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 06-Jul-2021 23:26:24 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/2_msa/Q86TP1_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1 --seed 2 --threads 4 --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 (4 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/2_msa/Q86TP1_trimmed_msa.fasta [00:00:00] Loaded alignment with 276 taxa and 195 sites WARNING: Sequences tr_G3QLH9_G3QLH9_GORGO_9595 and tr_A0A2I3TIP7_A0A2I3TIP7_PANTR_9598 are exactly identical! WARNING: Sequences tr_G3QLH9_G3QLH9_GORGO_9595 and sp_Q8WUY3_PRUN2_HUMAN_9606 are exactly identical! WARNING: Sequences tr_G3QLH9_G3QLH9_GORGO_9595 and tr_A0A2R9AC58_A0A2R9AC58_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A1D5QMC1_A0A1D5QMC1_MACMU_9544 and tr_G7PSK4_G7PSK4_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A1D5QMC1_A0A1D5QMC1_MACMU_9544 and tr_A0A096P1T8_A0A096P1T8_PAPAN_9555 are exactly identical! WARNING: Sequences tr_A0A1D5QMC1_A0A1D5QMC1_MACMU_9544 and tr_A0A2K6CS71_A0A2K6CS71_MACNE_9545 are exactly identical! WARNING: Sequences tr_F6T7J4_F6T7J4_MACMU_9544 and tr_G8F5T6_G8F5T6_MACFA_9541 are exactly identical! WARNING: Sequences tr_F6T7J4_F6T7J4_MACMU_9544 and tr_A0A2K5P5J4_A0A2K5P5J4_CERAT_9531 are exactly identical! WARNING: Sequences tr_F6T7J4_F6T7J4_MACMU_9544 and tr_A0A2K6BPQ0_A0A2K6BPQ0_MACNE_9545 are exactly identical! WARNING: Sequences tr_F6T7J4_F6T7J4_MACMU_9544 and tr_A0A2K5ZS61_A0A2K5ZS61_MANLE_9568 are exactly identical! WARNING: Sequences tr_W2PK54_W2PK54_PHYPN_761204 and tr_A0A0W8CW18_A0A0W8CW18_PHYNI_4790 are exactly identical! WARNING: Sequences tr_A0A2I0MFZ9_A0A2I0MFZ9_COLLI_8932 and tr_A0A1V4KCW6_A0A1V4KCW6_PATFA_372326 are exactly identical! WARNING: Sequences tr_A0A2D0RU12_A0A2D0RU12_ICTPU_7998 and tr_A0A2D0RUZ5_A0A2D0RUZ5_ICTPU_7998 are exactly identical! WARNING: Duplicate sequences found: 13 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/Q86TP1/3_mltree/Q86TP1.raxml.reduced.phy Alignment comprises 1 partitions and 195 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 195 / 195 Gaps: 9.83 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.rba Parallelization scheme autoconfig: 4 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 276 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 195 / 15600 [00:00:00] Data distribution: max. searches per worker: 5 Starting ML tree search with 20 distinct starting trees [00:00:00 -89165.450361] Initial branch length optimization [00:00:00 -72698.508058] Model parameter optimization (eps = 10.000000) [00:00:11 -72375.389925] AUTODETECT spr round 1 (radius: 5) [00:00:27 -52266.360244] AUTODETECT spr round 2 (radius: 10) [00:00:49 -43308.148561] AUTODETECT spr round 3 (radius: 15) [00:01:15 -38185.160851] AUTODETECT spr round 4 (radius: 20) [00:01:42 -36125.382346] AUTODETECT spr round 5 (radius: 25) [00:02:07 -36121.862263] SPR radius for FAST iterations: 25 (autodetect) [00:02:07 -36121.862263] Model parameter optimization (eps = 3.000000) [00:02:14 -36037.119984] FAST spr round 1 (radius: 25) [00:02:38 -33620.035160] FAST spr round 2 (radius: 25) [00:02:58 -33430.194563] FAST spr round 3 (radius: 25) [00:03:13 -33416.618862] FAST spr round 4 (radius: 25) [00:03:26 -33415.888456] FAST spr round 5 (radius: 25) [00:03:39 -33415.847047] Model parameter optimization (eps = 1.000000) [00:03:43 -33411.705593] SLOW spr round 1 (radius: 5) [00:04:09 -33405.185804] SLOW spr round 2 (radius: 5) [00:04:34 -33402.498469] SLOW spr round 3 (radius: 5) [00:04:58 -33401.661990] SLOW spr round 4 (radius: 5) [00:05:22 -33394.839244] SLOW spr round 5 (radius: 5) [00:05:45 -33394.836657] SLOW spr round 6 (radius: 10) [00:06:07 -33393.230499] SLOW spr round 7 (radius: 5) [00:06:40 -33392.770940] SLOW spr round 8 (radius: 5) [00:07:07 -33392.770877] SLOW spr round 9 (radius: 10) [00:07:30 -33392.770869] SLOW spr round 10 (radius: 15) [00:08:09 -33392.770867] SLOW spr round 11 (radius: 20) [00:08:40] [worker #2] ML tree search #3, logLikelihood: -33392.624625 [00:08:43] [worker #1] ML tree search #2, logLikelihood: -33401.952192 [00:08:50] [worker #3] ML tree search #4, logLikelihood: -33392.209789 [00:08:58 -33392.770867] SLOW spr round 12 (radius: 25) [00:09:54 -33392.770867] Model parameter optimization (eps = 0.100000) [00:09:57] [worker #0] ML tree search #1, logLikelihood: -33392.598200 [00:09:57 -88224.046693] Initial branch length optimization [00:09:58 -73164.863158] Model parameter optimization (eps = 10.000000) [00:10:09 -72754.339018] AUTODETECT spr round 1 (radius: 5) [00:10:25 -52361.818426] AUTODETECT spr round 2 (radius: 10) [00:10:45 -42752.338517] AUTODETECT spr round 3 (radius: 15) [00:11:11 -37334.151606] AUTODETECT spr round 4 (radius: 20) [00:11:44 -36165.089778] AUTODETECT spr round 5 (radius: 25) [00:12:23 -35922.505898] SPR radius for FAST iterations: 25 (autodetect) [00:12:23 -35922.505898] Model parameter optimization (eps = 3.000000) [00:12:31 -35847.415090] FAST spr round 1 (radius: 25) [00:12:52 -33658.611429] FAST spr round 2 (radius: 25) [00:13:11 -33437.777870] FAST spr round 3 (radius: 25) [00:13:26 -33416.922358] FAST spr round 4 (radius: 25) [00:13:40 -33411.872642] FAST spr round 5 (radius: 25) [00:13:54 -33410.353608] FAST spr round 6 (radius: 25) [00:14:07 -33410.353250] Model parameter optimization (eps = 1.000000) [00:14:11 -33408.020808] SLOW spr round 1 (radius: 5) [00:14:37 -33404.017307] SLOW spr round 2 (radius: 5) [00:15:01 -33403.544763] SLOW spr round 3 (radius: 5) [00:15:24 -33403.544307] SLOW spr round 4 (radius: 10) [00:15:48 -33401.470469] SLOW spr round 5 (radius: 5) [00:16:11] [worker #2] ML tree search #7, logLikelihood: -33395.966514 [00:16:20 -33401.432273] SLOW spr round 6 (radius: 10) [00:16:47 -33401.432145] SLOW spr round 7 (radius: 15) [00:17:24 -33401.432131] SLOW spr round 8 (radius: 20) [00:18:07] [worker #3] ML tree search #8, logLikelihood: -33389.512454 [00:18:19 -33401.432124] SLOW spr round 9 (radius: 25) [00:19:16 -33401.432120] Model parameter optimization (eps = 0.100000) [00:19:17] [worker #0] ML tree search #5, logLikelihood: -33401.386795 [00:19:17 -86661.979156] Initial branch length optimization [00:19:18 -70638.247005] Model parameter optimization (eps = 10.000000) [00:19:29 -70235.451701] AUTODETECT spr round 1 (radius: 5) [00:19:45 -52810.470536] AUTODETECT spr round 2 (radius: 10) [00:19:54] [worker #1] ML tree search #6, logLikelihood: -33396.317118 [00:20:06 -40565.698974] AUTODETECT spr round 3 (radius: 15) [00:20:33 -36814.047630] AUTODETECT spr round 4 (radius: 20) [00:21:00 -36286.084110] AUTODETECT spr round 5 (radius: 25) [00:21:31 -36239.741118] SPR radius for FAST iterations: 25 (autodetect) [00:21:31 -36239.741118] Model parameter optimization (eps = 3.000000) [00:21:37 -36181.552072] FAST spr round 1 (radius: 25) [00:22:00 -33475.245166] FAST spr round 2 (radius: 25) [00:22:16 -33418.733139] FAST spr round 3 (radius: 25) [00:22:30 -33412.211609] FAST spr round 4 (radius: 25) [00:22:44 -33410.476173] FAST spr round 5 (radius: 25) [00:22:57 -33407.700785] FAST spr round 6 (radius: 25) [00:23:09 -33407.699200] Model parameter optimization (eps = 1.000000) [00:23:14 -33403.959385] SLOW spr round 1 (radius: 5) [00:23:40 -33397.630908] SLOW spr round 2 (radius: 5) [00:24:04 -33397.439264] SLOW spr round 3 (radius: 5) [00:24:05] [worker #2] ML tree search #11, logLikelihood: -33398.262092 [00:24:28 -33397.439117] SLOW spr round 4 (radius: 10) [00:24:50 -33395.913837] SLOW spr round 5 (radius: 5) [00:25:23 -33395.446188] SLOW spr round 6 (radius: 5) [00:25:51 -33395.445948] SLOW spr round 7 (radius: 10) [00:26:14 -33395.322456] SLOW spr round 8 (radius: 5) [00:26:43] [worker #3] ML tree search #12, logLikelihood: -33393.177021 [00:26:46 -33395.322456] SLOW spr round 9 (radius: 10) [00:27:13 -33395.322456] SLOW spr round 10 (radius: 15) [00:27:48 -33395.322456] SLOW spr round 11 (radius: 20) [00:28:35 -33395.322456] SLOW spr round 12 (radius: 25) [00:29:31 -33395.322456] Model parameter optimization (eps = 0.100000) [00:29:36] [worker #0] ML tree search #9, logLikelihood: -33395.300316 [00:29:36 -87301.858777] Initial branch length optimization [00:29:36 -71532.971375] Model parameter optimization (eps = 10.000000) [00:29:48 -71197.817918] AUTODETECT spr round 1 (radius: 5) [00:30:03 -52707.926229] AUTODETECT spr round 2 (radius: 10) [00:30:23 -43213.168421] AUTODETECT spr round 3 (radius: 15) [00:30:49 -38958.282024] AUTODETECT spr round 4 (radius: 20) [00:31:20 -36897.575959] AUTODETECT spr round 5 (radius: 25) [00:31:51 -36883.991744] SPR radius for FAST iterations: 25 (autodetect) [00:31:51 -36883.991744] Model parameter optimization (eps = 3.000000) [00:31:58 -36797.025547] FAST spr round 1 (radius: 25) [00:31:59] [worker #1] ML tree search #10, logLikelihood: -33394.234185 [00:32:20 -33961.429166] FAST spr round 2 (radius: 25) [00:32:40 -33454.193941] FAST spr round 3 (radius: 25) [00:32:58 -33405.145103] FAST spr round 4 (radius: 25) [00:33:12 -33400.868460] FAST spr round 5 (radius: 25) [00:33:13] [worker #2] ML tree search #15, logLikelihood: -33391.831547 [00:33:25 -33400.868312] Model parameter optimization (eps = 1.000000) [00:33:29 -33398.714377] SLOW spr round 1 (radius: 5) [00:33:55 -33394.694606] SLOW spr round 2 (radius: 5) [00:34:20 -33394.526288] SLOW spr round 3 (radius: 5) [00:34:44 -33394.349523] SLOW spr round 4 (radius: 5) [00:35:08 -33394.349083] SLOW spr round 5 (radius: 10) [00:35:31 -33393.865325] SLOW spr round 6 (radius: 5) [00:35:51] [worker #3] ML tree search #16, logLikelihood: -33395.418763 [00:36:04 -33393.864855] SLOW spr round 7 (radius: 10) [00:36:31 -33393.864755] SLOW spr round 8 (radius: 15) [00:37:07 -33393.864721] SLOW spr round 9 (radius: 20) [00:37:55 -33393.864705] SLOW spr round 10 (radius: 25) [00:38:50 -33393.864696] Model parameter optimization (eps = 0.100000) [00:38:51] [worker #0] ML tree search #13, logLikelihood: -33393.862029 [00:38:51 -86645.117140] Initial branch length optimization [00:38:52 -70244.018672] Model parameter optimization (eps = 10.000000) [00:39:04 -69879.354550] AUTODETECT spr round 1 (radius: 5) [00:39:19 -52119.498738] AUTODETECT spr round 2 (radius: 10) [00:39:39 -43332.235125] AUTODETECT spr round 3 (radius: 15) [00:40:02 -37414.696824] AUTODETECT spr round 4 (radius: 20) [00:40:33 -36590.395030] AUTODETECT spr round 5 (radius: 25) [00:41:04 -36570.772002] SPR radius for FAST iterations: 25 (autodetect) [00:41:04 -36570.772002] Model parameter optimization (eps = 3.000000) [00:41:12 -36525.618341] FAST spr round 1 (radius: 25) [00:41:29] [worker #1] ML tree search #14, logLikelihood: -33399.021357 [00:41:36 -33527.310770] FAST spr round 2 (radius: 25) [00:41:56 -33421.927574] FAST spr round 3 (radius: 25) [00:42:11 -33416.214119] FAST spr round 4 (radius: 25) [00:42:24 -33412.754532] FAST spr round 5 (radius: 25) [00:42:37 -33410.629066] FAST spr round 6 (radius: 25) [00:42:50 -33410.629004] Model parameter optimization (eps = 1.000000) [00:42:55 -33407.007167] SLOW spr round 1 (radius: 5) [00:43:24 -33397.370787] SLOW spr round 2 (radius: 5) [00:43:48 -33396.851121] SLOW spr round 3 (radius: 5) [00:44:11 -33396.850956] SLOW spr round 4 (radius: 10) [00:44:12] [worker #2] ML tree search #19, logLikelihood: -33402.151853 [00:44:34 -33394.998569] SLOW spr round 5 (radius: 5) [00:44:42] [worker #3] ML tree search #20, logLikelihood: -33394.801309 [00:45:07 -33393.382703] SLOW spr round 6 (radius: 5) [00:45:34 -33393.382627] SLOW spr round 7 (radius: 10) [00:45:57 -33392.837665] SLOW spr round 8 (radius: 5) [00:46:29 -33392.791131] SLOW spr round 9 (radius: 10) [00:46:55 -33392.791130] SLOW spr round 10 (radius: 15) [00:47:32 -33392.791130] SLOW spr round 11 (radius: 20) [00:48:27 -33392.791129] SLOW spr round 12 (radius: 25) [00:49:25 -33392.791129] Model parameter optimization (eps = 0.100000) [00:49:27] [worker #0] ML tree search #17, logLikelihood: -33392.776870 [00:49:36] [worker #1] ML tree search #18, logLikelihood: -33397.748711 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.226067,0.435670) (0.228876,0.537768) (0.281803,0.844825) (0.263254,2.052593) 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: -33389.512454 AIC score: 67889.024909 / AICc score: 685049.024909 / BIC score: 69705.539664 Free parameters (model + branch lengths): 555 WARNING: Number of free parameters (K=555) is larger than alignment size (n=195). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 34 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86TP1/3_mltree/Q86TP1.raxml.log Analysis started: 06-Jul-2021 23:26:24 / finished: 07-Jul-2021 00:16:01 Elapsed time: 2976.928 seconds Consumed energy: 253.574 Wh (= 1 km in an electric car, or 6 km with an e-scooter!)