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 6258R CPU @ 2.70GHz, 56 cores, 187 GB RAM RAxML-NG was called at 26-Jul-2021 00:10:20 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/2_msa/A6NK44_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44 --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/250721_run/phylogeny-snakemake/results/A6NK44/2_msa/A6NK44_trimmed_msa.fasta [00:00:00] Loaded alignment with 310 taxa and 150 sites WARNING: Sequences tr_G3QWL3_G3QWL3_GORGO_9595 and sp_A6NK44_GLOD5_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A2I3T7G9_A0A2I3T7G9_PANTR_9598 and tr_A0A2R9CAD3_A0A2R9CAD3_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A0D2Y9K9_A0A0D2Y9K9_FUSO4_426428 and tr_A0A2H3H2K3_A0A2H3H2K3_FUSOX_327505 are exactly identical! WARNING: Sequences tr_A0A0D2YBU1_A0A0D2YBU1_FUSO4_426428 and tr_X0BZ32_X0BZ32_FUSOX_1089458 are exactly identical! WARNING: Sequences tr_A0A0D2YBU1_A0A0D2YBU1_FUSO4_426428 and tr_A0A2H3TKX8_A0A2H3TKX8_FUSOX_5507 are exactly identical! WARNING: Sequences tr_A0A2I3N4W8_A0A2I3N4W8_PAPAN_9555 and tr_A0A0D9RL90_A0A0D9RL90_CHLSB_60711 are exactly identical! WARNING: Sequences tr_A0A2I3N4W8_A0A2I3N4W8_PAPAN_9555 and tr_A0A2K6BF87_A0A2K6BF87_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A2I3N4W8_A0A2I3N4W8_PAPAN_9555 and tr_A0A2K6A1Y5_A0A2K6A1Y5_MANLE_9568 are exactly identical! WARNING: Sequences tr_A0A1S3SWX6_A0A1S3SWX6_SALSA_8030 and tr_B5XFQ2_B5XFQ2_SALSA_8030 are exactly identical! WARNING: Duplicate sequences found: 9 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.raxml.reduced.phy Alignment comprises 1 partitions and 150 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 150 / 150 Gaps: 10.98 % Invariant sites: 0.67 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.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 310 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 150 / 12000 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -63704.171414] Initial branch length optimization [00:00:01 -54698.250987] Model parameter optimization (eps = 10.000000) [00:00:21 -54656.939228] AUTODETECT spr round 1 (radius: 5) [00:00:51 -40972.125541] AUTODETECT spr round 2 (radius: 10) [00:01:28 -33212.709172] AUTODETECT spr round 3 (radius: 15) [00:02:12 -29766.678341] AUTODETECT spr round 4 (radius: 20) [00:03:20 -29470.518587] AUTODETECT spr round 5 (radius: 25) [00:04:40 -29397.352737] SPR radius for FAST iterations: 25 (autodetect) [00:04:40 -29397.352737] Model parameter optimization (eps = 3.000000) [00:04:54 -29340.015060] FAST spr round 1 (radius: 25) [00:05:36 -26893.769817] FAST spr round 2 (radius: 25) [00:06:10 -26760.927606] FAST spr round 3 (radius: 25) [00:06:37 -26756.640832] FAST spr round 4 (radius: 25) [00:07:03 -26754.730316] FAST spr round 5 (radius: 25) [00:07:27 -26754.730310] Model parameter optimization (eps = 1.000000) [00:07:38 -26751.158835] SLOW spr round 1 (radius: 5) [00:08:24 -26745.326401] SLOW spr round 2 (radius: 5) [00:09:07 -26739.712765] SLOW spr round 3 (radius: 5) [00:09:50 -26737.764913] SLOW spr round 4 (radius: 5) [00:10:30 -26737.764276] SLOW spr round 5 (radius: 10) [00:11:12 -26734.516413] SLOW spr round 6 (radius: 5) [00:12:12 -26731.823408] SLOW spr round 7 (radius: 5) [00:13:00 -26731.458290] SLOW spr round 8 (radius: 5) [00:13:44 -26731.458256] SLOW spr round 9 (radius: 10) [00:14:27 -26731.447723] SLOW spr round 10 (radius: 15) [00:15:02] [worker #1] ML tree search #2, logLikelihood: -26746.276364 [00:15:45 -26731.447699] SLOW spr round 11 (radius: 20) [00:17:15 -26731.447689] SLOW spr round 12 (radius: 25) [00:18:41 -26731.447679] Model parameter optimization (eps = 0.100000) [00:18:46] [worker #0] ML tree search #1, logLikelihood: -26731.170702 [00:18:47 -63467.818595] Initial branch length optimization [00:18:48 -54417.076506] Model parameter optimization (eps = 10.000000) [00:19:05 -54390.837397] AUTODETECT spr round 1 (radius: 5) [00:19:34 -38990.340077] AUTODETECT spr round 2 (radius: 10) [00:20:11 -32343.046082] AUTODETECT spr round 3 (radius: 15) [00:20:57 -31395.132557] AUTODETECT spr round 4 (radius: 20) [00:21:03] [worker #2] ML tree search #3, logLikelihood: -26720.713948 [00:21:51 -29632.965754] AUTODETECT spr round 5 (radius: 25) [00:22:47 -29599.324846] SPR radius for FAST iterations: 25 (autodetect) [00:22:47 -29599.324846] Model parameter optimization (eps = 3.000000) [00:23:00 -29556.960826] FAST spr round 1 (radius: 25) [00:23:44 -27046.008560] FAST spr round 2 (radius: 25) [00:24:20 -26769.543746] FAST spr round 3 (radius: 25) [00:24:52 -26736.981337] FAST spr round 4 (radius: 25) [00:25:17 -26736.980887] Model parameter optimization (eps = 1.000000) [00:25:28 -26731.708552] SLOW spr round 1 (radius: 5) [00:26:16 -26727.069252] SLOW spr round 2 (radius: 5) [00:27:00 -26726.930070] SLOW spr round 3 (radius: 5) [00:27:42 -26726.909672] SLOW spr round 4 (radius: 10) [00:28:25 -26726.909262] SLOW spr round 5 (radius: 15) [00:29:45 -26726.909251] SLOW spr round 6 (radius: 20) [00:31:12 -26726.909251] SLOW spr round 7 (radius: 25) [00:32:36 -26726.909251] Model parameter optimization (eps = 0.100000) [00:32:41] [worker #0] ML tree search #4, logLikelihood: -26726.843754 [00:32:41 -63134.183622] Initial branch length optimization [00:32:42 -54427.991159] Model parameter optimization (eps = 10.000000) [00:33:03 -54370.107550] AUTODETECT spr round 1 (radius: 5) [00:33:33 -40622.152825] AUTODETECT spr round 2 (radius: 10) [00:34:11 -32919.033614] AUTODETECT spr round 3 (radius: 15) [00:34:42] [worker #2] ML tree search #6, logLikelihood: -26737.846229 [00:34:56 -29483.860592] AUTODETECT spr round 4 (radius: 20) [00:35:50 -28755.273221] AUTODETECT spr round 5 (radius: 25) [00:36:51 -28739.580623] SPR radius for FAST iterations: 25 (autodetect) [00:36:51 -28739.580623] Model parameter optimization (eps = 3.000000) [00:37:06 -28676.416908] FAST spr round 1 (radius: 25) [00:37:48 -26922.483362] FAST spr round 2 (radius: 25) [00:38:23 -26782.480578] FAST spr round 3 (radius: 25) [00:38:52 -26768.164979] FAST spr round 4 (radius: 25) [00:39:16 -26767.005063] FAST spr round 5 (radius: 25) [00:39:41 -26767.004486] Model parameter optimization (eps = 1.000000) [00:39:50 -26765.399281] SLOW spr round 1 (radius: 5) [00:40:37 -26755.954760] SLOW spr round 2 (radius: 5) [00:41:21 -26753.837927] SLOW spr round 3 (radius: 5) [00:42:03 -26753.424579] SLOW spr round 4 (radius: 5) [00:42:44 -26753.424094] SLOW spr round 5 (radius: 10) [00:43:27 -26751.564378] SLOW spr round 6 (radius: 5) [00:44:26 -26751.564261] SLOW spr round 7 (radius: 10) [00:45:16 -26751.279452] SLOW spr round 8 (radius: 5) [00:46:12 -26751.278433] SLOW spr round 9 (radius: 10) [00:46:17] [worker #1] ML tree search #5, logLikelihood: -26737.625130 [00:47:01 -26751.278402] SLOW spr round 10 (radius: 15) [00:48:13 -26751.278398] SLOW spr round 11 (radius: 20) [00:49:48 -26751.278394] SLOW spr round 12 (radius: 25) [00:51:15 -26751.278390] Model parameter optimization (eps = 0.100000) [00:51:21] [worker #0] ML tree search #7, logLikelihood: -26751.165263 [00:51:21 -63817.947551] Initial branch length optimization [00:51:23 -54720.519404] Model parameter optimization (eps = 10.000000) [00:51:39 -54685.393443] AUTODETECT spr round 1 (radius: 5) [00:52:08 -40347.040056] AUTODETECT spr round 2 (radius: 10) [00:52:46 -31780.749072] AUTODETECT spr round 3 (radius: 15) [00:53:27 -29212.673944] AUTODETECT spr round 4 (radius: 20) [00:54:17 -28792.693940] AUTODETECT spr round 5 (radius: 25) [00:55:17 -28781.137046] SPR radius for FAST iterations: 25 (autodetect) [00:55:17 -28781.137046] Model parameter optimization (eps = 3.000000) [00:55:35 -28716.405338] FAST spr round 1 (radius: 25) [00:56:09] [worker #2] ML tree search #9, logLikelihood: -26725.252745 [00:56:18 -26830.906594] FAST spr round 2 (radius: 25) [00:56:53 -26763.662132] FAST spr round 3 (radius: 25) [00:57:24 -26735.233443] FAST spr round 4 (radius: 25) [00:57:48 -26735.232936] Model parameter optimization (eps = 1.000000) [00:57:59 -26733.701598] SLOW spr round 1 (radius: 5) [00:58:46 -26728.033174] SLOW spr round 2 (radius: 5) [00:59:29 -26727.519946] SLOW spr round 3 (radius: 5) [00:59:35] [worker #1] ML tree search #8, logLikelihood: -26748.978299 [01:00:11 -26727.519889] SLOW spr round 4 (radius: 10) [01:00:54 -26727.519883] SLOW spr round 5 (radius: 15) [01:02:14 -26727.519879] SLOW spr round 6 (radius: 20) [01:03:48 -26727.519875] SLOW spr round 7 (radius: 25) [01:05:12 -26727.519871] Model parameter optimization (eps = 0.100000) [01:05:16] [worker #0] ML tree search #10, logLikelihood: -26727.457732 [01:05:16 -63805.430055] Initial branch length optimization [01:05:18 -54655.895481] Model parameter optimization (eps = 10.000000) [01:05:36 -54633.439227] AUTODETECT spr round 1 (radius: 5) [01:06:05 -41241.008873] AUTODETECT spr round 2 (radius: 10) [01:06:45 -32669.700538] AUTODETECT spr round 3 (radius: 15) [01:07:29 -29699.065490] AUTODETECT spr round 4 (radius: 20) [01:08:23 -29340.020800] AUTODETECT spr round 5 (radius: 25) [01:09:19 -29240.964400] SPR radius for FAST iterations: 25 (autodetect) [01:09:19 -29240.964400] Model parameter optimization (eps = 3.000000) [01:09:34 -29195.745093] FAST spr round 1 (radius: 25) [01:10:19 -26969.508352] FAST spr round 2 (radius: 25) [01:10:56 -26787.305277] FAST spr round 3 (radius: 25) [01:11:27 -26769.261052] FAST spr round 4 (radius: 25) [01:11:53 -26761.574350] FAST spr round 5 (radius: 25) [01:12:08] [worker #2] ML tree search #12, logLikelihood: -26719.747145 [01:12:19 -26758.291978] FAST spr round 6 (radius: 25) [01:12:43 -26758.288384] Model parameter optimization (eps = 1.000000) [01:12:51 -26751.672178] SLOW spr round 1 (radius: 5) [01:13:39 -26747.106348] SLOW spr round 2 (radius: 5) [01:14:23 -26746.562963] SLOW spr round 3 (radius: 5) [01:15:04 -26746.561806] SLOW spr round 4 (radius: 10) [01:15:46 -26746.561714] SLOW spr round 5 (radius: 15) [01:17:06 -26735.745209] SLOW spr round 6 (radius: 5) [01:18:10 -26732.911324] SLOW spr round 7 (radius: 5) [01:19:00 -26731.800556] SLOW spr round 8 (radius: 5) [01:19:45 -26731.800536] SLOW spr round 9 (radius: 10) [01:20:29 -26731.800529] SLOW spr round 10 (radius: 15) [01:21:07] [worker #1] ML tree search #11, logLikelihood: -26723.227185 [01:21:48 -26731.800523] SLOW spr round 11 (radius: 20) [01:23:16 -26731.800517] SLOW spr round 12 (radius: 25) [01:24:38 -26731.800511] Model parameter optimization (eps = 0.100000) [01:24:47] [worker #0] ML tree search #13, logLikelihood: -26731.310972 [01:24:47 -62118.594046] Initial branch length optimization [01:24:48 -53515.251842] Model parameter optimization (eps = 10.000000) [01:25:01 -53486.795879] AUTODETECT spr round 1 (radius: 5) [01:25:30 -40260.880290] AUTODETECT spr round 2 (radius: 10) [01:26:07 -33437.303711] AUTODETECT spr round 3 (radius: 15) [01:26:53 -30942.584700] AUTODETECT spr round 4 (radius: 20) [01:27:39 -30188.032868] AUTODETECT spr round 5 (radius: 25) [01:28:25 -30176.356640] SPR radius for FAST iterations: 25 (autodetect) [01:28:25 -30176.356640] Model parameter optimization (eps = 3.000000) [01:28:39 -30141.987542] FAST spr round 1 (radius: 25) [01:29:22 -26918.667827] FAST spr round 2 (radius: 25) [01:29:57 -26775.299501] FAST spr round 3 (radius: 25) [01:30:28 -26741.713008] FAST spr round 4 (radius: 25) [01:30:54 -26739.022837] FAST spr round 5 (radius: 25) [01:31:18 -26739.022441] Model parameter optimization (eps = 1.000000) [01:31:28 -26732.554342] SLOW spr round 1 (radius: 5) [01:32:14 -26726.938745] SLOW spr round 2 (radius: 5) [01:32:57 -26724.407545] SLOW spr round 3 (radius: 5) [01:33:01] [worker #2] ML tree search #15, logLikelihood: -26732.360701 [01:33:39 -26724.363513] SLOW spr round 4 (radius: 10) [01:34:21 -26724.362316] SLOW spr round 5 (radius: 15) [01:35:39 -26724.362263] SLOW spr round 6 (radius: 20) [01:37:03 -26724.362256] SLOW spr round 7 (radius: 25) [01:38:25 -26724.362251] Model parameter optimization (eps = 0.100000) [01:38:33] [worker #0] ML tree search #16, logLikelihood: -26723.844639 [01:38:33 -62975.128479] Initial branch length optimization [01:38:34 -53850.217072] Model parameter optimization (eps = 10.000000) [01:38:49 -53830.732208] AUTODETECT spr round 1 (radius: 5) [01:39:18 -40328.703849] AUTODETECT spr round 2 (radius: 10) [01:39:56 -32615.955927] AUTODETECT spr round 3 (radius: 15) [01:40:45 -29234.731611] AUTODETECT spr round 4 (radius: 20) [01:41:38 -29098.372902] AUTODETECT spr round 5 (radius: 25) [01:42:15] [worker #1] ML tree search #14, logLikelihood: -26748.965658 [01:42:40 -29092.964737] SPR radius for FAST iterations: 25 (autodetect) [01:42:40 -29092.964737] Model parameter optimization (eps = 3.000000) [01:42:52 -29052.392095] FAST spr round 1 (radius: 25) [01:43:36 -26841.820915] FAST spr round 2 (radius: 25) [01:44:13 -26759.058238] FAST spr round 3 (radius: 25) [01:44:43 -26746.556561] FAST spr round 4 (radius: 25) [01:45:08 -26744.040662] FAST spr round 5 (radius: 25) [01:45:32 -26744.040345] Model parameter optimization (eps = 1.000000) [01:45:42 -26742.135578] SLOW spr round 1 (radius: 5) [01:46:28 -26729.739152] SLOW spr round 2 (radius: 5) [01:47:11 -26728.840706] SLOW spr round 3 (radius: 5) [01:47:27] [worker #2] ML tree search #18, logLikelihood: -26729.720398 [01:47:53 -26728.840627] SLOW spr round 4 (radius: 10) [01:48:36 -26727.374400] SLOW spr round 5 (radius: 5) [01:49:36 -26726.752411] SLOW spr round 6 (radius: 5) [01:50:25 -26726.751994] SLOW spr round 7 (radius: 10) [01:51:11 -26726.751966] SLOW spr round 8 (radius: 15) [01:52:26 -26726.751955] SLOW spr round 9 (radius: 20) [01:53:59 -26726.751945] SLOW spr round 10 (radius: 25) [01:55:23 -26726.751935] Model parameter optimization (eps = 0.100000) [01:55:29] [worker #0] ML tree search #19, logLikelihood: -26726.600378 [02:01:16] [worker #1] ML tree search #17, logLikelihood: -26734.623719 [02:20:01] [worker #1] ML tree search #20, logLikelihood: -26744.854539 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.174738,0.295429) (0.304592,0.395089) (0.250102,0.999115) (0.270567,2.136826) 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: -26719.747145 AIC score: 54685.494290 / AICc score: 832189.494290 / BIC score: 56561.120078 Free parameters (model + branch lengths): 623 WARNING: Number of free parameters (K=623) is larger than alignment size (n=150). This might lead to overfitting and compromise tree inference results! Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NK44/3_mltree/A6NK44.raxml.log Analysis started: 26-Jul-2021 00:10:20 / finished: 26-Jul-2021 02:30:22 Elapsed time: 8402.013 seconds Consumed energy: 346.531 Wh (= 2 km in an electric car, or 9 km with an e-scooter!)