187
PF07190
PF07193
PF07197
PF07198
PF07199
PF07203
PF07205
PF07208
PF07209
PF07210
PF07214
PF07215
PF07220
PF07226
PF07233
PF07235
PF07237
PF07242
PF07248
PF07252
PF07256
PF07270
PF07273
PF07274
PF07278
PF07279
PF07285
PF07286
PF07288
PF07290
PF07293
PF07301
PF07305
PF07306
PF07308
PF07312
PF07313
PF07314
PF07315
PF07316
PF07318
PF07323
PF07326
PF07330
PF07338
PF07339
PF07341
PF07342
PF07343
PF07345
PF07346
PF07349
PF07350
PF02520
PF07351
PF07356
PF07358
PF07363
PF07368
PF07369
PF07370
PF07371
PF07372
PF07374
PF07377
PF07379
PF07383
PF07384
PF07386
PF07389
PF07394
PF07397
PF07403
PF07405
PF07408
PF07411
PF07420
PF07423
PF07431
PF07433
PF07438
PF07439
PF07457
PF07466
PF07469
PF07481
PF07482
PF07509
PF07510
PF07511
PF07485
PF07550
PF07551
PF07556
PF07560
PF07561
PF07563
PF07564
PF07566
PF07577
PF07579
PF07588
PF07590
PF07597
PF07598
PF07599
PF07600
PF07602
PF07603
PF07606
PF07607
PF07608
PF07609
PF07610
PF07611
PF07613
PF07614
PF07617
PF07618
PF07619
PF07621
PF07622
PF07625
PF07628
PF07629
PF07632
PF07643
PF07659
PF01519
PF07667
PF07671
PF07713
PF07753
PF07754
PF07755
PF17396
PF07756
PF07758
PF07759
PF07760
PF07761
PF07762
PF07773
PF07774
PF07784
PF07785
PF07786
PF07789
PF07791
PF07793
PF07794
PF07843
PF07795
PF07845
PF07796
PF07797
PF07798
PF07849
PF07852
PF07799
PF07800
PF07816
PF07854
PF07801
PF07853
PF07864
PF07865
PF07866
PF07867
PF07868
PF07869
PF07870
PF07871
PF07872
PF02593
PF07877
PF07909
PF07889
PF07891
PF07892
PF07893
PF07894
PF07900
PF07901
PF07895
PF07896
PF07898
PF07911
PF07913
PF07914
PF07933
PF07946
PF07920
PF07939
PF07937
PF07955
PF07958
PF07954
PF07956
PF07950
PF07997
PF08002
PF08004
PF08006
PF08012
PF08014
PF08019
PF08020
PF08044
PF08101
PF08217
PF08213
PF05414
PF08224
PF08226
PF08349
PF08350
PF08333
PF08351
PF08353
PF08354
PF08331
PF08338
PF08340
PF08522
PF08409
PF08410
PF08401
PF08427
PF08489
PF08490
PF08508
PF08520
PF08538
PF08550
PF08555
PF08560
PF03564
PF08570
PF08576
PF08578
PF08719
PF08588
PF08589
PF08590
PF08592
PF08593
PF08611
PF08643
PF08648
PF08681
PF08682
PF08747
PF08760
PF08768
PF08796
PF08807
PF08811
PF08818
PF08819
PF08820
PF08822
PF08827
PF08830
PF08837
PF08838
PF08844
PF08846
PF08848
PF08850
PF08852
PF08853
PF08854
PF08855
PF08856
PF08860
PF08861
PF08862
PF08865
PF08875
PF08873
PF08874
PF08876
PF08878
PF08894
PF08893
PF08895
PF08897
PF08896
PF08898
PF08899
PF08900
PF08903
PF08901
PF08902
PF08904
PF08905
PF08906
PF08908
PF08907
PF08909
PF08983
PF08982
PF08984
PF08948
PF08949
PF08950
PF08933
PF08952
PF08956
PF08965
PF08958
PF08960
PF08962
PF08974
PF08963
PF08966
PF08980
PF08967
PF08968
PF09002
PF08986
PF09001
PF09004
PF08987
PF08979
PF08989
PF09005
PF08953
PF01579
PF08972
PF08921
PF08922
PF08924
PF08925
PF08926
PF08928
PF08929
PF08930
PF08939
PF08940
PF08942
PF09081
PF09082
PF09083
PF09086
PF09094
PF09095
PF09118
PF09122
PF09123
PF09130
PF09147
PF09148
PF09149
PF09151
PF09152
PF09153
PF09154
PF09155
PF09167
PF09172
PF09175
PF09178
PF09183
PF09185
PF09186
PF09188
PF09189
PF09196
PF09205
PF09209
PF09210
PF09211
PF09218
PF09224
PF09227
PF09234
PF09244
PF09248
PF09260
PF09269
PF09291
PF09301
PF09313
PF09314
PF09317
PF09320
PF09321
PF09322
PF09323
PF09324
PF09327
PF09331
PF09342
PF09345
PF09347
PF09348
PF09350
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PF03625
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PF03729
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PF03754
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PF03778
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PF11579
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PF07957
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PF11730
PF11738
PF11736
PF11737
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PF11742
PF11746
PF11745
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PF11748
PF11750
PF11752
PF03889
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PF11780
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PF11808
PF03891
PF11809
PF11811
PF11810
PF11812
PF11813
PF11815
PF11816
PF11819
PF11820
PF03904
PF11821
PF11822
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PF11824
PF11826
PF11827
PF11828
PF11829
PF11830
PF11832
PF11835
PF11837
PF11840
PF11841
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PF11844
PF11845
PF11847
PF11848
PF11849
PF11850
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PF11857
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PF11861
PF11862
PF11863
PF11864
PF11865
PF11866
PF11867
PF11868
PF11869
PF11870
PF11871
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PF11873
PF11874
PF11875
PF11876
PF11877
PF11878
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PF11890
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PF11899
PF11900
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PF11911
PF11912
PF11913
PF11914
PF11915
PF11917
PF11919
PF11920
PF11921
PF11922
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PF11925
PF11926
PF11927
PF11928
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PF11931
PF11932
PF11934
PF11935
PF11936
PF11937
PF11940
PF17432
PF11941
PF03984
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PF11947
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PF11950
PF03988
PF11953
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PF11958
PF11959
PF11960
PF11961
PF11963
PF11965
PF03990
PF11979
PF11981
PF11982
PF11984
PF11985
PF11990
PF11992
PF11994
PF03993
PF11995
PF11996
PF11997
PF11998
PF11999
PF12001
PF12004
PF12005
PF03994
PF12006
PF12007
PF12010
PF12012
PF12014
PF12015
PF12021
PF12022
PF12023
PF12024
PF12026
PF12027
PF12028
PF12029
PF12030
PF12033
PF12034
PF12036
PF12037
PF12038
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PF12040
PF12043
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PF12048
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PF04007
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PF12071
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PF12078
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PF04009
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PF12091
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PF04010
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PF12141
PF04019
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PF12159
PF12200
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PF12207
PF12208
PF12223
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PF12228
PF12239
PF12244
PF12263
PF12268
PF12266
PF12267
PF12274
PF12275
PF12276
PF12277
PF12279
PF04015
PF12285
PF12286
PF12291
PF12292
PF12294
PF12299
PF12302
PF12305
PF12307
PF12311
PF12321
PF12331
PF12337
PF12340
PF12342
PF12345
PF12358
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PF12364
PF12365
PF04033
PF12376
PF12379
PF12395
PF12396
PF04017
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PF12420
PF12425
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PF12432
PF12435
PF12438
PF04018
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PF12446
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PF12452
PF12461
PF12463
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PF12479
PF12480
PF04025
PF12487
PF12488
PF12493
PF04027
PF12502
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PF12506
PF12509
PF12511
PF12512
PF12514
PF12516
PF12517
PF12518
PF12520
PF12521
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PF12525
PF12527
PF12526
PF04123
PF12530
PF12532
PF12540
PF12541
PF12543
PF04028
PF12552
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PF12562
PF12565
PF12566
PF12570
PF12572
PF12576
PF12579
PF12581
PF12582
PF12585
PF12586
PF12587
PF12591
PF12592
PF12594
PF12597
PF12599
PF12600
PF12603
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PF12616
PF12618
PF12620
PF04070
PF12635
PF12636
PF12644
PF12646
PF12650
PF12653
PF12654
PF12655
PF12663
PF12664
PF12668
PF12670
PF12672
PF12673
PF12675
PF12676
PF12677
PF12683
PF12684
PF12686
PF12687
PF12290
PF12707
PF12712
PF12713
PF12720
PF10300
PF12723
PF12725
PF12758
PF12823
PF12825
PF12842
PF04037
PF12863
PF12864
PF12866
PF12873
PF12875
PF12877
PF12883
PF12889
PF04063
PF12903
PF12915
PF12916
PF12927
PF12930
PF12939
PF12943
PF04064
PF12952
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PF12954
PF12955
PF12956
PF12957
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PF12959
PF12960
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PF12962
PF12963
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PF12975
PF04074
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PF12978
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PF12990
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PF13020
PF13024
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PF04087
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PF04094
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PF13042
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PF13077
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PF13079
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PF04134
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PF04149
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PF13126
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PF13182
PF04165
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PF13198
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PF13210
PF13211
PF04167
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PF13213
PF13214
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PF13217
PF13218
PF13219
PF13220
PF13221
PF13222
PF13223
PF13224
PF13225
PF13226
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PF13228
PF13204
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PF13264
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PF04175
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PF13271
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PF13282
PF13281
PF13284
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PF13300
PF13301
PF13311
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PF13313
PF13314
PF13321
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PF13316
PF13317
PF13318
PF13319
PF13320
PF13322
PF13331
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PF13351
PF04190
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PF13388
PF13389
PF13390
PF04214
PF13422
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PF13430
PF13438
PF13448
PF13464
PF13475
PF13493
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PF04217
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PF13498
PF13503
PF13511
PF13526
PF13548
PF13552
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PF13559
PF04219
PF13566
PF13567
PF13569
PF13571
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PF13575
PF13590
PF13595
PF13598
PF13600
PF13605
PF13628
PF13635
PF13642
PF13643
PF13660
PF13663
PF13664
PF13665
PF13680
PF13687
PF13689
PF13698
PF13699
PF13700
PF13709
PF04222
PF13711
PF13732
PF13739
PF13747
PF13752
PF13761
PF13763
PF13767
PF13770
PF04224
PF13773
PF13775
PF13776
PF13777
PF13778
PF13779
PF13780
PF13783
PF13785
PF13786
PF04235
PF13788
PF13789
PF13799
PF13803
PF13810
PF13811
PF13821
PF13826
PF13827
PF13828
PF13829
PF13830
PF13834
PF13835
PF13836
PF13846
PF13852
PF10670
PF13858
PF04238
PF13863
PF13870
PF13875
PF13886
PF13898
PF13904
PF13907
PF13910
PF04239
PF13915
PF13926
PF13937
PF13946
PF13948
PF13952
PF13959
PF13960
PF13961
PF13968
PF13970
PF13973
PF13978
PF13986
PF13988
PF10774
PF14004
PF14009
PF14012
PF04241
PF14014
PF14015
PF14016
PF14017
PF14018
PF14019
PF14020
PF14022
PF14023
PF04242
PF14024
PF14025
PF14026
PF14027
PF14029
PF14030
PF14033
PF14042
PF14053
PF14054
PF14056
PF14059
PF14060
PF14062
PF14063
PF14065
PF14066
PF14074
PF14076
PF14078
PF14079
PF14080
PF14081
PF14082
PF14084
PF14085
PF14086
PF14087
PF14088
PF14091
PF14092
PF14093
PF14094
PF14096
PF14101
PF14103
PF14104
PF14105
PF14106
PF14107
PF14108
PF14110
PF14111
PF14114
PF14117
PF14119
PF04250
PF14123
PF14124
PF14125
PF14126
PF14127
PF14128
PF14129
PF14130
PF14131
PF14132
PF01861
PF14133
PF14134
PF14135
PF14136
PF14137
PF14146
PF14154
PF14155
PF14172
PF14187
PF14188
PF14189
PF14190
PF14192
PF14193
PF14195
PF14199
PF14201
PF04254
PF14208
PF14209
PF14210
PF14213
PF14216
PF14217
PF14219
PF14220
PF04255
PF14221
PF14224
PF14229
PF14230
PF14232
PF14233
PF14234
PF14235
PF14236
PF14237
PF04256
PF14238
PF14242
PF14243
PF14248
PF14251
PF14252
PF14254
PF14257
PF14258
PF14261
PF11611
PF14263
PF14265
PF14267
PF14270
PF14271
PF04260
PF14273
PF14274
PF14275
PF14276
PF14277
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#!/bin/bash
NAM=$(basename ${1} _protein.faa.gz)
awk -vN=${NAM} '{if ($0 ~ /^>/){print $0"\t"N}else{print $0}}' <(zcat ${1}) > ${NAM}.faa
library(data.table)
library(tidyverse)
library(ggpubr)
library(ggpubr)
taxonomy <- fread("gzcat ~/Downloads/genomes_taxonomy.tsv.gz", header = FALSE)
unk_vs_rs82 <- fread("gzcat ~/Downloads/gu_vs_refseq82_hypo.tsv.gz", header = FALSE)
unk_vs_rs82_1e25 <- unk_vs_rs82 %>% filter(V11 <= 1e-25) %>% tbl_df %>%
left_join(taxonomy, by = c("V15" = "V1"))
total_hits <- unk_vs_rs82_1e25$V2.x %>% unique() %>% length()
unk_vs_rs82_1e25_prop <- unk_vs_rs82_1e25 %>%
group_by(V2.x, V17) %>%
count %>%
ungroup() %>%
group_by(V2.x) %>%
mutate(prop = n/sum(n)) %>%
arrange(V2.x) %>%
ungroup() %>%
complete(V2.x, V17, fill = list(prop = 0, n = 0))
unk_vs_rs82_1e25_prop %>%
gghistogram(x = "prop",
color = "V17",
fill = "V17") +
theme_light()
g_c_gu %>% as.tibble() %>%
left_join(order_names) %>%
right_join(hits_hypo_1 %>%
mutate(cluster_id = as.character(V2.x))) %>%
.$components %>% table %>% hist
hits_hypo_1 <- unk_vs_rs82_1e25_prop %>%
filter(V17 == "hypo") %>%
filter(prop == 1)
hits_hypo_75_1 <- unk_vs_rs82_1e25_prop %>%
filter(V17 == "hypo") %>%
filter(prop >= 0.75)
hits_hypo_75_99 <- unk_vs_rs82_1e25_prop %>%
filter(V17 == "hypo") %>%
filter(prop >= 0.75, prop < 1)
hits_hypo_50_75 <- unk_vs_rs82_1e25_prop %>%
filter(V17 == "hypo") %>%
filter(prop >= 0.5, prop < 0.75)
hits_hypo_lt50 <- unk_vs_rs82_1e25_prop %>%
filter(V17 == "hypo") %>%
filter(prop < 0.5)
df <- data_frame(cl = c("100%","(100%,75%]","(75%,50%]","(50%,0)"),
prop = c(dim(hits_hypo_1)[[1]]/total_hits,
dim(hits_hypo_75_99)[[1]]/total_hits,
dim(hits_hypo_50_75)[[1]]/total_hits,
dim(hits_hypo_lt50)[[1]]/total_hits))
df$cl <- factor(df$cl, levels = rev(c("100%","(100%,75%]","(75%,50%]","(50%,0)")))
ggplot(df, aes(cl, prop)) +
geom_bar(stat = "identity") +
rotate() +
theme_light() +
ylab("Proportion") +
xlab("Proportion of hits to hypothetical") +
scale_y_continuous(labels = scales::percent, limits = c(0,0.80))
hits_hypo$prop %>% summary
hits_hypo_75_99$prop %>% summary
hits_hypo_50_75$prop %>% summary
hits_hypo_lt50$prop %>% summary
hits_hypo$prop %>% length()
hits_hypo_75_99$prop %>% length()
hits_hypo_50_75$prop %>% length()
hits_hypo_lt50$prop %>% length()
unk_vs_rs82_1e25 %>%
ungroup %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
select(V2.x, V15) %>%
group_by(V2.x, V15) %>% unique %>%
ungroup() %>%
group_by(V2.x) %>%
count %>%
gghistogram(x="n", bins = nclass.Sturges(hits_hypo_1$n), fill = "#3A3A3A") +
scale_y_sqrt(labels = scales::comma, breaks = scales::trans_breaks("sqrt", function(x) x^2)) +
scale_x_sqrt(labels = scales::comma, breaks = scales::trans_breaks("sqrt", function(x) x^2)) +
theme_light() +
ylab("Number of clusters") +
xlab("Number of genomes")
l<-unk_vs_rs82_1e25 %>%
ungroup %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
select(V2.x, V15) %>%
group_by(V2.x, V15) %>% unique %>%
ungroup() %>%
group_by(V2.x) %>%
count
l1<-l %>% ungroup() %>% top_n(100, wt = n)
l_phy<-unk_vs_rs82_1e25 %>%
ungroup %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
select(V2.x, V3.y) %>%
group_by(V2.x, V3.y) %>% unique %>%
ungroup() %>%
group_by(V2.x) %>%
count
l_phy %>%
gghistogram(x="n", bins = nclass.Sturges(hits_hypo_1$n), fill = "#3A3A3A") +
theme_light() +
ylab("Number of clusters") +
xlab("Number of genomes")
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_1$V2.x) %>%
group_by(V2.x) %>% count() %>% .$n %>% hist
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
group_by(V15) %>% count() %>% .$n %>% hist
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
group_by(V2.y) %>%
count() %>%
mutate(V3.y = fct_reorder(V3.y, n)) %>%
ggplot(aes(V2.y, n)) +
geom_bar(stat = "identity") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
l2 <- unk_vs_rs82_1e25 %>%
#filter(V2.x %in% l1$V2.x) %>%
select(V2.x, V3.y) %>%
group_by(V3.y) %>%
unique %>%
filter(!is.na(V3.y)) %>%
count()
l2$V3.y <- factor(l2$V3.y , levels = l2 %>% arrange((n)) %>% .$V3.y)
l2%>%
ggplot(aes(V3.y, n)) +
rotate() +
geom_bar(stat = "identity") +
theme_light() +
ylab("Hits") +
xlab("Phylum") +
scale_y_continuous(labels = scales::comma)
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
filter(V3.y == "Actinobacteria") %>%
select(V2.x, V4.y) %>%
unique %>%
group_by(V4.y) %>% count() %>%
ggplot(aes(V4.y, n)) +
geom_bar(stat = "identity") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
filter(V3.y == "Bacteroidetes") %>%
select(V2.x, V4.y) %>%
unique %>%
group_by(V4.y) %>% count() %>%
ggplot(aes(V4.y, n)) +
geom_bar(stat = "identity") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
filter(V3.y == "Firmicutes") %>%
select(V2.x, V4.y) %>%
unique %>%
group_by(V4.y) %>% count() %>%
ggplot(aes(V4.y, n)) +
geom_bar(stat = "identity") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
unk_vs_rs82_1e25 %>%
filter(V2.x %in% hits_hypo_75_1$V2.x) %>%
filter(V3.y == "Proteobacteria") %>%
select(V2.x, V4.y) %>%
unique %>%
group_by(V4.y) %>% count() %>%
ggplot(aes(V4.y, n)) +
geom_bar(stat = "identity") +
theme_light() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
#!/bin/bash
source ~/opt/scripts/activate_mpi
set -x
TSV="/bioinf/home/afernand/SANDBOX/unk_vs_refseq/all_refseq82_nr_names.tsv"
PROF="/bioinf/home/afernand/SANDBOX/unk_vs_refseq/marine_hmp_db_03112017_gu_hhm_profileDB"
# Get representative
# Get cluster num
scratch=$(mktemp -d -p /scratch/tmp)
function finish {
rm -rf "$scratch"
}
trap finish EXIT
#MD5=$(md5sum <(echo "$SEQS") | awk '{print $1}')
#N=$(LC_ALL=C grep -m 1 "${MD5}" "${TSV}" | cut -f2)
TMP=$(mktemp -d -p ${scratch})
cd $scratch
N=$(basename $1 .faa)
MMSEQS=~/opt/MMseqs2/build/bin/mmseqs
${MMSEQS} createdb $1 ${N}_db
${MMSEQS} search ${PROF} ${N}_db ${N}_results ${TMP} -c 0.8 --cov-mode 0 -e 1e-5 --threads ${NSLOTS}
${MMSEQS} convertalis ${PROF} ${N}_db ${N}_results ${N}_results.m8 --format-mode 2
join -1 2 -2 2 <(~/opt/coreutils/bin/sort -k2,2 ${N}_results.m8) <(LC_ALL=C grep -F $N $TSV | ~/opt/coreutils/bin/sort -k2,2 --parallel=$NSLOTS) > tmp && mv tmp ${N}_results.m8
rm -rf ${TMP} ${N}_db* *index
mv *m8 /bioinf/home/afernand/SANDBOX/unk_vs_refseq/results
#!/bin/bash
set -x
FILE=${1}
PATTERNS=${2}
FOUT=${3}
if [ -f ${FOUT} ]; then
rm ${FOUT}
fi
LC_ALL=C rg -j 4 -i -f ${PATTERNS} ${FILE} | awk '{print $0"\thypo"}' > ${FOUT}
LC_ALL=C rg -j 4 -v -i -f ${PATTERNS} ${FILE} | awk '{print $0"\tchar"}' >> ${FOUT}
#!/bin/bash
#$ -S /bin/bash
#$ -j y
#$ -pe threaded 4
#$ -cwd
#$ -R y
#$ -N gu_vs_r82
#$ -cwd
#$ -P megx.p
#$ -t 1-10604
G=$(awk -vT=$SGE_TASK_ID "NR==T" /bioinf/home/afernand/SANDBOX/unk_vs_refseq/genomes_list.txt)
/bioinf/home/afernand/SANDBOX/unk_vs_refseq/mmseqs_gu.sh $G
We will screen the RefSeq genomes for genoimc unknowns. We will use the non-redundant set of genomes identified by MASH+t-SNE+PAM clustering.
cd /bioinf/home/afernand/SANDBOX/unk_vs_refseq/
mkdir genomes
rsync -Pauvz /bioinf/projects/megx/UNKNOWNS/chiara/NETWORK/RefSeq82.ref.gen/proteomes/downloads/ genomes/
find genomes/ -name '*gz' \
| while read file; do NAM=$(basename $file _protein.faa.gz); zcat $file \
| mawk -vL=$NAM '$0 ~/^>/{gsub(">", "", $0); print L"\t"$0}'; done >> all_refseq82_nr_names.tsv
And rename the headers:
mkdir genomes_renamed
cd genomes_renamed
parallel -j 252 --progress ../rename_headers.sh ::: /bioinf/home/afernand/SANDBOX/unk_vs_refseq/genomes/*faa
cd ..
find genomes_renamed/ -name '*.faa' \
| while read line; do printf "/bioinf/home/afernand/SANDBOX/unk_vs_refseq/genomes_renamed/$line\n"; done > genomes_list.txt
find genomes/ -name '*gz' \
| while read file; do NAM=$(basename $file _protein.faa.gz); zcat $file | mawk -vL=$NAM '$0 ~/^>/{gsub(">", "", $0); print L"\t"$0}'; done >> all_refseq82_nr_names.tsv
We need the ffindex files with the HHM profiles, and convert them to MMSEQS2 format. First we copy the HHM profiles to scratch and we convert them:
mkdir /scratch/antonio/mmseqs2_profiles
cd /scratch/antonio/mmseqs2_profiles
cp /bioinf/projects/megx/UNKNOWNS/2017_11/classification/results/ffindex_data/marine_hmp_db_03112017_gu_hhm.ffdata marine_hmp_db_03112017_gu_hhm
cp /bioinf/projects/megx/UNKNOWNS/2017_11/classification/results/ffindex_data/marine_hmp_db_03112017_gu_hhm.ffindex marine_hmp_db_03112017_gu_hhm.index
~/opt/MMseqs2_uv/build/bin/mmseqs convertprofiledb marine_hmp_db_03112017_gu_hhm marine_hmp_db_03112017_gu_hhm_profileDB --threads 16
Once we have them converted we move them to the shared file system, we will use start the jobs in the clusters. One job per genome.
mv *profile* /bioinf/home/afernand/SANDBOX/unk_vs_refseq/
cd /bioinf/home/afernand/SANDBOX/unk_vs_refseq/
rm -rf /scratch/antonio/mmseqs2_profiles
We might need to redo the symlinks to the seq_h files
rm marine_hmp_db_03112017_gu_hhm_profileDB_seq_h
ln -s /bioinf/home/afernand/SANDBOX/unk_vs_refseq/marine_hmp_db_03112017_gu_hhm_profileDB_h marine_hmp_db_03112017_gu_hhm_profileDB_seq_h
ln -s /bioinf/home/afernand/SANDBOX/unk_vs_refseq/marine_hmp_db_03112017_gu_hhm_profileDB_h.index marine_hmp_db_03112017_gu_hhm_profileDB_seq_h.index
We will start an array in the cluster to process each genome independently
mkdir /bioinf/home/afernand/SANDBOX/unk_vs_refseq/results
qsub gu_vs_refseq_sge.sh
Needs to be in any of the machines with access to the cluster (sunrays, linux-desktop, arb-servers)
Once the search is done we will combine results
parallel -j 252 --progress cat {} > gu_vs_refseq82.tsv ::: results/*m8
cut -f 16- -d " " gu_vs_refseq82.tsv > tmp
paste <(cat gu_vs_refseq82.tsv | cut -f 1-15 -d " " | tr " " $'\t') tmp > gu_vs_refseq82_tab.tsv
and parse the hypotheticals and get the taxonomies:
bash ~/opt/scripts/hypo_parse.sh gu_vs_refseq82_tab.tsv ~/opt/scripts/unknown_grep.tsv gu_vs_refseq82_hypo.tsv
cp /bioinf/projects/megx/UNKNOWNS/chiara/NETWORK/RefSeq82.ref.gen/genomes_taxonomy.tsv.gz .
For plotting use the script here