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 20:50:13 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/2_msa/Q9BSQ5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/2_msa/Q9BSQ5_trimmed_msa.fasta [00:00:00] Loaded alignment with 211 taxa and 417 sites WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A2I2ZMX9_A0A2I2ZMX9_GORGO_9595 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_H2PM69_H2PM69_PONAB_9601 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A2I3T2C4_A0A2I3T2C4_PANTR_9598 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_H9G0F8_H9G0F8_MACMU_9544 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_G7P1T7_G7P1T7_MACFA_9541 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A096MV89_A0A096MV89_PAPAN_9555 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A0D9RT55_A0A0D9RT55_CHLSB_60711 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A2K6ECA6_A0A2K6ECA6_MACNE_9545 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A2K6A8Z4_A0A2K6A8Z4_MANLE_9568 are exactly identical! WARNING: Sequences tr_G1QVN9_G1QVN9_NOMLE_61853 and tr_A0A2R9AVP7_A0A2R9AVP7_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A096NUZ1_A0A096NUZ1_PAPAN_9555 and tr_A0A2K6D2X4_A0A2K6D2X4_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A151P463_A0A151P463_ALLMI_8496 and tr_A0A1U7SV82_A0A1U7SV82_ALLSI_38654 are exactly identical! WARNING: Sequences tr_A0A091VQE4_A0A091VQE4_NIPNI_128390 and tr_A0A087QJI6_A0A087QJI6_APTFO_9233 are exactly identical! WARNING: Sequences tr_A0A226N8H9_A0A226N8H9_CALSU_9009 and tr_A0A226NVV4_A0A226NVV4_COLVI_9014 are exactly identical! WARNING: Sequences tr_A0A2D0SLN9_A0A2D0SLN9_ICTPU_7998 and tr_A0A2D0SLP4_A0A2D0SLP4_ICTPU_7998 are exactly identical! WARNING: Duplicate sequences found: 15 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5.raxml.reduced.phy Alignment comprises 1 partitions and 417 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 417 / 417 Gaps: 13.47 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5.raxml.rba Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] Generating 20 random starting tree(s) with 211 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 209 / 16720 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -100426.754785] Initial branch length optimization [00:00:00 -77888.243169] Model parameter optimization (eps = 10.000000) [00:00:12 -77499.763753] AUTODETECT spr round 1 (radius: 5) [00:00:23 -43861.409863] AUTODETECT spr round 2 (radius: 10) [00:00:37 -33020.422768] AUTODETECT spr round 3 (radius: 15) [00:00:58 -30699.619089] AUTODETECT spr round 4 (radius: 20) [00:01:20 -30655.056098] AUTODETECT spr round 5 (radius: 25) [00:01:41 -30249.397834] SPR radius for FAST iterations: 25 (autodetect) [00:01:41 -30249.397834] Model parameter optimization (eps = 3.000000) [00:01:53 -29847.895487] FAST spr round 1 (radius: 25) [00:02:08 -28157.704202] FAST spr round 2 (radius: 25) [00:02:21 -28095.061699] FAST spr round 3 (radius: 25) [00:02:31 -28066.513178] FAST spr round 4 (radius: 25) [00:02:40 -28066.477128] Model parameter optimization (eps = 1.000000) [00:02:47 -28063.283963] SLOW spr round 1 (radius: 5) [00:03:05 -28056.780900] SLOW spr round 2 (radius: 5) [00:03:23 -28056.779675] SLOW spr round 3 (radius: 10) [00:03:39 -28055.307482] SLOW spr round 4 (radius: 5) [00:04:04 -28055.307416] SLOW spr round 5 (radius: 10) [00:04:24 -28055.307391] SLOW spr round 6 (radius: 15) [00:04:51 -28055.307377] SLOW spr round 7 (radius: 20) [00:05:26 -28055.307368] SLOW spr round 8 (radius: 25) [00:05:56 -28055.307361] Model parameter optimization (eps = 0.100000) [00:05:59] [worker #0] ML tree search #1, logLikelihood: -28055.277842 [00:05:59 -102071.523967] Initial branch length optimization [00:05:59 -80312.075551] Model parameter optimization (eps = 10.000000) [00:06:03] [worker #1] ML tree search #2, logLikelihood: -28117.488208 [00:06:13 -79953.955503] AUTODETECT spr round 1 (radius: 5) [00:06:24 -45657.549789] AUTODETECT spr round 2 (radius: 10) [00:06:32] [worker #2] ML tree search #3, logLikelihood: -28056.149057 [00:06:38 -33033.023354] AUTODETECT spr round 3 (radius: 15) [00:06:57 -30687.005868] AUTODETECT spr round 4 (radius: 20) [00:07:17 -30506.047609] AUTODETECT spr round 5 (radius: 25) [00:07:36 -30499.151506] SPR radius for FAST iterations: 25 (autodetect) [00:07:36 -30499.151506] Model parameter optimization (eps = 3.000000) [00:07:52 -30114.982799] FAST spr round 1 (radius: 25) [00:08:09 -28179.137259] FAST spr round 2 (radius: 25) [00:08:23 -28111.386355] FAST spr round 3 (radius: 25) [00:08:34 -28096.011216] FAST spr round 4 (radius: 25) [00:08:43 -28095.823188] FAST spr round 5 (radius: 25) [00:08:51 -28095.822626] Model parameter optimization (eps = 1.000000) [00:08:58 -28092.741581] SLOW spr round 1 (radius: 5) [00:09:18 -28088.446467] SLOW spr round 2 (radius: 5) [00:09:36 -28088.446315] SLOW spr round 3 (radius: 10) [00:09:52 -28087.016852] SLOW spr round 4 (radius: 5) [00:10:20 -28060.607200] SLOW spr round 5 (radius: 5) [00:10:41 -28060.605804] SLOW spr round 6 (radius: 10) [00:10:59 -28060.605719] SLOW spr round 7 (radius: 15) [00:11:26 -28060.605706] SLOW spr round 8 (radius: 20) [00:12:01 -28060.605702] SLOW spr round 9 (radius: 25) [00:12:30 -28060.605701] Model parameter optimization (eps = 0.100000) [00:12:32] [worker #2] ML tree search #6, logLikelihood: -28059.046610 [00:12:36] [worker #0] ML tree search #4, logLikelihood: -28060.021108 [00:12:37 -103494.758033] Initial branch length optimization [00:12:37 -81259.081745] Model parameter optimization (eps = 10.000000) [00:12:51 -80858.265461] AUTODETECT spr round 1 (radius: 5) [00:13:01 -46540.483171] AUTODETECT spr round 2 (radius: 10) [00:13:16] [worker #1] ML tree search #5, logLikelihood: -28118.166571 [00:13:17 -34699.244235] AUTODETECT spr round 3 (radius: 15) [00:13:37 -30440.310098] AUTODETECT spr round 4 (radius: 20) [00:13:59 -30379.853407] AUTODETECT spr round 5 (radius: 25) [00:14:24 -30371.681718] SPR radius for FAST iterations: 25 (autodetect) [00:14:24 -30371.681718] Model parameter optimization (eps = 3.000000) [00:14:36 -29965.514201] FAST spr round 1 (radius: 25) [00:14:52 -28178.493549] FAST spr round 2 (radius: 25) [00:15:04 -28135.286834] FAST spr round 3 (radius: 25) [00:15:13 -28135.285288] Model parameter optimization (eps = 1.000000) [00:15:19 -28129.982655] SLOW spr round 1 (radius: 5) [00:15:38 -28123.243720] SLOW spr round 2 (radius: 5) [00:15:56 -28123.241903] SLOW spr round 3 (radius: 10) [00:16:13 -28122.004925] SLOW spr round 4 (radius: 5) [00:16:39 -28122.003989] SLOW spr round 5 (radius: 10) [00:16:58 -28122.003519] SLOW spr round 6 (radius: 15) [00:17:25 -28120.842993] SLOW spr round 7 (radius: 5) [00:17:53 -28119.133469] SLOW spr round 8 (radius: 5) [00:18:15 -28119.133339] SLOW spr round 9 (radius: 10) [00:18:18] [worker #2] ML tree search #9, logLikelihood: -28117.037644 [00:18:34 -28119.133237] SLOW spr round 10 (radius: 15) [00:19:01 -28119.133153] SLOW spr round 11 (radius: 20) [00:19:35 -28119.133083] SLOW spr round 12 (radius: 25) [00:19:39] [worker #1] ML tree search #8, logLikelihood: -28057.297604 [00:20:05 -28119.133025] Model parameter optimization (eps = 0.100000) [00:20:07] [worker #0] ML tree search #7, logLikelihood: -28119.096440 [00:20:07 -98427.668384] Initial branch length optimization [00:20:07 -77136.667568] Model parameter optimization (eps = 10.000000) [00:20:18 -76802.963072] AUTODETECT spr round 1 (radius: 5) [00:20:29 -47537.150886] AUTODETECT spr round 2 (radius: 10) [00:20:43 -37020.794841] AUTODETECT spr round 3 (radius: 15) [00:21:01 -31574.144817] AUTODETECT spr round 4 (radius: 20) [00:21:21 -30973.335266] AUTODETECT spr round 5 (radius: 25) [00:21:44 -30969.113518] SPR radius for FAST iterations: 25 (autodetect) [00:21:44 -30969.113518] Model parameter optimization (eps = 3.000000) [00:21:54 -30656.991646] FAST spr round 1 (radius: 25) [00:22:12 -28241.277644] FAST spr round 2 (radius: 25) [00:22:25 -28084.443416] FAST spr round 3 (radius: 25) [00:22:36 -28077.544066] FAST spr round 4 (radius: 25) [00:22:44 -28077.543025] Model parameter optimization (eps = 1.000000) [00:22:52 -28074.227953] SLOW spr round 1 (radius: 5) [00:23:13 -28060.312901] SLOW spr round 2 (radius: 5) [00:23:31 -28059.322892] SLOW spr round 3 (radius: 5) [00:23:49 -28057.810007] SLOW spr round 4 (radius: 5) [00:24:07 -28057.809518] SLOW spr round 5 (radius: 10) [00:24:24 -28056.396861] SLOW spr round 6 (radius: 5) [00:24:49 -28056.396835] SLOW spr round 7 (radius: 10) [00:25:06] [worker #2] ML tree search #12, logLikelihood: -28116.960619 [00:25:10 -28056.396834] SLOW spr round 8 (radius: 15) [00:25:36] [worker #1] ML tree search #11, logLikelihood: -28116.333270 [00:25:38 -28056.396834] SLOW spr round 9 (radius: 20) [00:26:13 -28056.396833] SLOW spr round 10 (radius: 25) [00:26:43 -28056.396833] Model parameter optimization (eps = 0.100000) [00:26:48] [worker #0] ML tree search #10, logLikelihood: -28056.143900 [00:26:48 -101775.816189] Initial branch length optimization [00:26:48 -79864.666972] Model parameter optimization (eps = 10.000000) [00:27:03 -79466.219156] AUTODETECT spr round 1 (radius: 5) [00:27:13 -47159.903080] AUTODETECT spr round 2 (radius: 10) [00:27:28 -34855.291237] AUTODETECT spr round 3 (radius: 15) [00:27:43 -33059.622198] AUTODETECT spr round 4 (radius: 20) [00:28:02 -30914.372095] AUTODETECT spr round 5 (radius: 25) [00:28:20 -30913.628865] SPR radius for FAST iterations: 25 (autodetect) [00:28:20 -30913.628865] Model parameter optimization (eps = 3.000000) [00:28:32 -30479.105667] FAST spr round 1 (radius: 25) [00:28:48 -28221.151436] FAST spr round 2 (radius: 25) [00:29:01 -28127.550346] FAST spr round 3 (radius: 25) [00:29:10 -28127.546719] Model parameter optimization (eps = 1.000000) [00:29:15 -28124.980371] SLOW spr round 1 (radius: 5) [00:29:35 -28119.241541] SLOW spr round 2 (radius: 5) [00:29:53 -28119.240812] SLOW spr round 3 (radius: 10) [00:30:09 -28117.258578] SLOW spr round 4 (radius: 5) [00:30:35 -28117.257990] SLOW spr round 5 (radius: 10) [00:30:55 -28117.257828] SLOW spr round 6 (radius: 15) [00:31:21 -28117.257742] SLOW spr round 7 (radius: 20) [00:31:30] [worker #2] ML tree search #15, logLikelihood: -28058.846208 [00:31:33] [worker #1] ML tree search #14, logLikelihood: -28056.956883 [00:31:55 -28117.257678] SLOW spr round 8 (radius: 25) [00:32:25 -28117.257628] Model parameter optimization (eps = 0.100000) [00:32:27] [worker #0] ML tree search #13, logLikelihood: -28117.179769 [00:32:27 -103615.926083] Initial branch length optimization [00:32:28 -80666.686174] Model parameter optimization (eps = 10.000000) [00:32:39 -80256.885633] AUTODETECT spr round 1 (radius: 5) [00:32:50 -44879.009105] AUTODETECT spr round 2 (radius: 10) [00:33:04 -34516.683632] AUTODETECT spr round 3 (radius: 15) [00:33:20 -31841.534332] AUTODETECT spr round 4 (radius: 20) [00:33:40 -30768.230356] AUTODETECT spr round 5 (radius: 25) [00:34:01 -30742.414051] SPR radius for FAST iterations: 25 (autodetect) [00:34:01 -30742.414051] Model parameter optimization (eps = 3.000000) [00:34:14 -30325.570049] FAST spr round 1 (radius: 25) [00:34:29 -28227.510054] FAST spr round 2 (radius: 25) [00:34:41 -28168.346328] FAST spr round 3 (radius: 25) [00:34:51 -28164.597428] FAST spr round 4 (radius: 25) [00:35:00 -28164.597306] Model parameter optimization (eps = 1.000000) [00:35:06 -28153.304325] SLOW spr round 1 (radius: 5) [00:35:26 -28148.320837] SLOW spr round 2 (radius: 5) [00:35:44 -28148.318628] SLOW spr round 3 (radius: 10) [00:36:01 -28147.157002] SLOW spr round 4 (radius: 5) [00:36:28 -28116.476253] SLOW spr round 5 (radius: 5) [00:36:48 -28116.476093] SLOW spr round 6 (radius: 10) [00:37:06 -28116.475995] SLOW spr round 7 (radius: 15) [00:37:22] [worker #2] ML tree search #18, logLikelihood: -28117.990071 [00:37:25] [worker #1] ML tree search #17, logLikelihood: -28057.290680 [00:37:33 -28116.475908] SLOW spr round 8 (radius: 20) [00:38:07 -28116.475832] SLOW spr round 9 (radius: 25) [00:38:37 -28116.475764] Model parameter optimization (eps = 0.100000) [00:38:39] [worker #0] ML tree search #16, logLikelihood: -28116.379988 [00:38:39 -100106.100489] Initial branch length optimization [00:38:40 -77542.414288] Model parameter optimization (eps = 10.000000) [00:38:55 -77122.692874] AUTODETECT spr round 1 (radius: 5) [00:39:06 -45309.461640] AUTODETECT spr round 2 (radius: 10) [00:39:21 -34521.494036] AUTODETECT spr round 3 (radius: 15) [00:39:40 -30443.907708] AUTODETECT spr round 4 (radius: 20) [00:40:02 -30032.264422] AUTODETECT spr round 5 (radius: 25) [00:40:26 -30032.231000] SPR radius for FAST iterations: 20 (autodetect) [00:40:26 -30032.231000] Model parameter optimization (eps = 3.000000) [00:40:39 -29644.763795] FAST spr round 1 (radius: 20) [00:40:54 -28207.659965] FAST spr round 2 (radius: 20) [00:41:07 -28130.901112] FAST spr round 3 (radius: 20) [00:41:17 -28126.258834] FAST spr round 4 (radius: 20) [00:41:26 -28126.258698] Model parameter optimization (eps = 1.000000) [00:41:28 -28125.922726] SLOW spr round 1 (radius: 5) [00:41:48 -28118.453314] SLOW spr round 2 (radius: 5) [00:42:06 -28118.062474] SLOW spr round 3 (radius: 5) [00:42:24 -28118.062290] SLOW spr round 4 (radius: 10) [00:42:41 -28116.689066] SLOW spr round 5 (radius: 5) [00:43:06] [worker #1] ML tree search #20, logLikelihood: -28118.464863 [00:43:06 -28116.687652] SLOW spr round 6 (radius: 10) [00:43:26 -28116.687404] SLOW spr round 7 (radius: 15) [00:43:51 -28116.687211] SLOW spr round 8 (radius: 20) [00:44:24 -28116.687043] SLOW spr round 9 (radius: 25) [00:44:54 -28116.686894] Model parameter optimization (eps = 0.100000) [00:44:57] [worker #0] ML tree search #19, logLikelihood: -28116.584094 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.213184,0.652107) (0.111615,0.843980) (0.462331,0.736330) (0.212870,2.002875) 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: -28055.277842 AIC score: 56960.555684 / AICc score: 419060.555684 / BIC score: 58674.617328 Free parameters (model + branch lengths): 425 WARNING: Number of free parameters (K=425) is larger than alignment size (n=417). 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/Q9BSQ5/3_mltree/Q9BSQ5.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9BSQ5/3_mltree/Q9BSQ5.raxml.log Analysis started: 06-Jul-2021 20:50:13 / finished: 06-Jul-2021 21:35:11 Elapsed time: 2697.833 seconds Consumed energy: 252.635 Wh (= 1 km in an electric car, or 6 km with an e-scooter!)