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 03-Jul-2021 08:26:35 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/2_msa/Q8N660_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660 --seed 2 --threads 3 --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 (3 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/2_msa/Q8N660_trimmed_msa.fasta [00:00:00] Loaded alignment with 240 taxa and 168 sites WARNING: Sequences tr_A0A2I3GG31_A0A2I3GG31_NOMLE_61853 and tr_A0A2I2YJJ0_A0A2I2YJJ0_GORGO_9595 are exactly identical! WARNING: Sequences tr_A0A2I3TUD2_A0A2I3TUD2_PANTR_9598 and tr_A0A2R9A420_A0A2R9A420_PANPA_9597 are exactly identical! WARNING: Sequences tr_H2R773_H2R773_PANTR_9598 and tr_A0A2R9A2L8_A0A2R9A2L8_PANPA_9597 are exactly identical! WARNING: Sequences sp_B4DH59_NBPFP_HUMAN_9606 and sp_Q5TI25_NBPFE_HUMAN_9606 are exactly identical! WARNING: Sequences sp_Q5TAG4_NBPFC_HUMAN_9606 and sp_Q86T75_NBPFB_HUMAN_9606 are exactly identical! WARNING: Sequences sp_Q5VWK0_NBPF6_HUMAN_9606 and sp_Q86XG9_NBPF5_HUMAN_9606 are exactly identical! WARNING: Sequences sp_Q5VWK0_NBPF6_HUMAN_9606 and sp_Q96M43_NBPF4_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A1D5QNW3_A0A1D5QNW3_MACMU_9544 and tr_A0A2I3MHZ1_A0A2I3MHZ1_PAPAN_9555 are exactly identical! WARNING: Sequences tr_A0A1D5QNW3_A0A1D5QNW3_MACMU_9544 and tr_A0A2K6B1I2_A0A2K6B1I2_MACNE_9545 are exactly identical! WARNING: Sequences tr_F6PTA0_F6PTA0_MACMU_9544 and tr_A0A2K6E0Y1_A0A2K6E0Y1_MACNE_9545 are exactly identical! WARNING: Sequences tr_G7NTU3_G7NTU3_MACFA_9541 and tr_A0A2I3LFV0_A0A2I3LFV0_PAPAN_9555 are exactly identical! WARNING: Sequences tr_G7NTU3_G7NTU3_MACFA_9541 and tr_A0A2K6DLA2_A0A2K6DLA2_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A2K6E4R4_A0A2K6E4R4_MACNE_9545 and tr_A0A2K5XXQ9_A0A2K5XXQ9_MANLE_9568 are exactly identical! WARNING: Sequences tr_A0A2U4A343_A0A2U4A343_TURTR_9739 and tr_A0A2Y9NXA4_A0A2Y9NXA4_DELLE_9749 are exactly identical! WARNING: Sequences tr_A0A2U4A343_A0A2U4A343_TURTR_9739 and tr_A0A383Z2G8_A0A383Z2G8_BALAS_310752 are exactly identical! WARNING: Duplicate sequences found: 15 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/Q8N660/3_mltree/Q8N660.raxml.reduced.phy Alignment comprises 1 partitions and 168 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 168 / 168 Gaps: 20.35 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.rba Parallelization scheme autoconfig: 3 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 240 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 168 / 13440 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -53944.099029] Initial branch length optimization [00:00:00 -46585.090530] Model parameter optimization (eps = 10.000000) [00:00:11 -46023.731739] AUTODETECT spr round 1 (radius: 5) [00:00:21 -26866.391739] AUTODETECT spr round 2 (radius: 10) [00:00:34 -20435.979985] AUTODETECT spr round 3 (radius: 15) [00:00:50 -18811.301366] AUTODETECT spr round 4 (radius: 20) [00:01:08 -18767.933578] AUTODETECT spr round 5 (radius: 25) [00:01:29 -18763.866545] SPR radius for FAST iterations: 25 (autodetect) [00:01:29 -18763.866545] Model parameter optimization (eps = 3.000000) [00:01:37 -18669.558649] FAST spr round 1 (radius: 25) [00:01:52 -16478.076236] FAST spr round 2 (radius: 25) [00:02:03 -16212.449337] FAST spr round 3 (radius: 25) [00:02:12 -16205.993782] FAST spr round 4 (radius: 25) [00:02:21 -16205.931849] Model parameter optimization (eps = 1.000000) [00:02:25 -16203.711214] SLOW spr round 1 (radius: 5) [00:02:41 -16183.638576] SLOW spr round 2 (radius: 5) [00:02:56 -16183.259202] SLOW spr round 3 (radius: 5) [00:03:12 -16183.258707] SLOW spr round 4 (radius: 10) [00:03:27 -16183.258575] SLOW spr round 5 (radius: 15) [00:03:58 -16183.004425] SLOW spr round 6 (radius: 5) [00:04:20 -16182.989020] SLOW spr round 7 (radius: 10) [00:04:40 -16182.767955] SLOW spr round 8 (radius: 5) [00:05:02 -16182.388566] SLOW spr round 9 (radius: 5) [00:05:19 -16182.386166] SLOW spr round 10 (radius: 10) [00:05:35 -16182.287471] SLOW spr round 11 (radius: 15) [00:05:39] [worker #1] ML tree search #2, logLikelihood: -16175.170661 [00:06:04 -16182.281133] SLOW spr round 12 (radius: 20) [00:06:39 -16182.280832] SLOW spr round 13 (radius: 25) [00:07:07 -16182.280760] Model parameter optimization (eps = 0.100000) [00:07:10] [worker #0] ML tree search #1, logLikelihood: -16181.835090 [00:07:11 -52531.208457] Initial branch length optimization [00:07:11 -44576.522946] Model parameter optimization (eps = 10.000000) [00:07:18] [worker #2] ML tree search #3, logLikelihood: -16172.277366 [00:07:23 -44116.542965] AUTODETECT spr round 1 (radius: 5) [00:07:32 -26014.921469] AUTODETECT spr round 2 (radius: 10) [00:07:46 -20472.531843] AUTODETECT spr round 3 (radius: 15) [00:08:03 -18922.022755] AUTODETECT spr round 4 (radius: 20) [00:08:24 -18659.554612] AUTODETECT spr round 5 (radius: 25) [00:08:45 -18659.537334] SPR radius for FAST iterations: 20 (autodetect) [00:08:45 -18659.537334] Model parameter optimization (eps = 3.000000) [00:08:54 -18575.059352] FAST spr round 1 (radius: 20) [00:09:07 -16390.557526] FAST spr round 2 (radius: 20) [00:09:19 -16187.837275] FAST spr round 3 (radius: 20) [00:09:29 -16179.888725] FAST spr round 4 (radius: 20) [00:09:37 -16179.888107] Model parameter optimization (eps = 1.000000) [00:09:41 -16177.427425] SLOW spr round 1 (radius: 5) [00:09:57 -16171.160663] SLOW spr round 2 (radius: 5) [00:10:13 -16170.867985] SLOW spr round 3 (radius: 5) [00:10:28 -16170.867275] SLOW spr round 4 (radius: 10) [00:10:44 -16168.583958] SLOW spr round 5 (radius: 5) [00:11:06 -16166.425805] SLOW spr round 6 (radius: 5) [00:11:25 -16166.424636] SLOW spr round 7 (radius: 10) [00:11:29] [worker #1] ML tree search #5, logLikelihood: -16175.703699 [00:11:41 -16164.300852] SLOW spr round 8 (radius: 5) [00:12:04 -16163.926828] SLOW spr round 9 (radius: 5) [00:12:22 -16163.924306] SLOW spr round 10 (radius: 10) [00:12:38 -16163.924074] SLOW spr round 11 (radius: 15) [00:13:06 -16163.923893] SLOW spr round 12 (radius: 20) [00:13:18] [worker #2] ML tree search #6, logLikelihood: -16163.927447 [00:13:42 -16163.923713] SLOW spr round 13 (radius: 25) [00:14:10 -16163.923532] Model parameter optimization (eps = 0.100000) [00:14:14] [worker #0] ML tree search #4, logLikelihood: -16163.557261 [00:14:14 -52590.778798] Initial branch length optimization [00:14:14 -44656.531620] Model parameter optimization (eps = 10.000000) [00:14:23 -43983.281473] AUTODETECT spr round 1 (radius: 5) [00:14:33 -28263.370505] AUTODETECT spr round 2 (radius: 10) [00:14:46 -21258.995643] AUTODETECT spr round 3 (radius: 15) [00:15:01 -18840.398830] AUTODETECT spr round 4 (radius: 20) [00:15:21 -18683.146822] AUTODETECT spr round 5 (radius: 25) [00:15:40 -18660.407098] SPR radius for FAST iterations: 25 (autodetect) [00:15:40 -18660.407098] Model parameter optimization (eps = 3.000000) [00:15:49 -18563.821532] FAST spr round 1 (radius: 25) [00:16:02 -16376.507519] FAST spr round 2 (radius: 25) [00:16:15 -16195.604058] FAST spr round 3 (radius: 25) [00:16:24 -16185.930021] FAST spr round 4 (radius: 25) [00:16:32 -16185.929491] Model parameter optimization (eps = 1.000000) [00:16:35 -16185.351756] SLOW spr round 1 (radius: 5) [00:16:50 -16178.830807] SLOW spr round 2 (radius: 5) [00:17:05 -16178.827675] SLOW spr round 3 (radius: 10) [00:17:21 -16175.208297] SLOW spr round 4 (radius: 5) [00:17:43 -16173.672332] SLOW spr round 5 (radius: 5) [00:17:56] [worker #2] ML tree search #9, logLikelihood: -16180.608438 [00:18:02 -16173.661891] SLOW spr round 6 (radius: 10) [00:18:14] [worker #1] ML tree search #8, logLikelihood: -16162.094151 [00:18:18 -16173.661203] SLOW spr round 7 (radius: 15) [00:18:48 -16173.661042] SLOW spr round 8 (radius: 20) [00:19:25 -16173.660931] SLOW spr round 9 (radius: 25) [00:19:52 -16173.660825] Model parameter optimization (eps = 0.100000) [00:19:54] [worker #0] ML tree search #7, logLikelihood: -16173.604154 [00:19:54 -52717.022072] Initial branch length optimization [00:19:55 -45019.102366] Model parameter optimization (eps = 10.000000) [00:20:04 -44506.687490] AUTODETECT spr round 1 (radius: 5) [00:20:14 -28184.485909] AUTODETECT spr round 2 (radius: 10) [00:20:27 -19559.916631] AUTODETECT spr round 3 (radius: 15) [00:20:44 -18079.259949] AUTODETECT spr round 4 (radius: 20) [00:21:04 -17880.010863] AUTODETECT spr round 5 (radius: 25) [00:21:23 -17880.002616] SPR radius for FAST iterations: 20 (autodetect) [00:21:23 -17880.002616] Model parameter optimization (eps = 3.000000) [00:21:31 -17812.470390] FAST spr round 1 (radius: 20) [00:21:45 -16330.097161] FAST spr round 2 (radius: 20) [00:21:56 -16191.077213] FAST spr round 3 (radius: 20) [00:22:06 -16180.404693] FAST spr round 4 (radius: 20) [00:22:14 -16180.404613] Model parameter optimization (eps = 1.000000) [00:22:19 -16178.623691] SLOW spr round 1 (radius: 5) [00:22:34 -16174.906173] SLOW spr round 2 (radius: 5) [00:22:50 -16173.806260] SLOW spr round 3 (radius: 5) [00:23:06 -16173.806114] SLOW spr round 4 (radius: 10) [00:23:21 -16173.571873] SLOW spr round 5 (radius: 5) [00:23:43 -16173.571703] SLOW spr round 6 (radius: 10) [00:23:47] [worker #2] ML tree search #12, logLikelihood: -16166.673811 [00:24:02 -16173.571637] SLOW spr round 7 (radius: 15) [00:24:29 -16173.571606] SLOW spr round 8 (radius: 20) [00:25:00 -16173.571591] SLOW spr round 9 (radius: 25) [00:25:31 -16173.571583] Model parameter optimization (eps = 0.100000) [00:25:35] [worker #0] ML tree search #10, logLikelihood: -16173.441250 [00:25:35 -52248.959371] Initial branch length optimization [00:25:36 -44204.083292] Model parameter optimization (eps = 10.000000) [00:25:47 -43754.383022] AUTODETECT spr round 1 (radius: 5) [00:25:57 -27011.568428] AUTODETECT spr round 2 (radius: 10) [00:26:09 -20880.230022] AUTODETECT spr round 3 (radius: 15) [00:26:24 -18215.152766] AUTODETECT spr round 4 (radius: 20) [00:26:34] [worker #1] ML tree search #11, logLikelihood: -16175.755172 [00:26:43 -17851.900245] AUTODETECT spr round 5 (radius: 25) [00:27:03 -17850.393783] SPR radius for FAST iterations: 25 (autodetect) [00:27:03 -17850.393783] Model parameter optimization (eps = 3.000000) [00:27:11 -17787.089705] FAST spr round 1 (radius: 25) [00:27:25 -16249.670872] FAST spr round 2 (radius: 25) [00:27:37 -16188.234579] FAST spr round 3 (radius: 25) [00:27:47 -16181.218768] FAST spr round 4 (radius: 25) [00:27:56 -16176.087136] FAST spr round 5 (radius: 25) [00:28:04 -16175.805612] FAST spr round 6 (radius: 25) [00:28:12 -16175.805008] Model parameter optimization (eps = 1.000000) [00:28:17 -16174.470698] SLOW spr round 1 (radius: 5) [00:28:33 -16171.983900] SLOW spr round 2 (radius: 5) [00:28:48 -16171.982164] SLOW spr round 3 (radius: 10) [00:29:03 -16167.755659] SLOW spr round 4 (radius: 5) [00:29:25 -16167.755064] SLOW spr round 5 (radius: 10) [00:29:43 -16167.373353] SLOW spr round 6 (radius: 5) [00:30:05 -16165.847091] SLOW spr round 7 (radius: 5) [00:30:23 -16165.846968] SLOW spr round 8 (radius: 10) [00:30:40 -16165.846869] SLOW spr round 9 (radius: 15) [00:31:06 -16165.846772] SLOW spr round 10 (radius: 20) [00:31:42 -16165.846674] SLOW spr round 11 (radius: 25) [00:32:10 -16165.846576] Model parameter optimization (eps = 0.100000) [00:32:12] [worker #0] ML tree search #13, logLikelihood: -16165.827417 [00:32:12 -53692.775475] Initial branch length optimization [00:32:12 -45662.902758] Model parameter optimization (eps = 10.000000) [00:32:22 -45194.766240] AUTODETECT spr round 1 (radius: 5) [00:32:32 -27638.940974] AUTODETECT spr round 2 (radius: 10) [00:32:46 -21366.843392] AUTODETECT spr round 3 (radius: 15) [00:33:03 -18198.001955] AUTODETECT spr round 4 (radius: 20) [00:33:08] [worker #2] ML tree search #15, logLikelihood: -16174.330497 [00:33:25 -18074.771422] AUTODETECT spr round 5 (radius: 25) [00:33:44 -18074.766303] SPR radius for FAST iterations: 20 (autodetect) [00:33:44 -18074.766303] Model parameter optimization (eps = 3.000000) [00:33:52 -17966.834145] FAST spr round 1 (radius: 20) [00:34:06 -16320.642686] FAST spr round 2 (radius: 20) [00:34:18 -16184.525719] FAST spr round 3 (radius: 20) [00:34:27 -16179.705480] FAST spr round 4 (radius: 20) [00:34:35 -16179.704331] Model parameter optimization (eps = 1.000000) [00:34:40 -16178.205666] SLOW spr round 1 (radius: 5) [00:34:53] [worker #1] ML tree search #14, logLikelihood: -16177.289620 [00:34:55 -16172.952112] SLOW spr round 2 (radius: 5) [00:35:11 -16172.548347] SLOW spr round 3 (radius: 5) [00:35:27 -16172.547943] SLOW spr round 4 (radius: 10) [00:35:43 -16172.106101] SLOW spr round 5 (radius: 5) [00:36:05 -16170.762680] SLOW spr round 6 (radius: 5) [00:36:24 -16170.395059] SLOW spr round 7 (radius: 5) [00:36:40 -16170.394308] SLOW spr round 8 (radius: 10) [00:36:57 -16170.394125] SLOW spr round 9 (radius: 15) [00:37:27 -16170.393958] SLOW spr round 10 (radius: 20) [00:38:05 -16170.393791] SLOW spr round 11 (radius: 25) [00:38:30 -16170.393625] Model parameter optimization (eps = 0.100000) [00:38:33] [worker #0] ML tree search #16, logLikelihood: -16170.152662 [00:38:33 -52818.829275] Initial branch length optimization [00:38:34 -44589.443083] Model parameter optimization (eps = 10.000000) [00:38:43 -44186.156994] AUTODETECT spr round 1 (radius: 5) [00:38:53 -27769.329285] AUTODETECT spr round 2 (radius: 10) [00:38:59] [worker #2] ML tree search #18, logLikelihood: -16168.355051 [00:39:06 -18652.082084] AUTODETECT spr round 3 (radius: 15) [00:39:25 -17974.847701] AUTODETECT spr round 4 (radius: 20) [00:39:41 -17952.535631] AUTODETECT spr round 5 (radius: 25) [00:39:56 -17952.519225] SPR radius for FAST iterations: 20 (autodetect) [00:39:56 -17952.519225] Model parameter optimization (eps = 3.000000) [00:40:05 -17891.709176] FAST spr round 1 (radius: 20) [00:40:18 -16234.397330] FAST spr round 2 (radius: 20) [00:40:29 -16174.973547] FAST spr round 3 (radius: 20) [00:40:37 -16171.833278] FAST spr round 4 (radius: 20) [00:40:41] [worker #1] ML tree search #17, logLikelihood: -16176.770134 [00:40:46 -16171.833124] Model parameter optimization (eps = 1.000000) [00:40:50 -16168.589779] SLOW spr round 1 (radius: 5) [00:41:06 -16166.780775] SLOW spr round 2 (radius: 5) [00:41:21 -16166.780405] SLOW spr round 3 (radius: 10) [00:41:36 -16166.708025] SLOW spr round 4 (radius: 15) [00:42:07 -16165.213531] SLOW spr round 5 (radius: 5) [00:42:31 -16163.507893] SLOW spr round 6 (radius: 5) [00:42:50 -16163.497647] SLOW spr round 7 (radius: 10) [00:43:08 -16163.103854] SLOW spr round 8 (radius: 5) [00:43:30 -16162.149367] SLOW spr round 9 (radius: 5) [00:43:48 -16162.149201] SLOW spr round 10 (radius: 10) [00:44:05 -16162.149086] SLOW spr round 11 (radius: 15) [00:44:34 -16162.148974] SLOW spr round 12 (radius: 20) [00:45:11 -16162.148862] SLOW spr round 13 (radius: 25) [00:45:37 -16162.148751] Model parameter optimization (eps = 0.100000) [00:45:39] [worker #0] ML tree search #19, logLikelihood: -16162.049765 [00:48:55] [worker #1] ML tree search #20, logLikelihood: -16171.949103 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.131671,0.921874) (0.053709,0.851223) (0.436122,0.808401) (0.378498,1.269058) 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: -16162.049765 AIC score: 33290.099530 / AICc score: 500834.099530 / BIC score: 34798.974132 Free parameters (model + branch lengths): 483 WARNING: Number of free parameters (K=483) is larger than alignment size (n=168). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 42 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N660/3_mltree/Q8N660.raxml.log Analysis started: 03-Jul-2021 08:26:35 / finished: 03-Jul-2021 09:15:31 Elapsed time: 2935.560 seconds Consumed energy: 255.815 Wh (= 1 km in an electric car, or 6 km with an e-scooter!)