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 07-Jul-2021 00:37:26 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/2_msa/Q96R54_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54 --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/Q96R54/2_msa/Q96R54_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 301 sites

WARNING: Sequences tr_J9NSK9_J9NSK9_CANLF_9615 and sp_Q95154_OLF1_CANLF_9615 are exactly identical!
WARNING: Duplicate sequences found: 1

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/Q96R54/3_mltree/Q96R54.raxml.reduced.phy

Alignment comprises 1 partitions and 301 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 301 / 301
Gaps: 0.68 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.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 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 301 / 24080
[00:00:00] Data distribution: max. searches per worker: 4

Starting ML tree search with 20 distinct starting trees

[00:00:00 -493666.999164] Initial branch length optimization
[00:00:06 -429869.704019] Model parameter optimization (eps = 10.000000)
[00:01:17 -424546.976312] AUTODETECT spr round 1 (radius: 5)
[00:04:42 -335025.564867] AUTODETECT spr round 2 (radius: 10)
[00:08:40 -246479.009956] AUTODETECT spr round 3 (radius: 15)
[00:12:47 -210435.553285] AUTODETECT spr round 4 (radius: 20)
[00:18:36 -202718.090188] AUTODETECT spr round 5 (radius: 25)
[00:26:09 -200316.309142] SPR radius for FAST iterations: 25 (autodetect)
[00:26:09 -200316.309142] Model parameter optimization (eps = 3.000000)
[00:26:49 -200036.253516] FAST spr round 1 (radius: 25)
[00:31:20 -181323.993450] FAST spr round 2 (radius: 25)
[00:34:37 -180505.061674] FAST spr round 3 (radius: 25)
[00:37:34 -180435.270201] FAST spr round 4 (radius: 25)
[00:40:14 -180426.027918] FAST spr round 5 (radius: 25)
[00:42:53 -180416.947878] FAST spr round 6 (radius: 25)
[00:45:18 -180414.726740] FAST spr round 7 (radius: 25)
[00:47:40 -180411.226388] FAST spr round 8 (radius: 25)
[00:50:00 -180410.722541] FAST spr round 9 (radius: 25)
[00:52:20 -180410.237612] FAST spr round 10 (radius: 25)
[00:54:40 -180409.693493] FAST spr round 11 (radius: 25)
[00:57:00 -180409.537449] FAST spr round 12 (radius: 25)
[00:59:19 -180408.976338] FAST spr round 13 (radius: 25)
[01:01:40 -180408.832197] FAST spr round 14 (radius: 25)
[01:04:02 -180407.996076] FAST spr round 15 (radius: 25)
[01:06:25 -180407.194594] FAST spr round 16 (radius: 25)
[01:08:50 -180396.519603] FAST spr round 17 (radius: 25)
[01:11:12 -180395.966205] FAST spr round 18 (radius: 25)
[01:13:34 -180395.799708] FAST spr round 19 (radius: 25)
[01:15:56 -180395.336503] FAST spr round 20 (radius: 25)
[01:18:18 -180395.060030] FAST spr round 21 (radius: 25)
[01:20:40 -180393.016398] FAST spr round 22 (radius: 25)
[01:23:02 -180389.667638] FAST spr round 23 (radius: 25)
[01:25:34 -180381.978249] FAST spr round 24 (radius: 25)
[01:28:06 -180376.262070] FAST spr round 25 (radius: 25)
[01:30:27 -180376.153053] FAST spr round 26 (radius: 25)
[01:32:49 -180376.152854] Model parameter optimization (eps = 1.000000)
[01:32:56 -180376.039658] SLOW spr round 1 (radius: 5)
[01:36:30 -180342.280780] SLOW spr round 2 (radius: 5)
[01:39:51 -180337.871085] SLOW spr round 3 (radius: 5)
[01:43:02 -180337.087092] SLOW spr round 4 (radius: 5)
[01:46:11 -180336.679289] SLOW spr round 5 (radius: 5)
[01:49:21 -180334.812473] SLOW spr round 6 (radius: 5)
[01:52:29 -180334.776009] SLOW spr round 7 (radius: 10)
[01:55:52 -180333.176667] SLOW spr round 8 (radius: 5)
[01:59:46 -180331.872835] SLOW spr round 9 (radius: 5)
[02:03:16 -180327.670001] SLOW spr round 10 (radius: 5)
[02:06:30 -180327.410085] SLOW spr round 11 (radius: 5)
[02:09:38 -180327.410080] SLOW spr round 12 (radius: 10)
[02:13:01 -180327.410080] SLOW spr round 13 (radius: 15)
[02:19:42 -180325.713245] SLOW spr round 14 (radius: 5)
[02:23:50 -180325.589461] SLOW spr round 15 (radius: 5)
[02:27:21 -180325.589450] SLOW spr round 16 (radius: 10)
[02:30:45] [worker #3] ML tree search #4, logLikelihood: -180196.737927
[02:30:59 -180325.589450] SLOW spr round 17 (radius: 15)
[02:37:28 -180325.589450] SLOW spr round 18 (radius: 20)
[02:48:57 -180324.820354] SLOW spr round 19 (radius: 5)
[02:53:16 -180323.652936] SLOW spr round 20 (radius: 5)
[02:54:35] [worker #1] ML tree search #2, logLikelihood: -180161.939381
[02:56:50 -180323.652933] SLOW spr round 21 (radius: 10)
[03:00:33 -180319.597160] SLOW spr round 22 (radius: 5)
[03:04:19 -180313.628183] SLOW spr round 23 (radius: 5)
[03:07:41 -180313.628180] SLOW spr round 24 (radius: 10)
[03:11:11 -180313.628180] SLOW spr round 25 (radius: 15)
[03:17:46 -180313.628180] SLOW spr round 26 (radius: 20)
[03:29:06 -180313.628180] SLOW spr round 27 (radius: 25)
[03:36:38] [worker #4] ML tree search #5, logLikelihood: -180259.432507
[03:42:43 -180313.628180] Model parameter optimization (eps = 0.100000)

[03:42:57] [worker #0] ML tree search #1, logLikelihood: -180296.079178

[03:42:57 -493482.150456] Initial branch length optimization
[03:43:02 -429599.990662] Model parameter optimization (eps = 10.000000)
[03:44:22 -423826.819175] AUTODETECT spr round 1 (radius: 5)
[03:47:54 -336298.062158] AUTODETECT spr round 2 (radius: 10)
[03:52:06 -255169.845373] AUTODETECT spr round 3 (radius: 15)
[03:57:17 -214229.911935] AUTODETECT spr round 4 (radius: 20)
[04:03:27 -205271.360052] AUTODETECT spr round 5 (radius: 25)
[04:11:00 -203410.340752] SPR radius for FAST iterations: 25 (autodetect)
[04:11:00 -203410.340752] Model parameter optimization (eps = 3.000000)
[04:11:44 -202513.984499] FAST spr round 1 (radius: 25)
[04:16:33 -181149.462257] FAST spr round 2 (radius: 25)
[04:20:02 -180442.376163] FAST spr round 3 (radius: 25)
[04:23:07 -180382.105958] FAST spr round 4 (radius: 25)
[04:25:35] [worker #2] ML tree search #3, logLikelihood: -180240.034319
[04:25:44 -180378.732140] FAST spr round 5 (radius: 25)
[04:28:14 -180377.414219] FAST spr round 6 (radius: 25)
[04:30:42 -180376.795019] FAST spr round 7 (radius: 25)
[04:33:08 -180376.235478] FAST spr round 8 (radius: 25)
[04:35:33 -180375.606233] FAST spr round 9 (radius: 25)
[04:38:09 -180358.560982] FAST spr round 10 (radius: 25)
[04:40:34 -180357.944127] FAST spr round 11 (radius: 25)
[04:42:59 -180357.451130] FAST spr round 12 (radius: 25)
[04:45:23 -180357.241227] FAST spr round 13 (radius: 25)
[04:47:48 -180357.192193] Model parameter optimization (eps = 1.000000)
[04:48:08 -180330.394302] SLOW spr round 1 (radius: 5)
[04:51:48 -180286.272528] SLOW spr round 2 (radius: 5)
[04:55:14 -180282.332948] SLOW spr round 3 (radius: 5)
[04:58:25 -180282.332947] SLOW spr round 4 (radius: 10)
[05:01:55 -180273.538410] SLOW spr round 5 (radius: 5)
[05:05:50 -180268.862577] SLOW spr round 6 (radius: 5)
[05:07:43] [worker #1] ML tree search #7, logLikelihood: -180185.817003
[05:09:12 -180268.862543] SLOW spr round 7 (radius: 10)
[05:12:44 -180266.271107] SLOW spr round 8 (radius: 5)
[05:16:39 -180261.327540] SLOW spr round 9 (radius: 5)
[05:20:05 -180260.053867] SLOW spr round 10 (radius: 5)
[05:23:18 -180260.053867] SLOW spr round 11 (radius: 10)
[05:25:39] [worker #3] ML tree search #9, logLikelihood: -180298.747425
[05:26:47 -180255.972362] SLOW spr round 12 (radius: 5)
[05:30:36 -180255.972352] SLOW spr round 13 (radius: 10)
[05:34:27 -180255.972352] SLOW spr round 14 (radius: 15)
[05:40:29 -180255.972352] SLOW spr round 15 (radius: 20)
[05:51:36 -180250.275107] SLOW spr round 16 (radius: 5)
[05:55:54 -180248.719657] SLOW spr round 17 (radius: 5)
[05:59:33 -180246.445397] SLOW spr round 18 (radius: 5)
[06:02:53 -180244.838307] SLOW spr round 19 (radius: 5)
[06:06:05 -180244.838305] SLOW spr round 20 (radius: 10)
[06:09:33 -180244.493720] SLOW spr round 21 (radius: 5)
[06:13:23 -180244.362185] SLOW spr round 22 (radius: 5)
[06:16:48 -180244.362184] SLOW spr round 23 (radius: 10)
[06:20:23 -180244.362184] SLOW spr round 24 (radius: 15)
[06:21:28] [worker #4] ML tree search #10, logLikelihood: -180173.184701
[06:26:33 -180244.362184] SLOW spr round 25 (radius: 20)
[06:37:33 -180244.362184] SLOW spr round 26 (radius: 25)
[06:51:03 -180244.362184] Model parameter optimization (eps = 0.100000)

[06:51:10] [worker #0] ML tree search #6, logLikelihood: -180244.306587

[06:51:10 -494046.289940] Initial branch length optimization
[06:51:16 -430456.240673] Model parameter optimization (eps = 10.000000)
[06:52:26 -424718.080822] AUTODETECT spr round 1 (radius: 5)
[06:55:50 -340422.913127] AUTODETECT spr round 2 (radius: 10)
[07:00:05 -250375.213837] AUTODETECT spr round 3 (radius: 15)
[07:04:29 -210099.588686] AUTODETECT spr round 4 (radius: 20)
[07:09:54 -201241.009730] AUTODETECT spr round 5 (radius: 25)
[07:11:47] [worker #1] ML tree search #12, logLikelihood: -180252.896055
[07:16:04 -200995.391198] SPR radius for FAST iterations: 25 (autodetect)
[07:16:04 -200995.391198] Model parameter optimization (eps = 3.000000)
[07:16:39 -200177.706816] FAST spr round 1 (radius: 25)
[07:21:17 -181390.085226] FAST spr round 2 (radius: 25)
[07:24:42 -180591.170074] FAST spr round 3 (radius: 25)
[07:27:44 -180507.155767] FAST spr round 4 (radius: 25)
[07:30:28 -180494.119541] FAST spr round 5 (radius: 25)
[07:33:01 -180488.384220] FAST spr round 6 (radius: 25)
[07:35:37 -180468.087432] FAST spr round 7 (radius: 25)
[07:38:00 -180466.617170] FAST spr round 8 (radius: 25)
[07:40:21 -180466.299001] FAST spr round 9 (radius: 25)
[07:42:42 -180462.537510] FAST spr round 10 (radius: 25)
[07:45:03 -180461.227952] FAST spr round 11 (radius: 25)
[07:47:24 -180460.428443] FAST spr round 12 (radius: 25)
[07:49:44 -180460.428433] Model parameter optimization (eps = 1.000000)
[07:50:21 -180442.679718] SLOW spr round 1 (radius: 5)
[07:53:51 -180353.985350] SLOW spr round 2 (radius: 5)
[07:57:11 -180344.242312] SLOW spr round 3 (radius: 5)
[08:00:24 -180333.118612] SLOW spr round 4 (radius: 5)
[08:00:54] [worker #3] ML tree search #14, logLikelihood: -180257.830733
[08:03:33 -180330.197085] SLOW spr round 5 (radius: 5)
[08:06:37 -180330.196922] SLOW spr round 6 (radius: 10)
[08:10:02 -180320.181861] SLOW spr round 7 (radius: 5)
[08:10:33] [worker #2] ML tree search #8, logLikelihood: -180185.416172
[08:13:55 -180307.490324] SLOW spr round 8 (radius: 5)
[08:17:16 -180306.861186] SLOW spr round 9 (radius: 5)
[08:20:21 -180304.956077] SLOW spr round 10 (radius: 5)
[08:23:28 -180298.856782] SLOW spr round 11 (radius: 5)
[08:26:30 -180298.854789] SLOW spr round 12 (radius: 10)
[08:29:52 -180298.264797] SLOW spr round 13 (radius: 5)
[08:33:35 -180298.108712] SLOW spr round 14 (radius: 5)
[08:36:54 -180298.108699] SLOW spr round 15 (radius: 10)
[08:40:28 -180298.108686] SLOW spr round 16 (radius: 15)
[08:46:23 -180292.685769] SLOW spr round 17 (radius: 5)
[08:50:41 -180285.978662] SLOW spr round 18 (radius: 5)
[08:54:12 -180285.978457] SLOW spr round 19 (radius: 10)
[08:57:52 -180283.555222] SLOW spr round 20 (radius: 5)
[09:01:33 -180283.555208] SLOW spr round 21 (radius: 10)
[09:05:24 -180282.537358] SLOW spr round 22 (radius: 5)
[09:07:28] [worker #4] ML tree search #15, logLikelihood: -180204.468536
[09:09:05 -180282.537344] SLOW spr round 23 (radius: 10)
[09:12:53 -180282.201042] SLOW spr round 24 (radius: 5)
[09:16:39 -180277.797978] SLOW spr round 25 (radius: 5)
[09:19:59 -180277.797502] SLOW spr round 26 (radius: 10)
[09:23:33 -180276.820177] SLOW spr round 27 (radius: 5)
[09:27:17 -180276.820146] SLOW spr round 28 (radius: 10)
[09:31:07 -180275.593722] SLOW spr round 29 (radius: 5)
[09:34:51 -180274.212614] SLOW spr round 30 (radius: 5)
[09:38:11 -180274.212472] SLOW spr round 31 (radius: 10)
[09:41:41 -180274.212458] SLOW spr round 32 (radius: 15)
[09:47:34 -180274.212444] SLOW spr round 33 (radius: 20)
[09:58:19 -180274.212430] SLOW spr round 34 (radius: 25)
[10:11:39 -180274.212415] Model parameter optimization (eps = 0.100000)

[10:11:57] [worker #0] ML tree search #11, logLikelihood: -180273.057776

[10:11:57 -492879.701143] Initial branch length optimization
[10:12:02 -429792.985365] Model parameter optimization (eps = 10.000000)
[10:13:07 -424074.616472] AUTODETECT spr round 1 (radius: 5)
[10:16:28 -340061.946800] AUTODETECT spr round 2 (radius: 10)
[10:20:37 -248142.487359] AUTODETECT spr round 3 (radius: 15)
[10:21:20] [worker #3] ML tree search #19, logLikelihood: -180240.767951
[10:25:24 -211881.208641] AUTODETECT spr round 4 (radius: 20)
[10:31:37 -205754.902983] AUTODETECT spr round 5 (radius: 25)
[10:40:09 -205614.507130] SPR radius for FAST iterations: 25 (autodetect)
[10:40:09 -205614.507130] Model parameter optimization (eps = 3.000000)
[10:40:48 -204789.901629] FAST spr round 1 (radius: 25)
[10:45:33 -181279.841611] FAST spr round 2 (radius: 25)
[10:48:57 -180475.319937] FAST spr round 3 (radius: 25)
[10:51:56 -180386.388830] FAST spr round 4 (radius: 25)
[10:54:27 -180377.957289] FAST spr round 5 (radius: 25)
[10:55:54] [worker #1] ML tree search #17, logLikelihood: -180264.319353
[10:56:52 -180376.824642] FAST spr round 6 (radius: 25)
[10:59:13 -180376.341491] FAST spr round 7 (radius: 25)
[11:01:34 -180368.498118] FAST spr round 8 (radius: 25)
[11:03:53 -180368.151497] FAST spr round 9 (radius: 25)
[11:06:11 -180367.238292] FAST spr round 10 (radius: 25)
[11:08:30 -180367.238223] Model parameter optimization (eps = 1.000000)
[11:08:57 -180345.041022] SLOW spr round 1 (radius: 5)
[11:12:26 -180294.636802] SLOW spr round 2 (radius: 5)
[11:15:02] [worker #2] ML tree search #13, logLikelihood: -180183.808337
[11:15:41 -180289.908713] SLOW spr round 3 (radius: 5)
[11:18:45 -180289.908675] SLOW spr round 4 (radius: 10)
[11:22:11 -180288.964773] SLOW spr round 5 (radius: 5)
[11:26:01 -180284.918891] SLOW spr round 6 (radius: 5)
[11:29:20 -180284.917583] SLOW spr round 7 (radius: 10)
[11:32:54 -180278.833642] SLOW spr round 8 (radius: 5)
[11:36:43 -180274.320467] SLOW spr round 9 (radius: 5)
[11:40:00 -180274.320365] SLOW spr round 10 (radius: 10)
[11:43:31 -180273.278938] SLOW spr round 11 (radius: 5)
[11:47:17 -180271.510023] SLOW spr round 12 (radius: 5)
[11:50:35 -180271.510019] SLOW spr round 13 (radius: 10)
[11:54:09 -180266.821417] SLOW spr round 14 (radius: 5)
[11:57:51 -180266.821413] SLOW spr round 15 (radius: 10)
[12:01:40 -180266.821413] SLOW spr round 16 (radius: 15)
[12:07:38 -180266.821413] SLOW spr round 17 (radius: 20)
[12:18:35 -180253.410885] SLOW spr round 18 (radius: 5)
[12:19:16] [worker #4] ML tree search #20, logLikelihood: -180190.133907
[12:22:52 -180249.667884] SLOW spr round 19 (radius: 5)
[12:26:25 -180249.115171] SLOW spr round 20 (radius: 5)
[12:29:40 -180249.114846] SLOW spr round 21 (radius: 10)
[12:33:07 -180249.114844] SLOW spr round 22 (radius: 15)
[12:39:16 -180249.114843] SLOW spr round 23 (radius: 20)
[12:49:55 -180249.114843] SLOW spr round 24 (radius: 25)
[13:02:59 -180249.114843] Model parameter optimization (eps = 0.100000)

[13:03:13] [worker #0] ML tree search #16, logLikelihood: -180248.544569

[15:54:33] [worker #2] ML tree search #18, logLikelihood: -180221.469873

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.238302,0.571275) (0.233319,0.611294) (0.405440,1.566016) (0.122940,0.702074) 
   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: -180161.939381

AIC score: 364333.878762 / AICc score: 8408393.878762 / BIC score: 371766.634843
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=301).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 17 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96R54/3_mltree/Q96R54.raxml.log

Analysis started: 07-Jul-2021 00:37:26 / finished: 07-Jul-2021 16:32:00

Elapsed time: 57274.242 seconds

Consumed energy: 3409.728 Wh (= 17 km in an electric car, or 85 km with an e-scooter!)