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 09:26:39 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/2_msa/Q9BYR2_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/3_mltree/Q9BYR2 --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/Q9BYR2/2_msa/Q9BYR2_trimmed_msa.fasta [00:00:00] Loaded alignment with 571 taxa and 161 sites WARNING: Sequences tr_A0A2I3RYQ7_A0A2I3RYQ7_PANTR_9598 and sp_Q9BYQ7_KRA41_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A2I3RYQ7_A0A2I3RYQ7_PANTR_9598 and tr_A0A2R9ACU5_A0A2R9ACU5_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3TDL2_A0A2I3TDL2_PANTR_9598 and tr_A0A2R8ZLW8_A0A2R8ZLW8_PANPA_9597 are exactly identical! WARNING: Sequences tr_H2RGZ0_H2RGZ0_PANTR_9598 and tr_A0A2R8ZL57_A0A2R8ZL57_PANPA_9597 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_G8F6E0_G8F6E0_MACFA_9541 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_A0A096N9X2_A0A096N9X2_PAPAN_9555 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_A0A0D9SCF2_A0A0D9SCF2_CHLSB_60711 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_A0A2K5L1M7_A0A2K5L1M7_CERAT_9531 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_A0A2K6AMA0_A0A2K6AMA0_MACNE_9545 are exactly identical! WARNING: Sequences tr_F6WQI1_F6WQI1_MACMU_9544 and tr_A0A2K5XD40_A0A2K5XD40_MANLE_9568 are exactly identical! WARNING: Duplicate sequences found: 10 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/Q9BYR2/3_mltree/Q9BYR2.raxml.reduced.phy Alignment comprises 1 partitions and 161 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 161 / 161 Gaps: 18.78 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/3_mltree/Q9BYR2.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 571 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 161 / 12880 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -104087.757870] Initial branch length optimization [00:00:01 -90935.206290] Model parameter optimization (eps = 10.000000) [00:00:24 -90292.624522] AUTODETECT spr round 1 (radius: 5) [00:01:14 -61451.562798] AUTODETECT spr round 2 (radius: 10) [00:02:11 -48118.562614] AUTODETECT spr round 3 (radius: 15) [00:03:24 -41715.490512] AUTODETECT spr round 4 (radius: 20) [00:04:45 -40576.659152] AUTODETECT spr round 5 (radius: 25) [00:06:09 -40329.198393] SPR radius for FAST iterations: 25 (autodetect) [00:06:09 -40329.198393] Model parameter optimization (eps = 3.000000) [00:06:32 -39962.445706] FAST spr round 1 (radius: 25) [00:07:40 -37145.220843] FAST spr round 2 (radius: 25) [00:08:34 -36984.071323] FAST spr round 3 (radius: 25) [00:09:22 -36776.798275] FAST spr round 4 (radius: 25) [00:10:03 -36775.217642] FAST spr round 5 (radius: 25) [00:10:43 -36772.174605] FAST spr round 6 (radius: 25) [00:11:21 -36772.174590] Model parameter optimization (eps = 1.000000) [00:11:32 -36770.846721] SLOW spr round 1 (radius: 5) [00:12:33 -36766.117846] SLOW spr round 2 (radius: 5) [00:13:31 -36764.564951] SLOW spr round 3 (radius: 5) [00:14:28 -36763.133068] SLOW spr round 4 (radius: 5) [00:15:23 -36763.132991] SLOW spr round 5 (radius: 10) [00:16:20 -36759.540638] SLOW spr round 6 (radius: 5) [00:17:35 -36759.501489] SLOW spr round 7 (radius: 10) [00:18:43 -36759.501282] SLOW spr round 8 (radius: 15) [00:20:24 -36759.501281] SLOW spr round 9 (radius: 20) [00:22:37 -36758.585442] SLOW spr round 10 (radius: 5) [00:23:56 -36758.585283] SLOW spr round 11 (radius: 10) [00:25:13 -36758.585282] SLOW spr round 12 (radius: 15) [00:26:53 -36758.585282] SLOW spr round 13 (radius: 20) [00:29:06 -36758.585282] SLOW spr round 14 (radius: 25) [00:31:21 -36758.585282] Model parameter optimization (eps = 0.100000) [00:31:27] [worker #0] ML tree search #1, logLikelihood: -36758.473230 [00:31:27 -104616.926711] Initial branch length optimization [00:31:29 -91206.461722] Model parameter optimization (eps = 10.000000) [00:31:53 -90514.594432] AUTODETECT spr round 1 (radius: 5) [00:32:44 -63291.131116] AUTODETECT spr round 2 (radius: 10) [00:33:42 -47686.191805] AUTODETECT spr round 3 (radius: 15) [00:34:53 -41853.970973] AUTODETECT spr round 4 (radius: 20) [00:36:21 -40664.890281] AUTODETECT spr round 5 (radius: 25) [00:37:15] [worker #1] ML tree search #2, logLikelihood: -36739.629441 [00:38:01 -40621.126907] SPR radius for FAST iterations: 25 (autodetect) [00:38:01 -40621.126907] Model parameter optimization (eps = 3.000000) [00:38:21 -40240.280136] FAST spr round 1 (radius: 25) [00:39:32 -36963.692272] FAST spr round 2 (radius: 25) [00:40:27 -36827.606507] FAST spr round 3 (radius: 25) [00:41:18 -36790.209442] FAST spr round 4 (radius: 25) [00:42:04 -36780.380086] FAST spr round 5 (radius: 25) [00:42:44 -36777.852424] FAST spr round 6 (radius: 25) [00:43:27 -36772.914701] FAST spr round 7 (radius: 25) [00:44:05 -36772.914694] Model parameter optimization (eps = 1.000000) [00:44:15 -36768.441792] SLOW spr round 1 (radius: 5) [00:45:17 -36761.506917] SLOW spr round 2 (radius: 5) [00:46:17 -36758.539179] SLOW spr round 3 (radius: 5) [00:47:13 -36758.412694] SLOW spr round 4 (radius: 5) [00:48:07 -36758.411361] SLOW spr round 5 (radius: 10) [00:49:05 -36755.501988] SLOW spr round 6 (radius: 5) [00:49:51] [worker #2] ML tree search #3, logLikelihood: -36829.795491 [00:50:21 -36755.052659] SLOW spr round 7 (radius: 5) [00:51:26 -36755.051885] SLOW spr round 8 (radius: 10) [00:52:24 -36755.051706] SLOW spr round 9 (radius: 15) [00:54:07 -36755.051640] SLOW spr round 10 (radius: 20) [00:56:07 -36755.051616] SLOW spr round 11 (radius: 25) [00:58:20 -36755.051607] Model parameter optimization (eps = 0.100000) [00:58:24] [worker #0] ML tree search #4, logLikelihood: -36755.005665 [00:58:24 -105748.259410] Initial branch length optimization [00:58:26 -92218.308486] Model parameter optimization (eps = 10.000000) [00:58:49 -91616.082501] AUTODETECT spr round 1 (radius: 5) [00:59:39 -60581.325797] AUTODETECT spr round 2 (radius: 10) [01:00:35 -47866.410099] AUTODETECT spr round 3 (radius: 15) [01:01:33 -42302.263867] AUTODETECT spr round 4 (radius: 20) [01:03:05 -40803.350585] AUTODETECT spr round 5 (radius: 25) [01:04:40 -40650.392016] SPR radius for FAST iterations: 25 (autodetect) [01:04:40 -40650.392016] Model parameter optimization (eps = 3.000000) [01:04:57 -40245.892473] FAST spr round 1 (radius: 25) [01:06:08 -36934.093870] FAST spr round 2 (radius: 25) [01:07:00 -36773.649140] FAST spr round 3 (radius: 25) [01:07:48 -36747.181062] FAST spr round 4 (radius: 25) [01:08:31 -36742.284387] FAST spr round 5 (radius: 25) [01:09:10 -36742.284024] Model parameter optimization (eps = 1.000000) [01:09:20 -36740.573550] SLOW spr round 1 (radius: 5) [01:10:23 -36732.368471] SLOW spr round 2 (radius: 5) [01:11:23 -36728.410454] SLOW spr round 3 (radius: 5) [01:12:18 -36728.408429] SLOW spr round 4 (radius: 10) [01:13:18 -36726.412760] SLOW spr round 5 (radius: 5) [01:14:32 -36726.412530] SLOW spr round 6 (radius: 10) [01:15:41 -36726.412485] SLOW spr round 7 (radius: 15) [01:17:23 -36725.277502] SLOW spr round 8 (radius: 5) [01:18:41 -36725.275203] SLOW spr round 9 (radius: 10) [01:19:56 -36725.274864] SLOW spr round 10 (radius: 15) [01:21:29] [worker #2] ML tree search #6, logLikelihood: -36748.005718 [01:21:35 -36725.274811] SLOW spr round 11 (radius: 20) [01:23:50 -36722.931157] SLOW spr round 12 (radius: 5) [01:25:10 -36722.771329] SLOW spr round 13 (radius: 5) [01:26:19 -36722.771267] SLOW spr round 14 (radius: 10) [01:27:22 -36722.771264] SLOW spr round 15 (radius: 15) [01:29:07 -36722.771262] SLOW spr round 16 (radius: 20) [01:29:22] [worker #1] ML tree search #5, logLikelihood: -36753.922042 [01:31:21 -36722.771260] SLOW spr round 17 (radius: 25) [01:33:40 -36722.771258] Model parameter optimization (eps = 0.100000) [01:33:47] [worker #0] ML tree search #7, logLikelihood: -36722.668689 [01:33:47 -103711.328206] Initial branch length optimization [01:33:48 -90648.388334] Model parameter optimization (eps = 10.000000) [01:34:14 -89987.113308] AUTODETECT spr round 1 (radius: 5) [01:35:03 -61529.380156] AUTODETECT spr round 2 (radius: 10) [01:36:00 -46650.947227] AUTODETECT spr round 3 (radius: 15) [01:37:06 -41316.327631] AUTODETECT spr round 4 (radius: 20) [01:38:30 -40546.962132] AUTODETECT spr round 5 (radius: 25) [01:40:04 -40326.072462] SPR radius for FAST iterations: 25 (autodetect) [01:40:04 -40326.072462] Model parameter optimization (eps = 3.000000) [01:40:25 -39933.981897] FAST spr round 1 (radius: 25) [01:41:35 -36991.636621] FAST spr round 2 (radius: 25) [01:42:29 -36807.343778] FAST spr round 3 (radius: 25) [01:43:14 -36776.201805] FAST spr round 4 (radius: 25) [01:43:57 -36766.150364] FAST spr round 5 (radius: 25) [01:44:37 -36758.393962] FAST spr round 6 (radius: 25) [01:45:15 -36758.393799] Model parameter optimization (eps = 1.000000) [01:45:21 -36757.447892] SLOW spr round 1 (radius: 5) [01:46:26 -36742.072181] SLOW spr round 2 (radius: 5) [01:47:24 -36741.390560] SLOW spr round 3 (radius: 5) [01:48:19 -36741.353997] SLOW spr round 4 (radius: 10) [01:49:16 -36740.720544] SLOW spr round 5 (radius: 5) [01:50:30 -36740.720484] SLOW spr round 6 (radius: 10) [01:51:37 -36740.720470] SLOW spr round 7 (radius: 15) [01:53:15 -36740.720459] SLOW spr round 8 (radius: 20) [01:55:25 -36740.720449] SLOW spr round 9 (radius: 25) [01:57:41 -36740.428963] SLOW spr round 10 (radius: 5) [01:58:37] [worker #2] ML tree search #9, logLikelihood: -36704.103248 [01:59:01 -36740.428948] SLOW spr round 11 (radius: 10) [02:00:18 -36740.428943] SLOW spr round 12 (radius: 15) [02:01:53 -36740.428938] SLOW spr round 13 (radius: 20) [02:04:06 -36740.428935] SLOW spr round 14 (radius: 25) [02:06:20 -36740.428932] Model parameter optimization (eps = 0.100000) [02:06:25] [worker #0] ML tree search #10, logLikelihood: -36740.414157 [02:06:25 -105056.453342] Initial branch length optimization [02:06:26 -91412.075672] Model parameter optimization (eps = 10.000000) [02:06:50 -90866.602414] AUTODETECT spr round 1 (radius: 5) [02:07:40 -64105.160361] AUTODETECT spr round 2 (radius: 10) [02:08:37 -50086.194743] AUTODETECT spr round 3 (radius: 15) [02:09:43 -42733.155763] AUTODETECT spr round 4 (radius: 20) [02:11:08 -41282.322138] AUTODETECT spr round 5 (radius: 25) [02:12:34 -40872.818712] SPR radius for FAST iterations: 25 (autodetect) [02:12:34 -40872.818712] Model parameter optimization (eps = 3.000000) [02:12:55 -40459.360666] FAST spr round 1 (radius: 25) [02:13:45] [worker #1] ML tree search #8, logLikelihood: -36748.901584 [02:14:04 -36939.640183] FAST spr round 2 (radius: 25) [02:14:56 -36785.450333] FAST spr round 3 (radius: 25) [02:15:44 -36762.393891] FAST spr round 4 (radius: 25) [02:16:29 -36741.927649] FAST spr round 5 (radius: 25) [02:17:07 -36741.927634] Model parameter optimization (eps = 1.000000) [02:17:16 -36739.012924] SLOW spr round 1 (radius: 5) [02:18:18 -36727.526699] SLOW spr round 2 (radius: 5) [02:19:16 -36725.869412] SLOW spr round 3 (radius: 5) [02:20:11 -36725.768299] SLOW spr round 4 (radius: 5) [02:21:05 -36725.768168] SLOW spr round 5 (radius: 10) [02:22:01 -36724.935291] SLOW spr round 6 (radius: 5) [02:23:16 -36724.933460] SLOW spr round 7 (radius: 10) [02:24:23 -36724.644820] SLOW spr round 8 (radius: 5) [02:25:37 -36722.536517] SLOW spr round 9 (radius: 5) [02:25:51] [worker #2] ML tree search #12, logLikelihood: -36781.273933 [02:26:41 -36722.535627] SLOW spr round 10 (radius: 10) [02:27:40 -36722.535612] SLOW spr round 11 (radius: 15) [02:29:23 -36720.351021] SLOW spr round 12 (radius: 5) [02:30:40 -36720.347204] SLOW spr round 13 (radius: 10) [02:31:52 -36720.104945] SLOW spr round 14 (radius: 5) [02:33:04 -36720.104656] SLOW spr round 15 (radius: 10) [02:34:09 -36720.104653] SLOW spr round 16 (radius: 15) [02:35:48 -36720.104653] SLOW spr round 17 (radius: 20) [02:37:57 -36720.104652] SLOW spr round 18 (radius: 25) [02:40:09 -36719.432312] SLOW spr round 19 (radius: 5) [02:41:31 -36715.406236] SLOW spr round 20 (radius: 5) [02:42:44 -36705.661533] SLOW spr round 21 (radius: 5) [02:43:46 -36704.814438] SLOW spr round 22 (radius: 5) [02:44:43 -36704.812878] SLOW spr round 23 (radius: 10) [02:45:40 -36704.812814] SLOW spr round 24 (radius: 15) [02:47:29 -36704.386388] SLOW spr round 25 (radius: 5) [02:48:47 -36703.557232] SLOW spr round 26 (radius: 5) [02:49:53 -36703.557076] SLOW spr round 27 (radius: 10) [02:50:54 -36703.557069] SLOW spr round 28 (radius: 15) [02:52:38 -36703.557069] SLOW spr round 29 (radius: 20) [02:54:49 -36703.557069] SLOW spr round 30 (radius: 25) [02:57:04 -36703.557068] Model parameter optimization (eps = 0.100000) [02:57:09] [worker #0] ML tree search #13, logLikelihood: -36703.423111 [02:57:09 -104053.672777] Initial branch length optimization [02:57:11 -91133.473753] Model parameter optimization (eps = 10.000000) [02:57:33 -90447.091415] AUTODETECT spr round 1 (radius: 5) [02:58:23 -62617.204542] AUTODETECT spr round 2 (radius: 10) [02:59:24 -48857.458993] AUTODETECT spr round 3 (radius: 15) [03:00:37 -43574.817189] AUTODETECT spr round 4 (radius: 20) [03:02:06 -41771.606701] AUTODETECT spr round 5 (radius: 25) [03:03:36] [worker #1] ML tree search #11, logLikelihood: -36722.111369 [03:03:44 -41562.998524] SPR radius for FAST iterations: 25 (autodetect) [03:03:44 -41562.998524] Model parameter optimization (eps = 3.000000) [03:04:05 -41138.399407] FAST spr round 1 (radius: 25) [03:05:18 -37125.062467] FAST spr round 2 (radius: 25) [03:06:13 -36785.950527] FAST spr round 3 (radius: 25) [03:07:03 -36754.859043] FAST spr round 4 (radius: 25) [03:07:45 -36748.899127] FAST spr round 5 (radius: 25) [03:08:24 -36748.886256] Model parameter optimization (eps = 1.000000) [03:08:32 -36747.419033] SLOW spr round 1 (radius: 5) [03:09:36 -36737.604760] SLOW spr round 2 (radius: 5) [03:10:34 -36737.250158] SLOW spr round 3 (radius: 5) [03:11:29 -36737.250141] SLOW spr round 4 (radius: 10) [03:12:27 -36736.609700] SLOW spr round 5 (radius: 5) [03:13:42 -36735.651766] SLOW spr round 6 (radius: 5) [03:14:46 -36735.651546] SLOW spr round 7 (radius: 10) [03:15:47 -36735.590485] SLOW spr round 8 (radius: 15) [03:17:34 -36735.590447] SLOW spr round 9 (radius: 20) [03:19:47 -36731.451303] SLOW spr round 10 (radius: 5) [03:21:09 -36724.735036] SLOW spr round 11 (radius: 5) [03:22:18 -36723.634695] SLOW spr round 12 (radius: 5) [03:23:19 -36723.634537] SLOW spr round 13 (radius: 10) [03:24:19 -36723.634535] SLOW spr round 14 (radius: 15) [03:24:29] [worker #2] ML tree search #15, logLikelihood: -36736.790309 [03:26:06 -36723.634533] SLOW spr round 15 (radius: 20) [03:28:19 -36723.606568] SLOW spr round 16 (radius: 25) [03:30:41 -36718.653668] SLOW spr round 17 (radius: 5) [03:31:02] [worker #1] ML tree search #14, logLikelihood: -36744.072866 [03:32:01 -36717.833321] SLOW spr round 18 (radius: 5) [03:33:09 -36717.832035] SLOW spr round 19 (radius: 10) [03:34:12 -36717.776278] SLOW spr round 20 (radius: 15) [03:35:55 -36717.775268] SLOW spr round 21 (radius: 20) [03:38:10 -36717.775101] SLOW spr round 22 (radius: 25) [03:40:30 -36717.476348] SLOW spr round 23 (radius: 5) [03:41:50 -36717.474378] SLOW spr round 24 (radius: 10) [03:42:59 -36717.474227] SLOW spr round 25 (radius: 15) [03:44:20 -36717.474217] SLOW spr round 26 (radius: 20) [03:46:13 -36717.474216] SLOW spr round 27 (radius: 25) [03:48:29 -36717.474216] Model parameter optimization (eps = 0.100000) [03:48:34] [worker #0] ML tree search #16, logLikelihood: -36717.357290 [03:48:35 -105391.634616] Initial branch length optimization [03:48:37 -92029.243868] Model parameter optimization (eps = 10.000000) [03:48:56 -91447.632391] AUTODETECT spr round 1 (radius: 5) [03:49:48 -61930.579415] AUTODETECT spr round 2 (radius: 10) [03:50:45 -47239.842305] AUTODETECT spr round 3 (radius: 15) [03:51:54 -42339.173701] AUTODETECT spr round 4 (radius: 20) [03:53:16 -40211.749627] AUTODETECT spr round 5 (radius: 25) [03:54:47 -40090.783071] SPR radius for FAST iterations: 25 (autodetect) [03:54:47 -40090.783071] Model parameter optimization (eps = 3.000000) [03:55:09 -39672.569311] FAST spr round 1 (radius: 25) [03:56:15 -36989.560092] FAST spr round 2 (radius: 25) [03:57:08 -36817.742144] FAST spr round 3 (radius: 25) [03:57:54 -36789.504018] FAST spr round 4 (radius: 25) [03:58:34 -36789.502831] Model parameter optimization (eps = 1.000000) [03:58:43 -36786.410658] SLOW spr round 1 (radius: 5) [03:59:46 -36777.589087] SLOW spr round 2 (radius: 5) [04:00:43 -36777.588206] SLOW spr round 3 (radius: 10) [04:01:00] [worker #2] ML tree search #18, logLikelihood: -36751.293537 [04:01:42 -36775.130941] SLOW spr round 4 (radius: 5) [04:02:38] [worker #1] ML tree search #17, logLikelihood: -36770.360238 [04:02:57 -36774.126353] SLOW spr round 5 (radius: 5) [04:04:02 -36774.095515] SLOW spr round 6 (radius: 10) [04:05:02 -36772.847268] SLOW spr round 7 (radius: 5) [04:06:18 -36770.300256] SLOW spr round 8 (radius: 5) [04:07:21 -36770.298627] SLOW spr round 9 (radius: 10) [04:08:21 -36769.696024] SLOW spr round 10 (radius: 5) [04:09:34 -36769.394393] SLOW spr round 11 (radius: 5) [04:10:38 -36769.392402] SLOW spr round 12 (radius: 10) [04:11:37 -36769.391587] SLOW spr round 13 (radius: 15) [04:13:20 -36766.182125] SLOW spr round 14 (radius: 5) [04:14:38 -36766.181860] SLOW spr round 15 (radius: 10) [04:15:50 -36766.181775] SLOW spr round 16 (radius: 15) [04:17:24 -36765.008218] SLOW spr round 17 (radius: 5) [04:18:42 -36765.008190] SLOW spr round 18 (radius: 10) [04:19:54 -36765.008183] SLOW spr round 19 (radius: 15) [04:21:28 -36765.008179] SLOW spr round 20 (radius: 20) [04:23:44 -36765.008178] SLOW spr round 21 (radius: 25) [04:26:06 -36765.008177] Model parameter optimization (eps = 0.100000) [04:26:11] [worker #0] ML tree search #19, logLikelihood: -36764.898619 [04:45:09] [worker #1] ML tree search #20, logLikelihood: -36730.720771 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.496732,0.676954) (0.012370,1.289982) (0.287227,1.271148) (0.203671,1.387876) 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: -36703.423111 AIC score: 75696.846223 / AICc score: 2700036.846223 / BIC score: 79225.054221 Free parameters (model + branch lengths): 1145 WARNING: Number of free parameters (K=1145) is larger than alignment size (n=161). 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/Q9BYR2/3_mltree/Q9BYR2.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/3_mltree/Q9BYR2.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/3_mltree/Q9BYR2.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BYR2/3_mltree/Q9BYR2.raxml.log Analysis started: 03-Jul-2021 09:26:39 / finished: 03-Jul-2021 14:11:49 Elapsed time: 17109.473 seconds Consumed energy: 1543.739 Wh (= 8 km in an electric car, or 39 km with an e-scooter!)