RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab.
Developed by: Alexey M. Kozlov and Alexandros Stamatakis.
Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth.
Latest version: https://github.com/amkozlov/raxml-ng
Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml

System: Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 40 cores, 376 GB RAM

RAxML-NG was called at 04-Jul-2021 14:30:02 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/2_msa/P49675_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675 --seed 2 --threads 5 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (5 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/2_msa/P49675_trimmed_msa.fasta
[00:00:00] Loaded alignment with 278 taxa and 230 sites

WARNING: Sequences tr_B4QC20_B4QC20_DROSI_7240 and tr_B4IH40_B4IH40_DROSE_7238 are exactly identical!
WARNING: Sequences tr_G1RNP1_G1RNP1_NOMLE_61853 and tr_H2QW13_H2QW13_PANTR_9598 are exactly identical!
WARNING: Sequences tr_B5E1A0_B5E1A0_DROPS_46245 and tr_B4H561_B4H561_DROPE_7234 are exactly identical!
WARNING: Sequences tr_A0A2I3RBR4_A0A2I3RBR4_PANTR_9598 and tr_A0A2R9CKM8_A0A2R9CKM8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5QKZ9_A0A1D5QKZ9_MACMU_9544 and tr_A0A1D5RFI5_A0A1D5RFI5_MACMU_9544 are exactly identical!
WARNING: Sequences tr_F7GCG0_F7GCG0_MACMU_9544 and tr_A0A096N0P1_A0A096N0P1_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7GCG0_F7GCG0_MACMU_9544 and tr_A0A2K5KHP4_A0A2K5KHP4_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7GCG0_F7GCG0_MACMU_9544 and tr_A0A2K5YM32_A0A2K5YM32_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A1U7Q874_A0A1U7Q874_MESAU_10036 and sp_P70114_STAR_MESAU_10036 are exactly identical!
WARNING: Sequences tr_A0A226N5D6_A0A226N5D6_CALSU_9009 and tr_A0A226P5F6_A0A226P5F6_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2K5M495_A0A2K5M495_CERAT_9531 and tr_A0A2K5YLI4_A0A2K5YLI4_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 11

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.reduced.phy

Alignment comprises 1 partitions and 230 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 230 / 230
Gaps: 3.85 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.rba

Parallelization scheme autoconfig: 5 worker(s) x 1 thread(s)

Parallel reduction/worker buffer size: 1 KB  / 0 KB

[00:00:00] Generating 20 random starting tree(s) with 278 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 230 / 18400
[00:00:00] Data distribution: max. searches per worker: 4

Starting ML tree search with 20 distinct starting trees

[00:00:00 -105147.908036] Initial branch length optimization
[00:00:00 -83338.527365] Model parameter optimization (eps = 10.000000)
[00:00:17 -83038.182052] AUTODETECT spr round 1 (radius: 5)
[00:00:35 -51576.084438] AUTODETECT spr round 2 (radius: 10)
[00:00:58 -39105.046235] AUTODETECT spr round 3 (radius: 15)
[00:01:25 -36457.743874] AUTODETECT spr round 4 (radius: 20)
[00:02:00 -34488.740714] AUTODETECT spr round 5 (radius: 25)
[00:02:44 -34348.255397] SPR radius for FAST iterations: 25 (autodetect)
[00:02:44 -34348.255397] Model parameter optimization (eps = 3.000000)
[00:02:55 -34281.559158] FAST spr round 1 (radius: 25)
[00:03:23 -30661.524447] FAST spr round 2 (radius: 25)
[00:03:47 -30556.817174] FAST spr round 3 (radius: 25)
[00:04:06 -30544.305100] FAST spr round 4 (radius: 25)
[00:04:22 -30542.734405] FAST spr round 5 (radius: 25)
[00:04:38 -30542.734392] Model parameter optimization (eps = 1.000000)
[00:04:46 -30540.275470] SLOW spr round 1 (radius: 5)
[00:05:20 -30529.256081] SLOW spr round 2 (radius: 5)
[00:05:50 -30528.917867] SLOW spr round 3 (radius: 5)
[00:06:17 -30528.898780] SLOW spr round 4 (radius: 10)
[00:06:42 -30528.831659] SLOW spr round 5 (radius: 15)
[00:07:20 -30528.830618] SLOW spr round 6 (radius: 20)
[00:08:06 -30528.830481] SLOW spr round 7 (radius: 25)
[00:08:08] [worker #1] ML tree search #2, logLikelihood: -30520.216827
[00:08:23] [worker #3] ML tree search #4, logLikelihood: -30537.601048
[00:08:44] [worker #4] ML tree search #5, logLikelihood: -30517.539897
[00:08:57 -30528.830399] Model parameter optimization (eps = 0.100000)

[00:09:01] [worker #0] ML tree search #1, logLikelihood: -30528.517182

[00:09:01 -108301.170706] Initial branch length optimization
[00:09:02 -84798.428203] Model parameter optimization (eps = 10.000000)
[00:09:09] [worker #2] ML tree search #3, logLikelihood: -30519.169064
[00:09:14 -84453.944332] AUTODETECT spr round 1 (radius: 5)
[00:09:32 -51503.588184] AUTODETECT spr round 2 (radius: 10)
[00:09:57 -40262.662539] AUTODETECT spr round 3 (radius: 15)
[00:10:26 -35267.815387] AUTODETECT spr round 4 (radius: 20)
[00:10:58 -34950.640191] AUTODETECT spr round 5 (radius: 25)
[00:11:29 -34764.069398] SPR radius for FAST iterations: 25 (autodetect)
[00:11:29 -34764.069398] Model parameter optimization (eps = 3.000000)
[00:11:41 -34711.749512] FAST spr round 1 (radius: 25)
[00:12:05 -30890.193770] FAST spr round 2 (radius: 25)
[00:12:27 -30550.534956] FAST spr round 3 (radius: 25)
[00:12:45 -30533.861556] FAST spr round 4 (radius: 25)
[00:13:01 -30532.200669] FAST spr round 5 (radius: 25)
[00:13:16 -30532.196506] Model parameter optimization (eps = 1.000000)
[00:13:20 -30531.388412] SLOW spr round 1 (radius: 5)
[00:13:49 -30524.877730] SLOW spr round 2 (radius: 5)
[00:14:17 -30524.237941] SLOW spr round 3 (radius: 5)
[00:14:44 -30524.236823] SLOW spr round 4 (radius: 10)
[00:15:10 -30524.148841] SLOW spr round 5 (radius: 15)
[00:15:47 -30522.078808] SLOW spr round 6 (radius: 5)
[00:16:16] [worker #1] ML tree search #7, logLikelihood: -30514.365124
[00:16:26 -30517.928985] SLOW spr round 7 (radius: 5)
[00:16:57 -30516.990491] SLOW spr round 8 (radius: 5)
[00:17:26 -30516.988623] SLOW spr round 9 (radius: 10)
[00:17:52 -30516.988225] SLOW spr round 10 (radius: 15)
[00:18:10] [worker #4] ML tree search #10, logLikelihood: -30508.379719
[00:18:11] [worker #3] ML tree search #9, logLikelihood: -30513.774334
[00:18:27 -30516.988112] SLOW spr round 11 (radius: 20)
[00:19:11 -30516.988067] SLOW spr round 12 (radius: 25)
[00:19:54] [worker #2] ML tree search #8, logLikelihood: -30525.542770
[00:19:58 -30516.988043] Model parameter optimization (eps = 0.100000)

[00:20:01] [worker #0] ML tree search #6, logLikelihood: -30516.921698

[00:20:01 -108630.753414] Initial branch length optimization
[00:20:02 -85649.479671] Model parameter optimization (eps = 10.000000)
[00:20:18 -85258.060930] AUTODETECT spr round 1 (radius: 5)
[00:20:36 -54166.913493] AUTODETECT spr round 2 (radius: 10)
[00:21:01 -40916.868992] AUTODETECT spr round 3 (radius: 15)
[00:21:29 -34523.369193] AUTODETECT spr round 4 (radius: 20)
[00:22:04 -33623.931631] AUTODETECT spr round 5 (radius: 25)
[00:22:39 -33622.399695] SPR radius for FAST iterations: 25 (autodetect)
[00:22:39 -33622.399695] Model parameter optimization (eps = 3.000000)
[00:22:50 -33559.700450] FAST spr round 1 (radius: 25)
[00:23:15 -31080.848646] FAST spr round 2 (radius: 25)
[00:23:34 -30560.400928] FAST spr round 3 (radius: 25)
[00:23:51 -30540.482408] FAST spr round 4 (radius: 25)
[00:24:06 -30538.276304] FAST spr round 5 (radius: 25)
[00:24:21 -30533.742638] FAST spr round 6 (radius: 25)
[00:24:35 -30533.742571] Model parameter optimization (eps = 1.000000)
[00:24:42 -30531.497325] SLOW spr round 1 (radius: 5)
[00:25:11 -30525.895023] SLOW spr round 2 (radius: 5)
[00:25:40 -30523.040301] SLOW spr round 3 (radius: 5)
[00:25:54] [worker #3] ML tree search #14, logLikelihood: -30514.108228
[00:26:08 -30522.972568] SLOW spr round 4 (radius: 10)
[00:26:12] [worker #4] ML tree search #15, logLikelihood: -30520.970933
[00:26:33 -30522.972568] SLOW spr round 5 (radius: 15)
[00:27:03] [worker #1] ML tree search #12, logLikelihood: -30506.754113
[00:27:13 -30522.972568] SLOW spr round 6 (radius: 20)
[00:28:02 -30522.972568] SLOW spr round 7 (radius: 25)
[00:28:09] [worker #2] ML tree search #13, logLikelihood: -30513.010059
[00:28:55 -30522.972568] Model parameter optimization (eps = 0.100000)

[00:29:00] [worker #0] ML tree search #11, logLikelihood: -30522.900509

[00:29:00 -106947.283195] Initial branch length optimization
[00:29:01 -84698.154532] Model parameter optimization (eps = 10.000000)
[00:29:15 -84375.394598] AUTODETECT spr round 1 (radius: 5)
[00:29:33 -54433.553505] AUTODETECT spr round 2 (radius: 10)
[00:29:58 -39617.530628] AUTODETECT spr round 3 (radius: 15)
[00:30:27 -34833.073058] AUTODETECT spr round 4 (radius: 20)
[00:31:01 -34259.477427] AUTODETECT spr round 5 (radius: 25)
[00:31:32 -34235.715959] SPR radius for FAST iterations: 25 (autodetect)
[00:31:32 -34235.715959] Model parameter optimization (eps = 3.000000)
[00:31:42 -34196.106197] FAST spr round 1 (radius: 25)
[00:32:08 -30684.485967] FAST spr round 2 (radius: 25)
[00:32:30 -30558.404826] FAST spr round 3 (radius: 25)
[00:32:50 -30529.388279] FAST spr round 4 (radius: 25)
[00:33:06 -30528.186270] FAST spr round 5 (radius: 25)
[00:33:20 -30528.185869] Model parameter optimization (eps = 1.000000)
[00:33:33 -30523.124319] SLOW spr round 1 (radius: 5)
[00:34:05 -30515.377256] SLOW spr round 2 (radius: 5)
[00:34:32 -30515.307089] SLOW spr round 3 (radius: 10)
[00:34:45] [worker #4] ML tree search #20, logLikelihood: -30516.607942
[00:34:58 -30514.462571] SLOW spr round 4 (radius: 5)
[00:35:16] [worker #3] ML tree search #19, logLikelihood: -30508.871607
[00:35:33 -30514.462565] SLOW spr round 5 (radius: 10)
[00:36:04 -30514.462565] SLOW spr round 6 (radius: 15)
[00:36:39 -30514.462565] SLOW spr round 7 (radius: 20)
[00:36:39] [worker #1] ML tree search #17, logLikelihood: -30506.641566
[00:37:29 -30514.462565] SLOW spr round 8 (radius: 25)
[00:38:16 -30514.462565] Model parameter optimization (eps = 0.100000)

[00:38:21] [worker #0] ML tree search #16, logLikelihood: -30514.361864

[00:41:33] [worker #2] ML tree search #18, logLikelihood: -30507.665254

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.155354,0.636935) (0.229650,0.517988) (0.408971,0.963152) (0.206025,1.884201) 
   Base frequencies (model): 
M0: 0.147383 0.017579 0.058208 0.017707 0.026331 0.041582 0.017494 0.027859 0.011849 0.076971 0.147823 0.019535 0.037132 0.029940 0.008059 0.088179 0.089653 0.006477 0.032308 0.097931 
M1: 0.063139 0.066357 0.011586 0.066571 0.010800 0.009276 0.053984 0.146986 0.034214 0.088822 0.098196 0.032390 0.021263 0.072697 0.016761 0.020711 0.020797 0.025463 0.045615 0.094372 
M2: 0.062457 0.066826 0.049332 0.065270 0.006513 0.041231 0.058965 0.080852 0.028024 0.037024 0.075925 0.064131 0.019620 0.028710 0.104579 0.056388 0.062027 0.008241 0.033124 0.050760 
M3: 0.106471 0.074171 0.044513 0.096390 0.002148 0.066733 0.158908 0.037625 0.020691 0.014608 0.028797 0.105352 0.007864 0.007477 0.083595 0.055726 0.047711 0.003975 0.010088 0.027159 
   Substitution rates (model): 
M 0: 0.295719 0.067388 0.253712 1.029289 0.107964 0.514644 10.868848 0.380498 0.084223 0.086976 0.188789 0.286389 0.155567 1.671061 2.132922 0.529591 0.115551 0.102453 0.916683 0.448317 0.457483 0.576016 1.741924 0.736017 0.704334 5.658311 0.123387 0.221777 93.433377 0.382175 0.235965 6.535048 0.525521 0.303537 0.641259 0.289466 0.102065 2.358429 0.251987 0.216561 0.503084 0.435271 4.873453 0.090748 0.033310 0.746537 0.128905 0.127321 0.904011 0.939733 0.435450 0.046646 0.262076 0.043986 0.189008 0.599450 109.901504 1.070052 5.229858 0.052764 0.021407 0.621146 0.081091 0.205164 5.164456 0.747330 0.308078 0.260889 0.185083 0.080708 0.029955 0.084794 1.862626 0.553477 0.151733 0.230320 0.096955 0.352526 0.590018 0.386853 1.559564 0.606648 0.587531 0.592318 0.885230 4.117654 0.246260 6.508329 0.054187 0.195703 1.669092 0.810168 0.066081 2.437439 0.165666 0.106333 0.093417 0.035149 0.072549 1.202023 1.634845 0.060194 0.069359 2.448827 0.232297 0.064822 3.537387 0.435384 0.290413 0.280695 0.105999 0.206603 0.404968 0.048984 0.069963 0.256662 0.228519 0.241077 4.320442 3.656545 0.290216 0.307466 0.096556 0.306067 0.204296 0.504221 1.991533 0.655465 6.799829 11.291065 0.961142 0.448965 6.227274 20.304886 0.205944 1.495537 0.091940 1.994320 0.754940 0.170343 0.050315 0.372166 0.206332 0.097050 5.381403 0.122332 3.256485 2.261319 0.848067 0.064441 0.102493 0.459041 0.133091 0.561215 0.457430 0.163849 5.260446 0.360946 0.389413 0.033291 0.115301 0.112593 1.559944 0.426508 0.132547 0.498634 0.559069 0.264728 0.693307 0.438856 0.306683 0.109129 18.392863 66.647302 0.400021 4.586081 2.099355 0.411347 0.476350 0.584622 3.634276 0.101797 0.148995 0.089177 0.034710 0.063603 0.755865 20.561407 0.133790 0.154902 
M 1: 0.066142 0.590377 0.069930 9.850951 1.101363 0.150375 0.568586 0.051668 0.127170 0.292429 0.071458 1.218562 0.075144 7.169085 30.139501 13.461692 0.021372 0.045779 4.270235 0.468325 0.013688 0.302287 1.353957 0.028386 0.037750 0.262130 0.016923 0.064289 0.855973 0.079621 0.011169 0.161937 0.276530 0.161053 0.081472 0.036742 0.030342 2.851667 3.932151 8.159169 0.219934 0.421974 2.468752 0.344765 0.210724 1.172204 0.763553 0.082464 0.726566 11.149790 4.782635 0.058046 0.498072 0.258487 0.146882 0.249672 0.560142 0.046719 0.106259 0.003656 0.004200 0.014189 0.009876 0.002656 0.040244 0.267322 0.053740 0.006597 0.027639 0.012745 0.582670 0.005035 0.275844 0.098208 0.445038 1.217010 0.033969 1.988516 0.681161 0.825960 18.762977 11.949233 0.286794 0.534219 4.336817 3.054085 0.129551 4.210126 0.165753 1.088704 1.889645 3.344809 0.111063 2.067758 3.547017 2.466507 0.188236 0.203493 0.281953 0.037250 0.029788 0.008541 0.014768 0.125869 0.056702 0.004186 0.110993 0.201148 0.139705 0.009201 0.012095 0.043812 0.013513 0.002533 0.005848 0.031390 0.021612 0.004854 0.129497 0.976631 0.053397 0.019475 0.004964 0.015539 0.031779 0.064558 0.065585 0.079927 0.095591 0.196886 0.408834 0.126088 0.037226 0.452302 0.016212 7.278994 0.029917 7.918203 0.450964 0.169797 0.104288 1.578530 0.015909 0.094365 16.179952 0.042762 14.799537 1.506485 0.637893 0.123793 0.641351 0.154810 0.140750 3.416059 0.259400 0.009457 0.090576 0.292108 0.297913 0.017172 0.021976 0.032578 1.375871 0.457399 0.598048 4.418398 0.239749 0.168432 2.950318 0.143327 0.328689 0.125011 0.562720 1.414883 0.227807 3.478333 2.984862 0.061299 0.077470 1.050562 13.974326 0.154326 0.224675 0.112000 0.060703 0.123480 5.294490 0.447011 0.033381 0.045528 
M 2: 0.733336 0.558955 0.503360 4.149599 1.415369 1.367574 1.263002 0.994098 0.517204 0.775054 0.763094 1.890137 0.540460 0.200122 4.972745 1.825593 0.450842 0.526135 3.839269 0.597671 0.058964 2.863355 2.872594 0.258365 0.366868 2.578946 0.358350 0.672023 5.349861 0.691594 0.063347 0.032875 0.821562 0.580847 0.661866 0.265730 0.395134 5.581680 1.279881 1.335650 0.397108 1.840061 5.739035 0.284730 0.109781 1.612642 0.466979 0.141582 0.019509 4.670980 1.967383 0.088064 0.581928 0.145401 0.225860 0.434096 2.292917 1.024707 0.821921 0.027824 0.021443 0.088850 0.060820 0.018288 0.042687 1.199607 0.420710 0.037642 0.141233 0.090101 1.043232 0.209978 0.823594 3.039380 1.463390 1.983693 0.397640 2.831098 4.102068 0.059723 5.901348 2.034980 2.600668 5.413080 4.193725 4.534772 0.377181 4.877840 0.370939 1.298542 3.509873 2.646440 0.087872 0.072299 1.139018 0.864479 0.390688 0.322761 0.625409 0.496780 0.532488 0.232460 0.169219 0.755219 0.379926 0.020447 0.023282 0.503875 0.577513 0.109318 0.153776 0.696533 0.398817 0.008940 0.043707 0.436013 0.087640 0.064863 0.036426 1.673207 0.124068 0.218118 0.039217 0.104335 0.349195 0.838324 0.888693 0.488389 1.385133 0.050226 0.962470 0.502294 1.065585 8.351808 0.377304 5.102837 0.561690 7.010411 3.054968 0.039318 0.204155 2.653232 0.564368 0.854294 15.559906 0.401070 8.929538 5.525874 0.067505 0.273372 0.437116 1.927515 0.940458 2.508169 1.357738 0.043394 0.023126 0.567639 1.048288 0.120994 0.180650 0.449074 3.135353 0.012695 0.570771 2.319555 1.856122 0.975427 3.404087 0.015631 0.458799 0.151684 4.154750 11.429924 1.457957 0.233109 0.077004 0.011074 0.026268 0.052132 8.113282 0.377578 0.429221 0.260296 0.222293 0.273138 2.903836 4.731579 0.564762 0.681215 
M 3: 0.658412 0.566269 0.854111 0.884454 1.309554 1.272639 1.874713 0.552007 0.227683 0.581512 0.695190 0.967985 0.344015 0.978992 3.427163 2.333253 0.154701 0.221089 2.088785 0.540749 0.058015 5.851132 2.294145 0.182966 0.684164 3.192521 0.528161 1.128882 3.010922 1.012866 0.227296 0.156635 0.878405 0.802754 0.830884 0.431617 0.456530 3.060574 1.279257 1.438430 0.431464 2.075952 4.840271 0.644656 0.266076 2.084975 0.720060 0.291854 0.028961 4.071574 2.258357 0.073037 1.238426 0.199728 0.160296 0.482619 2.992763 1.296206 0.841829 0.031467 0.048542 0.132774 0.133055 0.056045 0.209188 0.925172 0.360522 0.094591 0.313945 0.118104 0.992259 0.086318 2.149634 5.103188 3.775817 3.954021 0.190734 1.776095 4.495841 0.264277 7.063879 2.221150 3.017954 8.558815 4.310199 2.130054 0.571406 4.137385 0.437589 2.071689 2.498630 1.763546 0.116381 0.296578 1.033710 1.283423 0.312579 0.305772 0.681277 0.507160 0.351381 0.189152 0.217780 0.767361 0.278392 0.092075 0.177263 0.451893 0.653836 0.074620 0.181992 0.752277 0.679853 0.025780 0.082005 0.326441 0.343977 0.195877 0.217424 3.057583 0.377558 0.401252 0.072258 0.241015 0.665865 1.266791 0.680174 0.717301 4.001286 0.362942 1.189259 0.964545 1.350568 12.869737 0.531100 8.904999 0.652629 10.091413 2.671718 0.086367 0.359932 4.797423 0.336801 1.021885 23.029406 0.440178 14.013035 5.069337 0.539010 0.742569 0.780580 1.331875 1.531589 4.414850 1.082703 0.091278 0.172734 0.693405 1.422571 0.068958 0.163829 0.481711 4.643214 0.121821 0.584083 4.216178 1.677263 1.575754 5.046403 0.161015 1.531223 0.599244 5.832025 33.873091 1.914768 1.287474 0.444362 0.076328 0.079916 0.466823 5.231362 0.548763 0.831890 0.382271 0.208791 0.307846 3.717971 5.910440 0.282540 0.964421 


Final LogLikelihood: -30506.641566

AIC score: 62131.283133 / AICc score: 688211.283133 / BIC score: 64053.169467
Free parameters (model + branch lengths): 559

WARNING: Number of free parameters (K=559) is larger than alignment size (n=230).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P49675/3_mltree/P49675.raxml.log

Analysis started: 04-Jul-2021 14:30:02 / finished: 04-Jul-2021 15:11:36

Elapsed time: 2493.968 seconds

Consumed energy: 228.421 Wh (= 1 km in an electric car, or 6 km with an e-scooter!)