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 09:20:20 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/2_msa/P01566_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/3_mltree/P01566 --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/P01566/2_msa/P01566_trimmed_msa.fasta [00:00:00] Loaded alignment with 660 taxa and 188 sites WARNING: Sequences tr_A0A2I3T4W8_A0A2I3T4W8_PANTR_9598 and tr_A0A2R8ZIR7_A0A2R8ZIR7_PANPA_9597 are exactly identical! WARNING: Sequences tr_H2QX24_H2QX24_PANTR_9598 and sp_P01568_IFN21_HUMAN_9606 are exactly identical! WARNING: Sequences tr_H2QX26_H2QX26_PANTR_9598 and tr_A0A2R8ZJA8_A0A2R8ZJA8_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A1D5QAU5_A0A1D5QAU5_MACMU_9544 and tr_G7PS88_G7PS88_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A1D5QAU5_A0A1D5QAU5_MACMU_9544 and tr_A0A2K6CIE3_A0A2K6CIE3_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A2I2UKA0_A0A2I2UKA0_FELCA_9685 and tr_M3WSK5_M3WSK5_FELCA_9685 are exactly identical! WARNING: Sequences tr_A0A096NBJ9_A0A096NBJ9_PAPAN_9555 and tr_B6CK13_B6CK13_CERAT_9531 are exactly identical! WARNING: Sequences tr_A0A1S3QQ44_A0A1S3QQ44_SALSA_8030 and tr_A0A1S3S6R6_A0A1S3S6R6_SALSA_8030 are exactly identical! WARNING: Duplicate sequences found: 8 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/P01566/3_mltree/P01566.raxml.reduced.phy Alignment comprises 1 partitions and 188 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 188 / 188 Gaps: 5.10 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/3_mltree/P01566.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 660 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 188 / 15040 [00:00:00] Data distribution: max. searches per worker: 5 Starting ML tree search with 20 distinct starting trees [00:00:00 -214679.042304] Initial branch length optimization [00:00:02 -180219.693206] Model parameter optimization (eps = 10.000000) [00:00:31 -179637.040557] AUTODETECT spr round 1 (radius: 5) [00:01:49 -138793.478387] AUTODETECT spr round 2 (radius: 10) [00:03:15 -102013.502220] AUTODETECT spr round 3 (radius: 15) [00:05:06 -82337.549210] AUTODETECT spr round 4 (radius: 20) [00:07:28 -75725.907282] AUTODETECT spr round 5 (radius: 25) [00:10:31 -75278.549304] SPR radius for FAST iterations: 25 (autodetect) [00:10:31 -75278.549304] Model parameter optimization (eps = 3.000000) [00:10:48 -75175.111758] FAST spr round 1 (radius: 25) [00:12:11 -63371.482335] FAST spr round 2 (radius: 25) [00:13:20 -62902.849196] FAST spr round 3 (radius: 25) [00:14:20 -62874.059570] FAST spr round 4 (radius: 25) [00:15:11 -62870.334099] FAST spr round 5 (radius: 25) [00:16:02 -62870.334093] Model parameter optimization (eps = 1.000000) [00:16:15 -62867.367306] SLOW spr round 1 (radius: 5) [00:17:41 -62851.618941] SLOW spr round 2 (radius: 5) [00:18:58 -62849.389167] SLOW spr round 3 (radius: 5) [00:20:16 -62849.160101] SLOW spr round 4 (radius: 5) [00:21:31 -62849.160088] SLOW spr round 5 (radius: 10) [00:22:51 -62844.517349] SLOW spr round 6 (radius: 5) [00:24:33 -62844.110072] SLOW spr round 7 (radius: 5) [00:26:00 -62844.110060] SLOW spr round 8 (radius: 10) [00:27:21 -62844.110060] SLOW spr round 9 (radius: 15) [00:30:09 -62844.110060] SLOW spr round 10 (radius: 20) [00:34:25 -62844.110060] SLOW spr round 11 (radius: 25) [00:34:30] [worker #1] ML tree search #2, logLikelihood: -62872.619362 [00:39:11 -62844.110060] Model parameter optimization (eps = 0.100000) [00:39:19] [worker #0] ML tree search #1, logLikelihood: -62843.628778 [00:39:19 -214499.510379] Initial branch length optimization [00:39:22 -180409.017872] Model parameter optimization (eps = 10.000000) [00:39:49 -179869.979061] AUTODETECT spr round 1 (radius: 5) [00:41:07 -136801.920410] AUTODETECT spr round 2 (radius: 10) [00:42:31] [worker #2] ML tree search #3, logLikelihood: -62852.758760 [00:42:39 -96164.751467] AUTODETECT spr round 3 (radius: 15) [00:44:25] [worker #3] ML tree search #4, logLikelihood: -62864.110495 [00:44:27 -77343.479907] AUTODETECT spr round 4 (radius: 20) [00:46:30 -73586.119985] AUTODETECT spr round 5 (radius: 25) [00:48:49 -73340.441730] SPR radius for FAST iterations: 25 (autodetect) [00:48:49 -73340.441730] Model parameter optimization (eps = 3.000000) [00:49:15 -73230.412607] FAST spr round 1 (radius: 25) [00:50:39 -63261.967208] FAST spr round 2 (radius: 25) [00:51:46 -62926.233923] FAST spr round 3 (radius: 25) [00:52:48 -62912.369256] FAST spr round 4 (radius: 25) [00:53:42 -62907.722643] FAST spr round 5 (radius: 25) [00:54:36 -62906.592297] FAST spr round 6 (radius: 25) [00:55:28 -62906.592133] Model parameter optimization (eps = 1.000000) [00:55:37 -62904.420003] SLOW spr round 1 (radius: 5) [00:57:02 -62888.871543] SLOW spr round 2 (radius: 5) [00:58:24 -62881.198588] SLOW spr round 3 (radius: 5) [00:59:40 -62881.197798] SLOW spr round 4 (radius: 10) [01:00:58 -62880.882027] SLOW spr round 5 (radius: 5) [01:02:40 -62880.292899] SLOW spr round 6 (radius: 5) [01:04:08 -62880.292899] SLOW spr round 7 (radius: 10) [01:05:29 -62880.245590] SLOW spr round 8 (radius: 15) [01:08:12 -62880.245327] SLOW spr round 9 (radius: 20) [01:10:13] [worker #1] ML tree search #6, logLikelihood: -62878.026540 [01:12:22 -62880.245323] SLOW spr round 10 (radius: 25) [01:16:59 -62880.245323] Model parameter optimization (eps = 0.100000) [01:17:04] [worker #0] ML tree search #5, logLikelihood: -62880.236209 [01:17:04 -214189.469931] Initial branch length optimization [01:17:06 -179704.276119] Model parameter optimization (eps = 10.000000) [01:17:32 -179172.064857] AUTODETECT spr round 1 (radius: 5) [01:18:51 -136429.201403] AUTODETECT spr round 2 (radius: 10) [01:20:22 -98416.400284] AUTODETECT spr round 3 (radius: 15) [01:22:15] [worker #3] ML tree search #8, logLikelihood: -62854.038279 [01:22:16 -77849.017707] AUTODETECT spr round 4 (radius: 20) [01:24:37 -75141.905768] AUTODETECT spr round 5 (radius: 25) [01:25:24] [worker #2] ML tree search #7, logLikelihood: -62882.389394 [01:27:45 -72787.013163] SPR radius for FAST iterations: 25 (autodetect) [01:27:45 -72787.013163] Model parameter optimization (eps = 3.000000) [01:28:02 -72674.880700] FAST spr round 1 (radius: 25) [01:29:27 -63576.762931] FAST spr round 2 (radius: 25) [01:30:35 -62945.722165] FAST spr round 3 (radius: 25) [01:31:41 -62885.883462] FAST spr round 4 (radius: 25) [01:32:38 -62881.275014] FAST spr round 5 (radius: 25) [01:33:31 -62879.987833] FAST spr round 6 (radius: 25) [01:34:24 -62879.987771] Model parameter optimization (eps = 1.000000) [01:34:37 -62878.041040] SLOW spr round 1 (radius: 5) [01:36:05 -62855.459840] SLOW spr round 2 (radius: 5) [01:37:31 -62847.461404] SLOW spr round 3 (radius: 5) [01:38:50 -62844.846031] SLOW spr round 4 (radius: 5) [01:40:07 -62844.846029] SLOW spr round 5 (radius: 10) [01:41:26 -62844.846029] SLOW spr round 6 (radius: 15) [01:44:14 -62844.846029] SLOW spr round 7 (radius: 20) [01:48:23 -62844.846029] SLOW spr round 8 (radius: 25) [01:51:04] [worker #1] ML tree search #10, logLikelihood: -62852.369477 [01:52:58 -62844.846029] Model parameter optimization (eps = 0.100000) [01:53:06] [worker #0] ML tree search #9, logLikelihood: -62844.588093 [01:53:06 -215580.419260] Initial branch length optimization [01:53:08 -180644.053159] Model parameter optimization (eps = 10.000000) [01:53:37 -179945.509632] AUTODETECT spr round 1 (radius: 5) [01:54:55 -137758.900420] AUTODETECT spr round 2 (radius: 10) [01:56:24 -93231.541124] AUTODETECT spr round 3 (radius: 15) [01:58:18 -81830.218838] AUTODETECT spr round 4 (radius: 20) [02:00:53 -74366.582741] AUTODETECT spr round 5 (radius: 25) [02:04:00 -73995.297589] SPR radius for FAST iterations: 25 (autodetect) [02:04:00 -73995.297589] Model parameter optimization (eps = 3.000000) [02:04:16] [worker #3] ML tree search #12, logLikelihood: -62884.190232 [02:04:18 -73923.710650] FAST spr round 1 (radius: 25) [02:04:27] [worker #2] ML tree search #11, logLikelihood: -62858.792140 [02:05:40 -63497.837402] FAST spr round 2 (radius: 25) [02:06:47 -62948.746306] FAST spr round 3 (radius: 25) [02:07:46 -62909.857195] FAST spr round 4 (radius: 25) [02:08:40 -62903.040556] FAST spr round 5 (radius: 25) [02:09:31 -62903.040185] Model parameter optimization (eps = 1.000000) [02:09:45 -62899.633984] SLOW spr round 1 (radius: 5) [02:11:09 -62874.737120] SLOW spr round 2 (radius: 5) [02:12:26 -62874.120686] SLOW spr round 3 (radius: 5) [02:13:42 -62874.120500] SLOW spr round 4 (radius: 10) [02:15:01 -62873.568855] SLOW spr round 5 (radius: 5) [02:16:41 -62873.568845] SLOW spr round 6 (radius: 10) [02:18:08 -62873.568841] SLOW spr round 7 (radius: 15) [02:20:36 -62873.568840] SLOW spr round 8 (radius: 20) [02:24:48 -62873.568840] SLOW spr round 9 (radius: 25) [02:29:00] [worker #1] ML tree search #14, logLikelihood: -62873.821113 [02:29:28 -62873.568840] Model parameter optimization (eps = 0.100000) [02:29:32] [worker #0] ML tree search #13, logLikelihood: -62873.546265 [02:29:32 -214594.376013] Initial branch length optimization [02:29:35 -180225.634022] Model parameter optimization (eps = 10.000000) [02:30:00 -179532.488398] AUTODETECT spr round 1 (radius: 5) [02:31:18 -139832.821714] AUTODETECT spr round 2 (radius: 10) [02:32:49 -93517.980682] AUTODETECT spr round 3 (radius: 15) [02:34:40 -79899.941851] AUTODETECT spr round 4 (radius: 20) [02:37:05 -74881.273331] AUTODETECT spr round 5 (radius: 25) [02:39:49 -73831.083091] SPR radius for FAST iterations: 25 (autodetect) [02:39:49 -73831.083091] Model parameter optimization (eps = 3.000000) [02:40:06 -73755.555417] FAST spr round 1 (radius: 25) [02:41:27] [worker #2] ML tree search #15, logLikelihood: -62867.528249 [02:41:27 -63372.605507] FAST spr round 2 (radius: 25) [02:42:34 -62919.326527] FAST spr round 3 (radius: 25) [02:43:33 -62900.858219] FAST spr round 4 (radius: 25) [02:44:26 -62895.235727] FAST spr round 5 (radius: 25) [02:45:17 -62895.235726] Model parameter optimization (eps = 1.000000) [02:45:28 -62892.520808] SLOW spr round 1 (radius: 5) [02:46:52 -62878.710292] SLOW spr round 2 (radius: 5) [02:48:13 -62875.765070] SLOW spr round 3 (radius: 5) [02:49:26] [worker #3] ML tree search #16, logLikelihood: -62866.598053 [02:49:30 -62875.650071] SLOW spr round 4 (radius: 5) [02:50:44 -62875.649906] SLOW spr round 5 (radius: 10) [02:52:02 -62875.649879] SLOW spr round 6 (radius: 15) [02:54:48 -62875.649865] SLOW spr round 7 (radius: 20) [02:58:54 -62875.649856] SLOW spr round 8 (radius: 25) [03:03:35 -62875.649850] Model parameter optimization (eps = 0.100000) [03:03:44] [worker #0] ML tree search #17, logLikelihood: -62874.922327 [03:06:29] [worker #1] ML tree search #18, logLikelihood: -62879.041220 [03:14:39] [worker #2] ML tree search #19, logLikelihood: -62865.549566 [03:23:41] [worker #3] ML tree search #20, logLikelihood: -62864.715408 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.132570,0.533751) (0.055934,0.625938) (0.421296,0.784311) (0.390200,1.444907) 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: -62843.628778 AIC score: 128333.257557 / AICc score: 3631637.257557 / BIC score: 132615.070274 Free parameters (model + branch lengths): 1323 WARNING: Number of free parameters (K=1323) is larger than alignment size (n=188). 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/P01566/3_mltree/P01566.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/3_mltree/P01566.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/3_mltree/P01566.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P01566/3_mltree/P01566.raxml.log Analysis started: 06-Jul-2021 09:20:20 / finished: 06-Jul-2021 12:44:02 Elapsed time: 12221.815 seconds Consumed energy: 1110.816 Wh (= 6 km in an electric car, or 28 km with an e-scooter!)