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 05-Jul-2021 23:05:53 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/2_msa/Q86VF2_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/3_mltree/Q86VF2 --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/Q86VF2/2_msa/Q86VF2_trimmed_msa.fasta [00:00:00] Loaded alignment with 510 taxa and 538 sites WARNING: Sequences tr_A0A2I2Y3R1_A0A2I2Y3R1_GORGO_9595 and tr_H2QJ24_H2QJ24_PANTR_9598 are exactly identical! WARNING: Sequences tr_A0A2I2Y3R1_A0A2I2Y3R1_GORGO_9595 and sp_Q8WZ42_TITIN_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A2I2Y3R1_A0A2I2Y3R1_GORGO_9595 and tr_A0A2R9B6M8_A0A2R9B6M8_PANPA_9597 are exactly identical! WARNING: Sequences tr_H2Q3A0_H2Q3A0_PANTR_9598 and tr_A0A2R9C3Q0_A0A2R9C3Q0_PANPA_9597 are exactly identical! WARNING: Sequences tr_G7PDD2_G7PDD2_MACFA_9541 and tr_A0A2K5LIE2_A0A2K5LIE2_CERAT_9531 are exactly identical! WARNING: Sequences tr_G7PDD2_G7PDD2_MACFA_9541 and tr_A0A2K6AY33_A0A2K6AY33_MACNE_9545 are exactly identical! WARNING: Sequences tr_G7PDD2_G7PDD2_MACFA_9541 and tr_A0A2K5YQ97_A0A2K5YQ97_MANLE_9568 are exactly identical! WARNING: Sequences tr_A0A096MTQ4_A0A096MTQ4_PAPAN_9555 and tr_A0A0D9RKL7_A0A0D9RKL7_CHLSB_60711 are exactly identical! WARNING: Sequences tr_A0A096MTQ4_A0A096MTQ4_PAPAN_9555 and tr_A0A2K5NPS1_A0A2K5NPS1_CERAT_9531 are exactly identical! WARNING: Sequences tr_A0A096MTQ4_A0A096MTQ4_PAPAN_9555 and tr_A0A2K6B9B0_A0A2K6B9B0_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A096MTQ4_A0A096MTQ4_PAPAN_9555 and tr_A0A2K5Z357_A0A2K5Z357_MANLE_9568 are exactly identical! WARNING: Sequences tr_A0A1S3PWV0_A0A1S3PWV0_SALSA_8030 and tr_A0A1S3QTR0_A0A1S3QTR0_SALSA_8030 are exactly identical! WARNING: Sequences tr_A0A1D1UD13_A0A1D1UD13_RAMVA_947166 and tr_A0A1D1UFR1_A0A1D1UFR1_RAMVA_947166 are exactly identical! WARNING: Sequences tr_A0A226N2E6_A0A226N2E6_CALSU_9009 and tr_A0A226PD93_A0A226PD93_COLVI_9014 are exactly identical! WARNING: Duplicate sequences found: 14 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/Q86VF2/3_mltree/Q86VF2.raxml.reduced.phy Alignment comprises 1 partitions and 538 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 538 / 538 Gaps: 29.38 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/3_mltree/Q86VF2.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 510 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 269 / 21520 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -445217.417385] Initial branch length optimization [00:00:03 -366905.598460] Model parameter optimization (eps = 10.000000) [00:00:32 -365572.692801] AUTODETECT spr round 1 (radius: 5) [00:01:33 -252407.354807] AUTODETECT spr round 2 (radius: 10) [00:02:42 -192039.984523] AUTODETECT spr round 3 (radius: 15) [00:04:00 -170660.837412] AUTODETECT spr round 4 (radius: 20) [00:05:32 -163173.732099] AUTODETECT spr round 5 (radius: 25) [00:07:26 -161671.897256] SPR radius for FAST iterations: 25 (autodetect) [00:07:26 -161671.897256] Model parameter optimization (eps = 3.000000) [00:07:48 -161256.902710] FAST spr round 1 (radius: 25) [00:09:35 -149883.088818] FAST spr round 2 (radius: 25) [00:10:55 -149364.053507] FAST spr round 3 (radius: 25) [00:12:05 -149300.812030] FAST spr round 4 (radius: 25) [00:12:58 -149292.565468] FAST spr round 5 (radius: 25) [00:13:47 -149291.705052] FAST spr round 6 (radius: 25) [00:14:35 -149291.704321] Model parameter optimization (eps = 1.000000) [00:14:59 -149276.445173] SLOW spr round 1 (radius: 5) [00:16:22 -149250.338851] SLOW spr round 2 (radius: 5) [00:17:39 -149248.967016] SLOW spr round 3 (radius: 5) [00:18:53 -149248.964983] SLOW spr round 4 (radius: 10) [00:20:26 -149244.325528] SLOW spr round 5 (radius: 5) [00:22:06 -149243.121200] SLOW spr round 6 (radius: 5) [00:23:26 -149243.119972] SLOW spr round 7 (radius: 10) [00:25:04 -149243.119307] SLOW spr round 8 (radius: 15) [00:28:12 -149242.615937] SLOW spr round 9 (radius: 5) [00:29:50 -149242.578058] SLOW spr round 10 (radius: 10) [00:31:46 -149241.651122] SLOW spr round 11 (radius: 5) [00:33:17 -149241.650391] SLOW spr round 12 (radius: 10) [00:35:07 -149241.650187] SLOW spr round 13 (radius: 15) [00:38:19 -149241.650072] SLOW spr round 14 (radius: 20) [00:42:58 -149241.649996] SLOW spr round 15 (radius: 25) [00:44:11] [worker #1] ML tree search #2, logLikelihood: -149246.087053 [00:46:17] [worker #2] ML tree search #3, logLikelihood: -149238.096036 [00:47:24 -149241.649945] Model parameter optimization (eps = 0.100000) [00:47:28] [worker #0] ML tree search #1, logLikelihood: -149241.635378 [00:47:28 -444179.926855] Initial branch length optimization [00:47:32 -365288.415230] Model parameter optimization (eps = 10.000000) [00:48:13 -364060.099402] AUTODETECT spr round 1 (radius: 5) [00:49:14 -253961.578865] AUTODETECT spr round 2 (radius: 10) [00:50:20 -194909.730739] AUTODETECT spr round 3 (radius: 15) [00:51:39 -166512.388526] AUTODETECT spr round 4 (radius: 20) [00:53:11 -164325.258044] AUTODETECT spr round 5 (radius: 25) [00:55:00 -164057.854838] SPR radius for FAST iterations: 25 (autodetect) [00:55:00 -164057.854838] Model parameter optimization (eps = 3.000000) [00:55:22 -163658.497708] FAST spr round 1 (radius: 25) [00:57:20 -149910.232746] FAST spr round 2 (radius: 25) [00:58:44 -149396.902543] FAST spr round 3 (radius: 25) [00:59:54 -149357.662697] FAST spr round 4 (radius: 25) [01:00:53 -149348.406594] FAST spr round 5 (radius: 25) [01:01:43 -149346.620298] FAST spr round 6 (radius: 25) [01:02:32 -149344.030693] FAST spr round 7 (radius: 25) [01:03:19 -149344.029265] Model parameter optimization (eps = 1.000000) [01:03:31 -149330.739664] SLOW spr round 1 (radius: 5) [01:04:52 -149276.814386] SLOW spr round 2 (radius: 5) [01:06:13 -149269.763972] SLOW spr round 3 (radius: 5) [01:07:28 -149269.736030] SLOW spr round 4 (radius: 10) [01:08:59 -149267.605491] SLOW spr round 5 (radius: 5) [01:10:44 -149254.938350] SLOW spr round 6 (radius: 5) [01:12:13 -149252.827568] SLOW spr round 7 (radius: 5) [01:13:33 -149252.827320] SLOW spr round 8 (radius: 10) [01:15:09 -149252.827312] SLOW spr round 9 (radius: 15) [01:18:00] [worker #1] ML tree search #5, logLikelihood: -149233.685959 [01:18:28 -149250.113104] SLOW spr round 10 (radius: 5) [01:20:12 -149250.084345] SLOW spr round 11 (radius: 10) [01:22:13 -149250.084342] SLOW spr round 12 (radius: 15) [01:25:20 -149250.084339] SLOW spr round 13 (radius: 20) [01:29:57 -149250.084336] SLOW spr round 14 (radius: 25) [01:32:35] [worker #2] ML tree search #6, logLikelihood: -149228.596221 [01:34:17 -149250.084333] Model parameter optimization (eps = 0.100000) [01:34:28] [worker #0] ML tree search #4, logLikelihood: -149249.013898 [01:34:28 -443250.808178] Initial branch length optimization [01:34:31 -361875.381940] Model parameter optimization (eps = 10.000000) [01:35:13 -360526.650235] AUTODETECT spr round 1 (radius: 5) [01:36:13 -255632.424538] AUTODETECT spr round 2 (radius: 10) [01:37:25 -197699.003635] AUTODETECT spr round 3 (radius: 15) [01:38:50 -176293.113233] AUTODETECT spr round 4 (radius: 20) [01:40:29 -166298.955368] AUTODETECT spr round 5 (radius: 25) [01:42:14 -165356.835780] SPR radius for FAST iterations: 25 (autodetect) [01:42:14 -165356.835780] Model parameter optimization (eps = 3.000000) [01:42:36 -164956.828116] FAST spr round 1 (radius: 25) [01:44:35 -149939.718409] FAST spr round 2 (radius: 25) [01:46:03 -149309.346133] FAST spr round 3 (radius: 25) [01:47:04 -149291.529685] FAST spr round 4 (radius: 25) [01:47:57 -149289.745471] FAST spr round 5 (radius: 25) [01:48:46 -149288.352547] FAST spr round 6 (radius: 25) [01:49:34 -149288.351690] Model parameter optimization (eps = 1.000000) [01:49:44 -149282.550027] SLOW spr round 1 (radius: 5) [01:51:02 -149266.202017] SLOW spr round 2 (radius: 5) [01:52:17 -149265.886455] SLOW spr round 3 (radius: 5) [01:53:37 -149259.856371] SLOW spr round 4 (radius: 5) [01:54:54 -149251.475609] SLOW spr round 5 (radius: 5) [01:56:09 -149245.710834] SLOW spr round 6 (radius: 5) [01:57:24 -149245.707949] SLOW spr round 7 (radius: 10) [01:59:00 -149242.116129] SLOW spr round 8 (radius: 5) [02:00:42 -149238.953930] SLOW spr round 9 (radius: 5) [02:02:08 -149238.479458] SLOW spr round 10 (radius: 5) [02:03:27 -149238.477851] SLOW spr round 11 (radius: 10) [02:04:45] [worker #1] ML tree search #8, logLikelihood: -149224.246890 [02:05:02 -149237.489247] SLOW spr round 12 (radius: 5) [02:06:41 -149237.279420] SLOW spr round 13 (radius: 5) [02:08:06 -149237.276594] SLOW spr round 14 (radius: 10) [02:09:43 -149237.276309] SLOW spr round 15 (radius: 15) [02:12:59 -149237.276259] SLOW spr round 16 (radius: 20) [02:17:28 -149237.276241] SLOW spr round 17 (radius: 25) [02:21:57 -149237.276231] Model parameter optimization (eps = 0.100000) [02:22:16] [worker #0] ML tree search #7, logLikelihood: -149232.328161 [02:22:16 -441871.165046] Initial branch length optimization [02:22:19 -359637.639634] Model parameter optimization (eps = 10.000000) [02:22:49 -358214.597275] AUTODETECT spr round 1 (radius: 5) [02:23:46 -260186.809521] AUTODETECT spr round 2 (radius: 10) [02:24:57 -199987.107399] AUTODETECT spr round 3 (radius: 15) [02:25:16] [worker #2] ML tree search #9, logLikelihood: -149237.868152 [02:26:20 -170350.024499] AUTODETECT spr round 4 (radius: 20) [02:27:50 -164253.131633] AUTODETECT spr round 5 (radius: 25) [02:29:37 -163327.020465] SPR radius for FAST iterations: 25 (autodetect) [02:29:37 -163327.020465] Model parameter optimization (eps = 3.000000) [02:30:00 -162960.786020] FAST spr round 1 (radius: 25) [02:31:54 -149897.382726] FAST spr round 2 (radius: 25) [02:33:21 -149356.424484] FAST spr round 3 (radius: 25) [02:34:31 -149300.972714] FAST spr round 4 (radius: 25) [02:35:25 -149298.672424] FAST spr round 5 (radius: 25) [02:36:11 -149295.929856] FAST spr round 6 (radius: 25) [02:36:59 -149295.929818] Model parameter optimization (eps = 1.000000) [02:37:14 -149278.414920] SLOW spr round 1 (radius: 5) [02:38:36 -149253.955746] SLOW spr round 2 (radius: 5) [02:39:54 -149252.498928] SLOW spr round 3 (radius: 5) [02:41:10 -149252.498023] SLOW spr round 4 (radius: 10) [02:42:43 -149248.941653] SLOW spr round 5 (radius: 5) [02:44:24 -149248.935300] SLOW spr round 6 (radius: 10) [02:46:16 -149248.933789] SLOW spr round 7 (radius: 15) [02:49:06 -149248.080651] SLOW spr round 8 (radius: 5) [02:50:45 -149247.964454] SLOW spr round 9 (radius: 5) [02:52:14 -149247.962225] SLOW spr round 10 (radius: 10) [02:53:53 -149247.961958] SLOW spr round 11 (radius: 15) [02:56:49 -149247.961884] SLOW spr round 12 (radius: 20) [03:01:11 -149247.373842] SLOW spr round 13 (radius: 5) [03:03:00 -149243.864822] SLOW spr round 14 (radius: 5) [03:04:31 -149243.591895] SLOW spr round 15 (radius: 5) [03:05:52 -149243.590919] SLOW spr round 16 (radius: 10) [03:07:22 -149243.590665] SLOW spr round 17 (radius: 15) [03:10:23 -149243.590509] SLOW spr round 18 (radius: 20) [03:12:00] [worker #1] ML tree search #11, logLikelihood: -149230.906012 [03:12:07] [worker #2] ML tree search #12, logLikelihood: -149245.784629 [03:14:50 -149243.590401] SLOW spr round 19 (radius: 25) [03:19:23 -149243.590326] Model parameter optimization (eps = 0.100000) [03:19:34] [worker #0] ML tree search #10, logLikelihood: -149243.163246 [03:19:34 -440887.429535] Initial branch length optimization [03:19:37 -359545.962725] Model parameter optimization (eps = 10.000000) [03:20:22 -358159.510363] AUTODETECT spr round 1 (radius: 5) [03:21:22 -260153.063052] AUTODETECT spr round 2 (radius: 10) [03:22:34 -191315.304076] AUTODETECT spr round 3 (radius: 15) [03:23:53 -173360.034794] AUTODETECT spr round 4 (radius: 20) [03:25:23 -166825.164081] AUTODETECT spr round 5 (radius: 25) [03:27:15 -164661.105973] SPR radius for FAST iterations: 25 (autodetect) [03:27:15 -164661.105973] Model parameter optimization (eps = 3.000000) [03:27:43 -164304.936795] FAST spr round 1 (radius: 25) [03:29:32 -150065.107153] FAST spr round 2 (radius: 25) [03:30:58 -149343.035630] FAST spr round 3 (radius: 25) [03:32:04 -149297.534595] FAST spr round 4 (radius: 25) [03:32:55 -149294.280550] FAST spr round 5 (radius: 25) [03:33:44 -149293.724047] FAST spr round 6 (radius: 25) [03:34:29 -149293.722962] Model parameter optimization (eps = 1.000000) [03:34:39 -149292.350148] SLOW spr round 1 (radius: 5) [03:35:58 -149264.230762] SLOW spr round 2 (radius: 5) [03:37:17 -149260.946752] SLOW spr round 3 (radius: 5) [03:38:32 -149260.945560] SLOW spr round 4 (radius: 10) [03:40:02 -149259.237945] SLOW spr round 5 (radius: 5) [03:41:42 -149259.200074] SLOW spr round 6 (radius: 10) [03:43:34 -149259.200007] SLOW spr round 7 (radius: 15) [03:46:36 -149259.199987] SLOW spr round 8 (radius: 20) [03:51:00 -149259.199976] SLOW spr round 9 (radius: 25) [03:51:24] [worker #2] ML tree search #15, logLikelihood: -149238.108979 [03:55:26] [worker #1] ML tree search #14, logLikelihood: -149247.420186 [03:55:37 -149259.199967] Model parameter optimization (eps = 0.100000) [03:55:43] [worker #0] ML tree search #13, logLikelihood: -149259.074231 [03:55:43 -443481.643317] Initial branch length optimization [03:55:46 -360666.120623] Model parameter optimization (eps = 10.000000) [03:56:16 -359217.526584] AUTODETECT spr round 1 (radius: 5) [03:57:15 -259314.693799] AUTODETECT spr round 2 (radius: 10) [03:58:26 -194888.323187] AUTODETECT spr round 3 (radius: 15) [03:59:49 -169846.171669] AUTODETECT spr round 4 (radius: 20) [04:01:21 -163363.984529] AUTODETECT spr round 5 (radius: 25) [04:03:11 -163231.719774] SPR radius for FAST iterations: 25 (autodetect) [04:03:11 -163231.719774] Model parameter optimization (eps = 3.000000) [04:03:37 -162837.275834] FAST spr round 1 (radius: 25) [04:05:27 -150091.005768] FAST spr round 2 (radius: 25) [04:06:48 -149350.183263] FAST spr round 3 (radius: 25) [04:07:57 -149296.688728] FAST spr round 4 (radius: 25) [04:08:52 -149292.895703] FAST spr round 5 (radius: 25) [04:09:41 -149292.895379] Model parameter optimization (eps = 1.000000) [04:09:55 -149278.445790] SLOW spr round 1 (radius: 5) [04:11:15 -149251.059335] SLOW spr round 2 (radius: 5) [04:12:36 -149246.986876] SLOW spr round 3 (radius: 5) [04:13:51 -149246.985382] SLOW spr round 4 (radius: 10) [04:15:22 -149246.107682] SLOW spr round 5 (radius: 5) [04:17:02 -149241.758643] SLOW spr round 6 (radius: 5) [04:18:25 -149241.753311] SLOW spr round 7 (radius: 10) [04:20:04 -149241.752362] SLOW spr round 8 (radius: 15) [04:23:13 -149241.324784] SLOW spr round 9 (radius: 5) [04:24:56 -149241.324685] SLOW spr round 10 (radius: 10) [04:26:56 -149241.324644] SLOW spr round 11 (radius: 15) [04:29:51 -149241.324622] SLOW spr round 12 (radius: 20) [04:34:11 -149241.324609] SLOW spr round 13 (radius: 25) [04:38:34 -149241.324600] Model parameter optimization (eps = 0.100000) [04:38:47] [worker #0] ML tree search #16, logLikelihood: -149236.881490 [04:38:47 -438204.979163] Initial branch length optimization [04:38:50 -362176.898654] Model parameter optimization (eps = 10.000000) [04:39:31 -360827.171114] AUTODETECT spr round 1 (radius: 5) [04:40:29 -252748.063052] AUTODETECT spr round 2 (radius: 10) [04:41:34 -194011.913038] AUTODETECT spr round 3 (radius: 15) [04:43:00 -165474.530919] AUTODETECT spr round 4 (radius: 20) [04:44:30 -160831.498962] AUTODETECT spr round 5 (radius: 25) [04:45:50] [worker #1] ML tree search #17, logLikelihood: -149237.026628 [04:46:08 -160345.560489] SPR radius for FAST iterations: 25 (autodetect) [04:46:08 -160345.560489] Model parameter optimization (eps = 3.000000) [04:46:30 -160012.225562] FAST spr round 1 (radius: 25) [04:47:26] [worker #2] ML tree search #18, logLikelihood: -149236.841469 [04:48:27 -149678.966547] FAST spr round 2 (radius: 25) [04:49:51 -149382.020972] FAST spr round 3 (radius: 25) [04:51:03 -149336.329629] FAST spr round 4 (radius: 25) [04:51:59 -149328.840094] FAST spr round 5 (radius: 25) [04:52:44 -149328.833651] Model parameter optimization (eps = 1.000000) [04:52:48 -149328.474336] SLOW spr round 1 (radius: 5) [04:54:12 -149297.151735] SLOW spr round 2 (radius: 5) [04:55:35 -149285.742795] SLOW spr round 3 (radius: 5) [04:56:57 -149277.393032] SLOW spr round 4 (radius: 5) [04:58:17 -149268.850880] SLOW spr round 5 (radius: 5) [04:59:35 -149263.362181] SLOW spr round 6 (radius: 5) [05:00:53 -149260.477159] SLOW spr round 7 (radius: 5) [05:02:09 -149260.474870] SLOW spr round 8 (radius: 10) [05:03:40 -149260.474452] SLOW spr round 9 (radius: 15) [05:07:02 -149258.041512] SLOW spr round 10 (radius: 5) [05:08:48 -149258.013506] SLOW spr round 11 (radius: 10) [05:10:52 -149258.013443] SLOW spr round 12 (radius: 15) [05:14:02 -149258.013401] SLOW spr round 13 (radius: 20) [05:18:47 -149258.013373] SLOW spr round 14 (radius: 25) [05:23:17 -149258.013352] Model parameter optimization (eps = 0.100000) [05:23:21] [worker #0] ML tree search #19, logLikelihood: -149257.942570 [05:25:05] [worker #1] ML tree search #20, logLikelihood: -149243.011742 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.162997,0.787986) (0.085418,1.049946) (0.437839,0.863737) (0.313746,1.286706) 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: -149224.246890 AIC score: 300494.493780 / AICc score: 2395598.493780 / BIC score: 304880.973087 Free parameters (model + branch lengths): 1023 WARNING: Number of free parameters (K=1023) is larger than alignment size (n=538). 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/Q86VF2/3_mltree/Q86VF2.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/3_mltree/Q86VF2.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/3_mltree/Q86VF2.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86VF2/3_mltree/Q86VF2.raxml.log Analysis started: 05-Jul-2021 23:05:53 / finished: 06-Jul-2021 04:30:59 Elapsed time: 19505.409 seconds Consumed energy: 1729.882 Wh (= 9 km in an electric car, or 43 km with an e-scooter!)