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 16:57:48 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/2_msa/Q8N162_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/3_mltree/Q8N162 --seed 2 --threads 5 --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 (5 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/2_msa/Q8N162_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 313 sites WARNING: Sequences tr_F7HC70_F7HC70_MACMU_9544 and tr_G7PS82_G7PS82_MACFA_9541 are exactly identical! WARNING: Duplicate sequences found: 1 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/Q8N162/3_mltree/Q8N162.raxml.reduced.phy Alignment comprises 1 partitions and 313 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 313 / 313 Gaps: 1.47 % Invariant sites: 0.32 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/3_mltree/Q8N162.raxml.rba Parallelization scheme autoconfig: 5 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 1001 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 313 / 25040 [00:00:00] Data distribution: max. searches per worker: 4 Starting ML tree search with 20 distinct starting trees [00:00:00 -448115.526603] Initial branch length optimization [00:00:11 -395866.263592] Model parameter optimization (eps = 10.000000) [00:03:16 -394831.007366] AUTODETECT spr round 1 (radius: 5) [00:11:29 -294498.079572] AUTODETECT spr round 2 (radius: 10) [00:19:55 -210896.437944] AUTODETECT spr round 3 (radius: 15) [00:28:54 -180145.793968] AUTODETECT spr round 4 (radius: 20) [00:40:46 -173787.416548] AUTODETECT spr round 5 (radius: 25) [00:56:12 -173226.234602] SPR radius for FAST iterations: 25 (autodetect) [00:56:12 -173226.234602] Model parameter optimization (eps = 3.000000) [00:57:16 -172681.257640] FAST spr round 1 (radius: 25) [01:07:34 -153307.656617] FAST spr round 2 (radius: 25) [01:14:40 -152342.569986] FAST spr round 3 (radius: 25) [01:21:22 -152268.091677] FAST spr round 4 (radius: 25) [01:27:18 -152248.893763] FAST spr round 5 (radius: 25) [01:33:00 -152239.363173] FAST spr round 6 (radius: 25) [01:38:28 -152234.625506] FAST spr round 7 (radius: 25) [01:38:29] [worker #1] ML tree search #2, logLikelihood: -152171.514461 [01:43:58 -152226.665798] FAST spr round 8 (radius: 25) [01:48:35 -152226.665786] Model parameter optimization (eps = 1.000000) [01:49:11 -152223.258566] SLOW spr round 1 (radius: 5) [01:56:50 -152183.517536] SLOW spr round 2 (radius: 5) [02:04:20 -152172.594200] SLOW spr round 3 (radius: 5) [02:11:04 -152170.263275] SLOW spr round 4 (radius: 5) [02:17:44 -152165.412248] SLOW spr round 5 (radius: 5) [02:18:44] [worker #2] ML tree search #3, logLikelihood: -152168.894172 [02:24:19 -152165.412247] SLOW spr round 6 (radius: 10) [02:31:01 -152165.412247] SLOW spr round 7 (radius: 15) [02:43:55] [worker #3] ML tree search #4, logLikelihood: -152156.846681 [02:44:12 -152165.412247] SLOW spr round 8 (radius: 20) [03:08:13 -152165.412247] SLOW spr round 9 (radius: 25) [03:21:09] [worker #1] ML tree search #7, logLikelihood: -152186.950192 [03:38:11 -152165.412247] Model parameter optimization (eps = 0.100000) [03:38:22] [worker #0] ML tree search #1, logLikelihood: -152165.405767 [03:38:22 -447562.558506] Initial branch length optimization [03:38:35 -395334.471083] Model parameter optimization (eps = 10.000000) [03:40:54 -394357.864821] AUTODETECT spr round 1 (radius: 5) [03:48:14 -290873.250118] AUTODETECT spr round 2 (radius: 10) [03:56:50 -209832.338901] AUTODETECT spr round 3 (radius: 15) [04:07:00 -176758.080604] AUTODETECT spr round 4 (radius: 20) [04:10:26] [worker #2] ML tree search #8, logLikelihood: -152161.467350 [04:20:25 -170333.605238] AUTODETECT spr round 5 (radius: 25) [04:38:28 -170002.787576] SPR radius for FAST iterations: 25 (autodetect) [04:38:28 -170002.787576] Model parameter optimization (eps = 3.000000) [04:39:24 -169564.697225] FAST spr round 1 (radius: 25) [04:49:14 -152886.764031] FAST spr round 2 (radius: 25) [04:56:32 -152317.536507] FAST spr round 3 (radius: 25) [05:02:41 -152255.167355] FAST spr round 4 (radius: 25) [05:03:35] [worker #3] ML tree search #9, logLikelihood: -152185.398528 [05:07:54 -152247.507519] FAST spr round 5 (radius: 25) [05:10:33] [worker #1] ML tree search #12, logLikelihood: -152158.014589 [05:13:06 -152247.379546] FAST spr round 6 (radius: 25) [05:18:10 -152245.927464] FAST spr round 7 (radius: 25) [05:23:19 -152243.763926] FAST spr round 8 (radius: 25) [05:28:00 -152243.613110] FAST spr round 9 (radius: 25) [05:32:49 -152243.562951] Model parameter optimization (eps = 1.000000) [05:33:37 -152235.317901] SLOW spr round 1 (radius: 5) [05:41:22 -152170.331566] SLOW spr round 2 (radius: 5) [05:48:13 -152160.207423] SLOW spr round 3 (radius: 5) [05:48:19] [worker #2] ML tree search #13, logLikelihood: -152219.400208 [05:55:25 -152158.069477] SLOW spr round 4 (radius: 5) [06:01:18] [worker #4] ML tree search #5, logLikelihood: -152170.057837 [06:02:17 -152157.536928] SLOW spr round 5 (radius: 5) [06:08:46 -152157.536927] SLOW spr round 6 (radius: 10) [06:16:00 -152155.172149] SLOW spr round 7 (radius: 5) [06:24:31 -152154.659232] SLOW spr round 8 (radius: 5) [06:32:18 -152154.659221] SLOW spr round 9 (radius: 10) [06:39:35 -152154.227162] SLOW spr round 10 (radius: 5) [06:48:17 -152153.109014] SLOW spr round 11 (radius: 5) [06:48:57] [worker #3] ML tree search #14, logLikelihood: -152136.827938 [06:56:13 -152153.109014] SLOW spr round 12 (radius: 10) [07:03:21 -152153.109014] SLOW spr round 13 (radius: 15) [07:16:06 -152153.109014] SLOW spr round 14 (radius: 20) [07:27:09] [worker #1] ML tree search #17, logLikelihood: -152156.392211 [07:40:52 -152153.109014] SLOW spr round 15 (radius: 25) [07:49:04] [worker #2] ML tree search #18, logLikelihood: -152163.795067 [08:10:31 -152153.109014] Model parameter optimization (eps = 0.100000) [08:10:56] [worker #0] ML tree search #6, logLikelihood: -152152.987515 [08:10:56 -446984.034265] Initial branch length optimization [08:11:09 -394074.156640] Model parameter optimization (eps = 10.000000) [08:13:24 -393187.157708] AUTODETECT spr round 1 (radius: 5) [08:20:58 -293057.674947] AUTODETECT spr round 2 (radius: 10) [08:29:07 -216519.593113] AUTODETECT spr round 3 (radius: 15) [08:37:15 -181785.100775] AUTODETECT spr round 4 (radius: 20) [08:40:43] [worker #3] ML tree search #19, logLikelihood: -152147.656085 [08:46:08 -175672.218564] AUTODETECT spr round 5 (radius: 25) [08:57:36 -173636.847721] SPR radius for FAST iterations: 25 (autodetect) [08:57:36 -173636.847721] Model parameter optimization (eps = 3.000000) [08:58:21 -173312.938227] FAST spr round 1 (radius: 25) [09:06:16 -152969.753259] FAST spr round 2 (radius: 25) [09:12:04 -152327.770462] FAST spr round 3 (radius: 25) [09:17:01 -152250.552563] FAST spr round 4 (radius: 25) [09:21:20 -152242.103059] FAST spr round 5 (radius: 25) [09:25:17 -152239.230413] FAST spr round 6 (radius: 25) [09:29:07 -152238.745762] FAST spr round 7 (radius: 25) [09:33:02 -152237.781139] FAST spr round 8 (radius: 25) [09:36:52 -152231.738267] FAST spr round 9 (radius: 25) [09:40:38 -152227.892377] FAST spr round 10 (radius: 25) [09:44:18 -152226.439145] FAST spr round 11 (radius: 25) [09:48:05 -152225.575359] FAST spr round 12 (radius: 25) [09:51:34] [worker #4] ML tree search #10, logLikelihood: -152163.099792 [09:52:10 -152224.683239] FAST spr round 13 (radius: 25) [09:56:11 -152224.430820] FAST spr round 14 (radius: 25) [10:00:00 -152223.907104] FAST spr round 15 (radius: 25) [10:03:43 -152223.709292] FAST spr round 16 (radius: 25) [10:07:29 -152223.537193] FAST spr round 17 (radius: 25) [10:11:26 -152223.407578] FAST spr round 18 (radius: 25) [10:15:27 -152223.264838] FAST spr round 19 (radius: 25) [10:19:12 -152223.184851] Model parameter optimization (eps = 1.000000) [10:19:37 -152218.690371] SLOW spr round 1 (radius: 5) [10:25:31 -152187.643529] SLOW spr round 2 (radius: 5) [10:31:04 -152176.721238] SLOW spr round 3 (radius: 5) [10:36:30 -152170.968250] SLOW spr round 4 (radius: 5) [10:41:50 -152168.717460] SLOW spr round 5 (radius: 5) [10:46:52 -152168.717460] SLOW spr round 6 (radius: 10) [10:52:33 -152168.524800] SLOW spr round 7 (radius: 5) [10:59:23 -152166.993927] SLOW spr round 8 (radius: 5) [11:05:24 -152166.302404] SLOW spr round 9 (radius: 5) [11:11:17 -152165.737791] SLOW spr round 10 (radius: 5) [11:16:54 -152165.737791] SLOW spr round 11 (radius: 10) [11:22:38 -152164.870961] SLOW spr round 12 (radius: 5) [11:29:32 -152162.058192] SLOW spr round 13 (radius: 5) [11:35:52 -152160.879552] SLOW spr round 14 (radius: 5) [11:41:17 -152160.307500] SLOW spr round 15 (radius: 5) [11:46:33 -152160.307499] SLOW spr round 16 (radius: 10) [11:47:52] [worker #4] ML tree search #15, logLikelihood: -152186.115921 [11:52:23 -152158.737075] SLOW spr round 17 (radius: 5) [11:59:46 -152153.085175] SLOW spr round 18 (radius: 5) [12:05:30 -152153.084735] SLOW spr round 19 (radius: 10) [12:11:29 -152153.084716] SLOW spr round 20 (radius: 15) [12:20:49 -152153.084715] SLOW spr round 21 (radius: 20) [12:38:26 -152153.084715] SLOW spr round 22 (radius: 25) [12:59:30 -152153.084715] Model parameter optimization (eps = 0.100000) [12:59:56] [worker #0] ML tree search #11, logLikelihood: -152152.878759 [12:59:56 -447403.292742] Initial branch length optimization [13:00:02 -395240.423325] Model parameter optimization (eps = 10.000000) [13:01:51 -394348.314362] AUTODETECT spr round 1 (radius: 5) [13:08:06 -291692.277966] AUTODETECT spr round 2 (radius: 10) [13:15:05 -204301.884635] AUTODETECT spr round 3 (radius: 15) [13:21:37] [worker #4] ML tree search #20, logLikelihood: -152179.508632 [13:22:38 -176421.966461] AUTODETECT spr round 4 (radius: 20) [13:33:48 -171144.185074] AUTODETECT spr round 5 (radius: 25) [13:46:17 -171141.883306] SPR radius for FAST iterations: 25 (autodetect) [13:46:17 -171141.883306] Model parameter optimization (eps = 3.000000) [13:47:13 -170756.876821] FAST spr round 1 (radius: 25) [13:54:48 -152842.297924] FAST spr round 2 (radius: 25) [14:00:28 -152301.162345] FAST spr round 3 (radius: 25) [14:05:19 -152246.815590] FAST spr round 4 (radius: 25) [14:09:44 -152239.901128] FAST spr round 5 (radius: 25) [14:13:42 -152232.452589] FAST spr round 6 (radius: 25) [14:17:32 -152230.571504] FAST spr round 7 (radius: 25) [14:21:12 -152230.152506] FAST spr round 8 (radius: 25) [14:25:05 -152230.071948] Model parameter optimization (eps = 1.000000) [14:25:41 -152227.527950] SLOW spr round 1 (radius: 5) [14:31:48 -152191.813936] SLOW spr round 2 (radius: 5) [14:37:51 -152170.553994] SLOW spr round 3 (radius: 5) [14:43:27 -152160.116166] SLOW spr round 4 (radius: 5) [14:49:07 -152151.397590] SLOW spr round 5 (radius: 5) [14:54:15 -152149.571337] SLOW spr round 6 (radius: 5) [14:59:18 -152149.571335] SLOW spr round 7 (radius: 10) [15:04:59 -152149.571335] SLOW spr round 8 (radius: 15) [15:15:02 -152149.571335] SLOW spr round 9 (radius: 20) [15:32:24 -152149.571335] SLOW spr round 10 (radius: 25) [15:55:06 -152149.571335] Model parameter optimization (eps = 0.100000) [15:55:27] [worker #0] ML tree search #16, logLikelihood: -152149.453124 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.273244,0.443150) (0.277390,0.574274) (0.353274,1.362002) (0.096092,2.481522) 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: -152136.827938 AIC score: 308283.655875 / AICc score: 8352343.655875 / BIC score: 315794.793272 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=313). 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/Q8N162/3_mltree/Q8N162.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/3_mltree/Q8N162.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/3_mltree/Q8N162.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8N162/3_mltree/Q8N162.raxml.log Analysis started: 06-Jul-2021 16:57:48 / finished: 07-Jul-2021 08:53:16 Elapsed time: 57327.333 seconds Consumed energy: 4393.695 Wh (= 22 km in an electric car, or 110 km with an e-scooter!)