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 6140 CPU @ 2.30GHz, 36 cores, 251 GB RAM

RAxML-NG was called at 10-Jul-2021 05:14:20 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/2_msa/Q5SY68_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68 --seed 2 --threads 2 --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 (2 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/2_msa/Q5SY68_trimmed_msa.fasta
[00:00:00] Loaded alignment with 92 taxa and 86 sites

WARNING: Sequences tr_A0A2J8Q3N5_A0A2J8Q3N5_PANTR_9598 and tr_A0A2R9CD46_A0A2R9CD46_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2R1M2_H2R1M2_PANTR_9598 and sp_Q5SY68_S1A7B_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H2R1M2_H2R1M2_PANTR_9598 and tr_A0A2R9BYW2_A0A2R9BYW2_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G7MDR2_G7MDR2_MACMU_9544 and tr_G8F4W0_G8F4W0_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G7MDR2_G7MDR2_MACMU_9544 and tr_A0A2K5XU46_A0A2K5XU46_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F1SFU5_F1SFU5_PIG_9823 and tr_K7GNU8_K7GNU8_PIG_9823 are exactly identical!
WARNING: Sequences tr_G1M0L8_G1M0L8_AILME_9646 and tr_A0A384CK96_A0A384CK96_URSMA_29073 are exactly identical!
WARNING: Sequences tr_F1MHS5_F1MHS5_BOVIN_9913 and sp_P28783_S10A9_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_A0A226MEV1_A0A226MEV1_CALSU_9009 and tr_A0A226MEG3_A0A226MEG3_COLVI_9014 are exactly identical!
WARNING: Duplicate sequences found: 9

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.reduced.phy

Alignment comprises 1 partitions and 86 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 86 / 86
Gaps: 1.82 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.rba

Parallelization scheme autoconfig: 2 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 92 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 86 / 6880
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -12764.665043] Initial branch length optimization
[00:00:00 -10132.485512] Model parameter optimization (eps = 10.000000)
[00:00:02 -10118.899935] AUTODETECT spr round 1 (radius: 5)
[00:00:03 -6707.162935] AUTODETECT spr round 2 (radius: 10)
[00:00:05 -5480.633033] AUTODETECT spr round 3 (radius: 15)
[00:00:08 -5276.157418] AUTODETECT spr round 4 (radius: 20)
[00:00:10 -5276.150843] SPR radius for FAST iterations: 15 (autodetect)
[00:00:10 -5276.150843] Model parameter optimization (eps = 3.000000)
[00:00:12 -5236.096297] FAST spr round 1 (radius: 15)
[00:00:15 -4949.371652] FAST spr round 2 (radius: 15)
[00:00:17 -4921.606741] FAST spr round 3 (radius: 15)
[00:00:18 -4910.177346] FAST spr round 4 (radius: 15)
[00:00:19 -4906.494026] FAST spr round 5 (radius: 15)
[00:00:21 -4905.644102] FAST spr round 6 (radius: 15)
[00:00:22 -4902.885872] FAST spr round 7 (radius: 15)
[00:00:23 -4902.885845] Model parameter optimization (eps = 1.000000)
[00:00:24 -4902.404642] SLOW spr round 1 (radius: 5)
[00:00:27 -4902.403965] SLOW spr round 2 (radius: 10)
[00:00:30 -4902.403937] SLOW spr round 3 (radius: 15)
[00:00:34] [worker #1] ML tree search #2, logLikelihood: -4902.171511
[00:00:34 -4901.880571] SLOW spr round 4 (radius: 5)
[00:00:39 -4901.880468] SLOW spr round 5 (radius: 10)
[00:00:43 -4901.880467] SLOW spr round 6 (radius: 15)
[00:00:46 -4901.880467] SLOW spr round 7 (radius: 20)
[00:00:50 -4901.880467] SLOW spr round 8 (radius: 25)
[00:00:52 -4901.880467] Model parameter optimization (eps = 0.100000)

[00:00:53] [worker #0] ML tree search #1, logLikelihood: -4901.429088

[00:00:53 -12818.481652] Initial branch length optimization
[00:00:53 -10220.270433] Model parameter optimization (eps = 10.000000)
[00:00:55 -10203.704686] AUTODETECT spr round 1 (radius: 5)
[00:00:56 -7390.178884] AUTODETECT spr round 2 (radius: 10)
[00:00:59 -5377.982808] AUTODETECT spr round 3 (radius: 15)
[00:01:01 -5339.649210] AUTODETECT spr round 4 (radius: 20)
[00:01:03 -5337.159365] AUTODETECT spr round 5 (radius: 25)
[00:01:04 -5337.146321] SPR radius for FAST iterations: 20 (autodetect)
[00:01:04 -5337.146321] Model parameter optimization (eps = 3.000000)
[00:01:07 -5305.732225] FAST spr round 1 (radius: 20)
[00:01:09 -4941.822049] FAST spr round 2 (radius: 20)
[00:01:11 -4912.270953] FAST spr round 3 (radius: 20)
[00:01:13 -4909.036646] FAST spr round 4 (radius: 20)
[00:01:14 -4904.393503] FAST spr round 5 (radius: 20)
[00:01:16 -4904.109813] FAST spr round 6 (radius: 20)
[00:01:17 -4904.109801] Model parameter optimization (eps = 1.000000)
[00:01:18 -4901.657533] SLOW spr round 1 (radius: 5)
[00:01:21 -4901.657354] SLOW spr round 2 (radius: 10)
[00:01:24 -4901.657353] SLOW spr round 3 (radius: 15)
[00:01:28 -4901.657353] SLOW spr round 4 (radius: 20)
[00:01:30] [worker #1] ML tree search #4, logLikelihood: -4901.232864
[00:01:31 -4901.657353] SLOW spr round 5 (radius: 25)
[00:01:33 -4901.657353] Model parameter optimization (eps = 0.100000)

[00:01:33] [worker #0] ML tree search #3, logLikelihood: -4901.657337

[00:01:33 -13032.745467] Initial branch length optimization
[00:01:33 -10387.006103] Model parameter optimization (eps = 10.000000)
[00:01:35 -10374.513969] AUTODETECT spr round 1 (radius: 5)
[00:01:36 -7193.183685] AUTODETECT spr round 2 (radius: 10)
[00:01:38 -5724.186416] AUTODETECT spr round 3 (radius: 15)
[00:01:41 -5319.898706] AUTODETECT spr round 4 (radius: 20)
[00:01:42 -5319.894402] SPR radius for FAST iterations: 15 (autodetect)
[00:01:42 -5319.894402] Model parameter optimization (eps = 3.000000)
[00:01:45 -5282.589699] FAST spr round 1 (radius: 15)
[00:01:47 -4951.324537] FAST spr round 2 (radius: 15)
[00:01:49 -4913.001383] FAST spr round 3 (radius: 15)
[00:01:51 -4911.896409] FAST spr round 4 (radius: 15)
[00:01:52 -4911.896386] Model parameter optimization (eps = 1.000000)
[00:01:53 -4911.464686] SLOW spr round 1 (radius: 5)
[00:01:56 -4903.846650] SLOW spr round 2 (radius: 5)
[00:01:59 -4902.343889] SLOW spr round 3 (radius: 5)
[00:02:01 -4902.343655] SLOW spr round 4 (radius: 10)
[00:02:04 -4902.343652] SLOW spr round 5 (radius: 15)
[00:02:08 -4902.343652] SLOW spr round 6 (radius: 20)
[00:02:11 -4902.343652] SLOW spr round 7 (radius: 25)
[00:02:12] [worker #1] ML tree search #6, logLikelihood: -4901.864630
[00:02:13 -4902.343652] Model parameter optimization (eps = 0.100000)

[00:02:14] [worker #0] ML tree search #5, logLikelihood: -4901.657417

[00:02:14 -13263.116400] Initial branch length optimization
[00:02:14 -10239.752843] Model parameter optimization (eps = 10.000000)
[00:02:17 -10219.155958] AUTODETECT spr round 1 (radius: 5)
[00:02:19 -6869.584024] AUTODETECT spr round 2 (radius: 10)
[00:02:21 -5355.558784] AUTODETECT spr round 3 (radius: 15)
[00:02:24 -5188.406888] AUTODETECT spr round 4 (radius: 20)
[00:02:25 -5188.374071] SPR radius for FAST iterations: 15 (autodetect)
[00:02:25 -5188.374071] Model parameter optimization (eps = 3.000000)
[00:02:28 -5156.513245] FAST spr round 1 (radius: 15)
[00:02:30 -4918.510702] FAST spr round 2 (radius: 15)
[00:02:32 -4904.686581] FAST spr round 3 (radius: 15)
[00:02:33 -4904.686083] Model parameter optimization (eps = 1.000000)
[00:02:34 -4904.189571] SLOW spr round 1 (radius: 5)
[00:02:37 -4903.646362] SLOW spr round 2 (radius: 5)
[00:02:40 -4903.257820] SLOW spr round 3 (radius: 5)
[00:02:43 -4903.257762] SLOW spr round 4 (radius: 10)
[00:02:45 -4903.257762] SLOW spr round 5 (radius: 15)
[00:02:49 -4903.212297] SLOW spr round 6 (radius: 20)
[00:02:53 -4903.212163] SLOW spr round 7 (radius: 25)
[00:02:54 -4903.212161] Model parameter optimization (eps = 0.100000)

[00:02:56] [worker #0] ML tree search #7, logLikelihood: -4902.865793

[00:02:56 -12605.702976] Initial branch length optimization
[00:02:56 -10081.802152] Model parameter optimization (eps = 10.000000)
[00:02:57 -10065.693451] AUTODETECT spr round 1 (radius: 5)
[00:02:59 -6899.026607] AUTODETECT spr round 2 (radius: 10)
[00:03:01 -5411.372689] AUTODETECT spr round 3 (radius: 15)
[00:03:03 -5211.221146] AUTODETECT spr round 4 (radius: 20)
[00:03:06 -5211.205973] SPR radius for FAST iterations: 15 (autodetect)
[00:03:06 -5211.205973] Model parameter optimization (eps = 3.000000)
[00:03:08] [worker #1] ML tree search #8, logLikelihood: -4901.232819
[00:03:08 -5170.885540] FAST spr round 1 (radius: 15)
[00:03:10 -4930.160293] FAST spr round 2 (radius: 15)
[00:03:12 -4910.019586] FAST spr round 3 (radius: 15)
[00:03:14 -4902.094858] FAST spr round 4 (radius: 15)
[00:03:15 -4901.447669] FAST spr round 5 (radius: 15)
[00:03:16 -4901.447666] Model parameter optimization (eps = 1.000000)
[00:03:17 -4900.915418] SLOW spr round 1 (radius: 5)
[00:03:20 -4900.915172] SLOW spr round 2 (radius: 10)
[00:03:23 -4900.915172] SLOW spr round 3 (radius: 15)
[00:03:27 -4900.915172] SLOW spr round 4 (radius: 20)
[00:03:30 -4900.915172] SLOW spr round 5 (radius: 25)
[00:03:32 -4900.915172] Model parameter optimization (eps = 0.100000)

[00:03:32] [worker #0] ML tree search #9, logLikelihood: -4900.914992

[00:03:32 -12748.248780] Initial branch length optimization
[00:03:32 -10107.392905] Model parameter optimization (eps = 10.000000)
[00:03:34 -10088.926190] AUTODETECT spr round 1 (radius: 5)
[00:03:36 -7205.172415] AUTODETECT spr round 2 (radius: 10)
[00:03:38 -5269.816301] AUTODETECT spr round 3 (radius: 15)
[00:03:41 -5123.484382] AUTODETECT spr round 4 (radius: 20)
[00:03:43 -5123.478097] SPR radius for FAST iterations: 15 (autodetect)
[00:03:43 -5123.478097] Model parameter optimization (eps = 3.000000)
[00:03:45 -5078.607323] FAST spr round 1 (radius: 15)
[00:03:47 -4918.165210] FAST spr round 2 (radius: 15)
[00:03:49 -4903.475654] FAST spr round 3 (radius: 15)
[00:03:50 -4901.685724] FAST spr round 4 (radius: 15)
[00:03:52 -4901.685670] Model parameter optimization (eps = 1.000000)
[00:03:52 -4901.233303] SLOW spr round 1 (radius: 5)
[00:03:55 -4901.232921] SLOW spr round 2 (radius: 10)
[00:03:58 -4901.232918] SLOW spr round 3 (radius: 15)
[00:04:01] [worker #1] ML tree search #10, logLikelihood: -4901.746967
[00:04:02 -4901.232917] SLOW spr round 4 (radius: 20)
[00:04:05 -4901.232916] SLOW spr round 5 (radius: 25)
[00:04:07 -4901.232916] Model parameter optimization (eps = 0.100000)

[00:04:07] [worker #0] ML tree search #11, logLikelihood: -4901.232810

[00:04:07 -13102.546883] Initial branch length optimization
[00:04:07 -10371.859067] Model parameter optimization (eps = 10.000000)
[00:04:10 -10356.609262] AUTODETECT spr round 1 (radius: 5)
[00:04:11 -7097.513539] AUTODETECT spr round 2 (radius: 10)
[00:04:13 -5320.449505] AUTODETECT spr round 3 (radius: 15)
[00:04:16 -5246.499149] AUTODETECT spr round 4 (radius: 20)
[00:04:18 -5243.466631] AUTODETECT spr round 5 (radius: 25)
[00:04:20 -5243.458388] SPR radius for FAST iterations: 20 (autodetect)
[00:04:20 -5243.458388] Model parameter optimization (eps = 3.000000)
[00:04:23 -5192.984590] FAST spr round 1 (radius: 20)
[00:04:25 -4921.653584] FAST spr round 2 (radius: 20)
[00:04:27 -4903.745864] FAST spr round 3 (radius: 20)
[00:04:28 -4902.794695] FAST spr round 4 (radius: 20)
[00:04:30 -4902.794660] Model parameter optimization (eps = 1.000000)
[00:04:31 -4901.657625] SLOW spr round 1 (radius: 5)
[00:04:34 -4901.657537] SLOW spr round 2 (radius: 10)
[00:04:36 -4901.657536] SLOW spr round 3 (radius: 15)
[00:04:39] [worker #1] ML tree search #12, logLikelihood: -4904.408614
[00:04:40 -4901.657535] SLOW spr round 4 (radius: 20)
[00:04:44 -4901.657534] SLOW spr round 5 (radius: 25)
[00:04:46 -4901.657533] Model parameter optimization (eps = 0.100000)

[00:04:46] [worker #0] ML tree search #13, logLikelihood: -4901.657525

[00:04:46 -12979.648254] Initial branch length optimization
[00:04:46 -10287.414586] Model parameter optimization (eps = 10.000000)
[00:04:48 -10263.580705] AUTODETECT spr round 1 (radius: 5)
[00:04:49 -7236.759684] AUTODETECT spr round 2 (radius: 10)
[00:04:51 -5758.201464] AUTODETECT spr round 3 (radius: 15)
[00:04:54 -5488.913712] AUTODETECT spr round 4 (radius: 20)
[00:04:55 -5488.145517] AUTODETECT spr round 5 (radius: 25)
[00:04:56 -5488.116891] SPR radius for FAST iterations: 20 (autodetect)
[00:04:56 -5488.116891] Model parameter optimization (eps = 3.000000)
[00:04:58 -5422.766492] FAST spr round 1 (radius: 20)
[00:05:00 -5021.150020] FAST spr round 2 (radius: 20)
[00:05:02 -4918.557225] FAST spr round 3 (radius: 20)
[00:05:04 -4913.719464] FAST spr round 4 (radius: 20)
[00:05:05 -4913.718803] Model parameter optimization (eps = 1.000000)
[00:05:06 -4911.996440] SLOW spr round 1 (radius: 5)
[00:05:10 -4907.560961] SLOW spr round 2 (radius: 5)
[00:05:12 -4907.207956] SLOW spr round 3 (radius: 5)
[00:05:15 -4907.205589] SLOW spr round 4 (radius: 10)
[00:05:18 -4907.204838] SLOW spr round 5 (radius: 15)
[00:05:22 -4907.204591] SLOW spr round 6 (radius: 20)
[00:05:22] [worker #1] ML tree search #14, logLikelihood: -4905.684036
[00:05:25 -4907.204512] SLOW spr round 7 (radius: 25)
[00:05:27 -4907.204487] Model parameter optimization (eps = 0.100000)

[00:05:28] [worker #0] ML tree search #15, logLikelihood: -4907.037143

[00:05:28 -12515.151784] Initial branch length optimization
[00:05:28 -10056.373866] Model parameter optimization (eps = 10.000000)
[00:05:32 -10023.895848] AUTODETECT spr round 1 (radius: 5)
[00:05:34 -7390.600480] AUTODETECT spr round 2 (radius: 10)
[00:05:36 -5459.382361] AUTODETECT spr round 3 (radius: 15)
[00:05:39 -5422.109002] AUTODETECT spr round 4 (radius: 20)
[00:05:41 -5412.333727] AUTODETECT spr round 5 (radius: 25)
[00:05:42 -5407.484610] SPR radius for FAST iterations: 25 (autodetect)
[00:05:42 -5407.484610] Model parameter optimization (eps = 3.000000)
[00:05:44 -5376.519007] FAST spr round 1 (radius: 25)
[00:05:47 -4936.955844] FAST spr round 2 (radius: 25)
[00:05:48 -4914.787743] FAST spr round 3 (radius: 25)
[00:05:50 -4913.730485] FAST spr round 4 (radius: 25)
[00:05:51 -4912.902890] FAST spr round 5 (radius: 25)
[00:05:52 -4912.902366] Model parameter optimization (eps = 1.000000)
[00:05:54 -4910.930040] SLOW spr round 1 (radius: 5)
[00:05:57 -4907.736982] SLOW spr round 2 (radius: 5)
[00:05:58] [worker #1] ML tree search #16, logLikelihood: -4903.894974
[00:06:00 -4907.190404] SLOW spr round 3 (radius: 5)
[00:06:02 -4907.187769] SLOW spr round 4 (radius: 10)
[00:06:05 -4907.187113] SLOW spr round 5 (radius: 15)
[00:06:09 -4907.186906] SLOW spr round 6 (radius: 20)
[00:06:12 -4907.186839] SLOW spr round 7 (radius: 25)
[00:06:15 -4907.186816] Model parameter optimization (eps = 0.100000)

[00:06:16] [worker #0] ML tree search #17, logLikelihood: -4907.037281

[00:06:16 -13051.498621] Initial branch length optimization
[00:06:16 -10332.381175] Model parameter optimization (eps = 10.000000)
[00:06:17 -10319.987456] AUTODETECT spr round 1 (radius: 5)
[00:06:19 -7092.273854] AUTODETECT spr round 2 (radius: 10)
[00:06:21 -5311.757941] AUTODETECT spr round 3 (radius: 15)
[00:06:24 -5184.391245] AUTODETECT spr round 4 (radius: 20)
[00:06:26 -5184.389300] SPR radius for FAST iterations: 15 (autodetect)
[00:06:26 -5184.389300] Model parameter optimization (eps = 3.000000)
[00:06:28 -5146.473958] FAST spr round 1 (radius: 15)
[00:06:30 -4924.912141] FAST spr round 2 (radius: 15)
[00:06:31 -4908.971040] FAST spr round 3 (radius: 15)
[00:06:33 -4908.969884] Model parameter optimization (eps = 1.000000)
[00:06:34 -4908.039145] SLOW spr round 1 (radius: 5)
[00:06:37 -4907.576225] SLOW spr round 2 (radius: 5)
[00:06:39 -4907.573458] SLOW spr round 3 (radius: 10)
[00:06:40] [worker #1] ML tree search #18, logLikelihood: -4902.695127
[00:06:42 -4907.572571] SLOW spr round 4 (radius: 15)
[00:06:46 -4907.572280] SLOW spr round 5 (radius: 20)
[00:06:49 -4907.572187] SLOW spr round 6 (radius: 25)
[00:06:52 -4907.572157] Model parameter optimization (eps = 0.100000)

[00:06:52] [worker #0] ML tree search #19, logLikelihood: -4907.549823

[00:07:17] [worker #1] ML tree search #20, logLikelihood: -4902.684446

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.162483,0.896705) (0.175448,1.004541) (0.282082,0.597771) (0.379988,1.340665) 
   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: -4900.914992

AIC score: 10175.829983 / AICc score: 80487.829983 / BIC score: 10634.792928
Free parameters (model + branch lengths): 187

WARNING: Number of free parameters (K=187) is larger than alignment size (n=86).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 3 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.bestTreeCollapsed
Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SY68/3_mltree/Q5SY68.raxml.log

Analysis started: 10-Jul-2021 05:14:20 / finished: 10-Jul-2021 05:21:38

Elapsed time: 437.997 seconds