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 07:35:49 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/2_msa/Q8NCN5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5 --seed 2 --threads 8 --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 (8 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/2_msa/Q8NCN5_trimmed_msa.fasta [00:00:00] Loaded alignment with 469 taxa and 822 sites WARNING: Sequences tr_H2QR51_H2QR51_PANTR_9598 and tr_A0A2R8ZK34_A0A2R8ZK34_PANPA_9597 are exactly identical! WARNING: Sequences tr_F6RY22_F6RY22_MACMU_9544 and tr_G7Q1M1_G7Q1M1_MACFA_9541 are exactly identical! WARNING: Sequences tr_F6RY22_F6RY22_MACMU_9544 and tr_A0A096NLW6_A0A096NLW6_PAPAN_9555 are exactly identical! WARNING: Sequences tr_A0A096MVD4_A0A096MVD4_PAPAN_9555 and tr_A0A2K6B2Z2_A0A2K6B2Z2_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A0V1CH05_A0A0V1CH05_TRIBR_45882 and tr_A0A0V1A3V7_A0A0V1A3V7_9BILA_990121 are exactly identical! WARNING: Sequences tr_A0A0V1CH05_A0A0V1CH05_TRIBR_45882 and tr_A0A0V1NLQ3_A0A0V1NLQ3_9BILA_92180 are exactly identical! WARNING: Sequences tr_A0A0V0XBQ9_A0A0V0XBQ9_9BILA_92179 and tr_A0A0V0URU6_A0A0V0URU6_9BILA_181606 are exactly identical! WARNING: Sequences tr_A0A0V0XBQ9_A0A0V0XBQ9_9BILA_92179 and tr_A0A0V0TMR1_A0A0V0TMR1_9BILA_144512 are exactly identical! WARNING: Duplicate sequences found: 8 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.reduced.phy Alignment comprises 1 partitions and 822 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 822 / 822 Gaps: 14.13 % Invariant sites: 0.12 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.rba Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] Generating 20 random starting tree(s) with 469 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 206 / 16480 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -637381.085425] Initial branch length optimization [00:00:07 -518699.443503] Model parameter optimization (eps = 10.000000) [00:00:52 -516235.747264] AUTODETECT spr round 1 (radius: 5) [00:01:42 -318097.610472] AUTODETECT spr round 2 (radius: 10) [00:02:39 -218757.393674] AUTODETECT spr round 3 (radius: 15) [00:03:56 -179165.397977] AUTODETECT spr round 4 (radius: 20) [00:05:19 -176113.780853] AUTODETECT spr round 5 (radius: 25) [00:06:52 -172080.244539] SPR radius for FAST iterations: 25 (autodetect) [00:06:52 -172080.244539] Model parameter optimization (eps = 3.000000) [00:07:10 -171921.608002] FAST spr round 1 (radius: 25) [00:08:21 -159002.741431] FAST spr round 2 (radius: 25) [00:09:14 -158610.092682] FAST spr round 3 (radius: 25) [00:09:57 -158597.119650] FAST spr round 4 (radius: 25) [00:10:37 -158596.525661] FAST spr round 5 (radius: 25) [00:11:15 -158596.524925] Model parameter optimization (eps = 1.000000) [00:11:26 -158592.193659] SLOW spr round 1 (radius: 5) [00:12:31 -158555.761231] SLOW spr round 2 (radius: 5) [00:13:34 -158555.747445] SLOW spr round 3 (radius: 10) [00:14:37 -158555.744847] SLOW spr round 4 (radius: 15) [00:16:22 -158555.744247] SLOW spr round 5 (radius: 20) [00:18:29 -158555.744094] SLOW spr round 6 (radius: 25) [00:21:05 -158555.744053] Model parameter optimization (eps = 0.100000) [00:21:14] [worker #0] ML tree search #1, logLikelihood: -158555.456300 [00:21:15 -638454.466644] Initial branch length optimization [00:21:18 -523420.864863] Model parameter optimization (eps = 10.000000) [00:21:46 -521101.855129] AUTODETECT spr round 1 (radius: 5) [00:22:38 -308860.876311] AUTODETECT spr round 2 (radius: 10) [00:23:01] [worker #1] ML tree search #2, logLikelihood: -158550.825471 [00:23:35 -200017.243735] AUTODETECT spr round 3 (radius: 15) [00:24:54 -173503.605543] AUTODETECT spr round 4 (radius: 20) [00:26:23 -172239.281750] AUTODETECT spr round 5 (radius: 25) [00:28:08 -171920.076040] SPR radius for FAST iterations: 25 (autodetect) [00:28:08 -171920.076040] Model parameter optimization (eps = 3.000000) [00:28:28 -171735.465652] FAST spr round 1 (radius: 25) [00:29:36 -158885.691597] FAST spr round 2 (radius: 25) [00:30:32 -158603.526770] FAST spr round 3 (radius: 25) [00:31:18 -158586.566627] FAST spr round 4 (radius: 25) [00:31:58 -158586.558447] Model parameter optimization (eps = 1.000000) [00:32:06 -158582.938785] SLOW spr round 1 (radius: 5) [00:33:17 -158559.283452] SLOW spr round 2 (radius: 5) [00:34:23 -158556.662024] SLOW spr round 3 (radius: 5) [00:35:27 -158555.708284] SLOW spr round 4 (radius: 5) [00:36:28 -158555.706697] SLOW spr round 5 (radius: 10) [00:37:34 -158555.706488] SLOW spr round 6 (radius: 15) [00:39:25 -158555.706449] SLOW spr round 7 (radius: 20) [00:41:40 -158555.706441] SLOW spr round 8 (radius: 25) [00:44:23 -158555.706439] Model parameter optimization (eps = 0.100000) [00:44:29] [worker #0] ML tree search #3, logLikelihood: -158555.406471 [00:44:29 -634954.913287] Initial branch length optimization [00:44:34 -515771.166259] Model parameter optimization (eps = 10.000000) [00:45:01 -513394.867492] AUTODETECT spr round 1 (radius: 5) [00:45:51 -324545.365503] AUTODETECT spr round 2 (radius: 10) [00:46:48 -236704.658780] AUTODETECT spr round 3 (radius: 15) [00:47:33] [worker #1] ML tree search #4, logLikelihood: -158557.517019 [00:48:00 -188344.269582] AUTODETECT spr round 4 (radius: 20) [00:49:47 -180718.667824] AUTODETECT spr round 5 (radius: 25) [00:51:39 -180300.096553] SPR radius for FAST iterations: 25 (autodetect) [00:51:39 -180300.096553] Model parameter optimization (eps = 3.000000) [00:52:00 -180071.219238] FAST spr round 1 (radius: 25) [00:53:08 -159369.229277] FAST spr round 2 (radius: 25) [00:54:00 -158641.992330] FAST spr round 3 (radius: 25) [00:54:48 -158589.657298] FAST spr round 4 (radius: 25) [00:55:28 -158589.655488] Model parameter optimization (eps = 1.000000) [00:55:37 -158586.349646] SLOW spr round 1 (radius: 5) [00:56:46 -158553.960013] SLOW spr round 2 (radius: 5) [00:57:51 -158552.857842] SLOW spr round 3 (radius: 5) [00:58:53 -158552.853168] SLOW spr round 4 (radius: 10) [00:59:57 -158552.852817] SLOW spr round 5 (radius: 15) [01:01:46 -158552.852708] SLOW spr round 6 (radius: 20) [01:04:00 -158552.852673] SLOW spr round 7 (radius: 25) [01:06:42 -158552.852662] Model parameter optimization (eps = 0.100000) [01:06:48] [worker #0] ML tree search #5, logLikelihood: -158552.741228 [01:06:49 -630456.341810] Initial branch length optimization [01:06:52 -517426.796808] Model parameter optimization (eps = 10.000000) [01:07:28 -514872.003648] AUTODETECT spr round 1 (radius: 5) [01:08:18 -300304.555939] AUTODETECT spr round 2 (radius: 10) [01:09:13 -240025.470990] AUTODETECT spr round 3 (radius: 15) [01:10:21 -213081.134625] AUTODETECT spr round 4 (radius: 20) [01:11:43 -183767.729904] AUTODETECT spr round 5 (radius: 25) [01:13:10 -182293.826987] SPR radius for FAST iterations: 25 (autodetect) [01:13:10 -182293.826987] Model parameter optimization (eps = 3.000000) [01:13:28 -182115.806361] FAST spr round 1 (radius: 25) [01:14:34] [worker #1] ML tree search #6, logLikelihood: -158558.791052 [01:14:45 -159516.815510] FAST spr round 2 (radius: 25) [01:15:45 -158706.088279] FAST spr round 3 (radius: 25) [01:16:38 -158604.239318] FAST spr round 4 (radius: 25) [01:17:18 -158600.817870] FAST spr round 5 (radius: 25) [01:17:57 -158600.817536] Model parameter optimization (eps = 1.000000) [01:18:07 -158598.142983] SLOW spr round 1 (radius: 5) [01:19:15 -158568.905497] SLOW spr round 2 (radius: 5) [01:20:19 -158566.098676] SLOW spr round 3 (radius: 5) [01:21:21 -158566.098099] SLOW spr round 4 (radius: 10) [01:22:25 -158566.097963] SLOW spr round 5 (radius: 15) [01:24:15 -158566.097930] SLOW spr round 6 (radius: 20) [01:26:27 -158566.097922] SLOW spr round 7 (radius: 25) [01:29:08 -158566.097920] Model parameter optimization (eps = 0.100000) [01:29:16] [worker #0] ML tree search #7, logLikelihood: -158565.822257 [01:29:16 -639290.753782] Initial branch length optimization [01:29:19 -518628.555752] Model parameter optimization (eps = 10.000000) [01:29:55 -516263.831026] AUTODETECT spr round 1 (radius: 5) [01:30:47 -298698.571948] AUTODETECT spr round 2 (radius: 10) [01:31:45 -227888.938604] AUTODETECT spr round 3 (radius: 15) [01:32:54 -182486.371259] AUTODETECT spr round 4 (radius: 20) [01:34:27 -177954.913546] AUTODETECT spr round 5 (radius: 25) [01:36:09] [worker #1] ML tree search #8, logLikelihood: -158563.619809 [01:36:20 -177949.673943] SPR radius for FAST iterations: 25 (autodetect) [01:36:20 -177949.673943] Model parameter optimization (eps = 3.000000) [01:36:39 -177684.915939] FAST spr round 1 (radius: 25) [01:37:56 -159338.938653] FAST spr round 2 (radius: 25) [01:38:57 -158624.266827] FAST spr round 3 (radius: 25) [01:39:48 -158605.250327] FAST spr round 4 (radius: 25) [01:40:29 -158599.127624] FAST spr round 5 (radius: 25) [01:41:09 -158599.126756] Model parameter optimization (eps = 1.000000) [01:41:21 -158594.311389] SLOW spr round 1 (radius: 5) [01:42:33 -158560.241029] SLOW spr round 2 (radius: 5) [01:43:38 -158559.889369] SLOW spr round 3 (radius: 5) [01:44:41 -158559.888997] SLOW spr round 4 (radius: 10) [01:45:46 -158559.888898] SLOW spr round 5 (radius: 15) [01:47:34 -158559.888870] SLOW spr round 6 (radius: 20) [01:49:47 -158559.888862] SLOW spr round 7 (radius: 25) [01:52:28 -158559.888859] Model parameter optimization (eps = 0.100000) [01:52:36] [worker #0] ML tree search #9, logLikelihood: -158559.653046 [01:52:36 -642119.883806] Initial branch length optimization [01:52:40 -523686.699602] Model parameter optimization (eps = 10.000000) [01:53:13 -521280.521884] AUTODETECT spr round 1 (radius: 5) [01:54:04 -315511.703313] AUTODETECT spr round 2 (radius: 10) [01:55:01 -237419.883216] AUTODETECT spr round 3 (radius: 15) [01:56:12 -200522.439610] AUTODETECT spr round 4 (radius: 20) [01:57:41] [worker #1] ML tree search #10, logLikelihood: -158568.904434 [01:57:46 -180379.059541] AUTODETECT spr round 5 (radius: 25) [01:59:19 -179155.401596] SPR radius for FAST iterations: 25 (autodetect) [01:59:19 -179155.401596] Model parameter optimization (eps = 3.000000) [01:59:37 -178968.267699] FAST spr round 1 (radius: 25) [02:00:52 -159200.127936] FAST spr round 2 (radius: 25) [02:01:48 -158673.705898] FAST spr round 3 (radius: 25) [02:02:39 -158612.359020] FAST spr round 4 (radius: 25) [02:03:20 -158603.061964] FAST spr round 5 (radius: 25) [02:03:59 -158603.061082] Model parameter optimization (eps = 1.000000) [02:04:11 -158596.632725] SLOW spr round 1 (radius: 5) [02:05:22 -158574.010691] SLOW spr round 2 (radius: 5) [02:06:26 -158573.962568] SLOW spr round 3 (radius: 10) [02:07:31 -158572.072867] SLOW spr round 4 (radius: 5) [02:08:58 -158568.150416] SLOW spr round 5 (radius: 5) [02:10:12 -158568.150334] SLOW spr round 6 (radius: 10) [02:11:20 -158568.150315] SLOW spr round 7 (radius: 15) [02:13:03 -158568.150310] SLOW spr round 8 (radius: 20) [02:15:09 -158568.150309] SLOW spr round 9 (radius: 25) [02:17:37 -158568.150308] Model parameter optimization (eps = 0.100000) [02:17:42] [worker #0] ML tree search #11, logLikelihood: -158568.067091 [02:17:42 -634792.764100] Initial branch length optimization [02:17:47 -523803.333355] Model parameter optimization (eps = 10.000000) [02:18:05] [worker #1] ML tree search #12, logLikelihood: -158560.425390 [02:18:14 -521421.163941] AUTODETECT spr round 1 (radius: 5) [02:19:07 -299344.109400] AUTODETECT spr round 2 (radius: 10) [02:20:04 -221722.204018] AUTODETECT spr round 3 (radius: 15) [02:21:11 -195858.080934] AUTODETECT spr round 4 (radius: 20) [02:22:53 -178682.349006] AUTODETECT spr round 5 (radius: 25) [02:24:28 -178563.361092] SPR radius for FAST iterations: 25 (autodetect) [02:24:28 -178563.361092] Model parameter optimization (eps = 3.000000) [02:24:46 -178401.921874] FAST spr round 1 (radius: 25) [02:25:58 -159002.315460] FAST spr round 2 (radius: 25) [02:26:54 -158671.126059] FAST spr round 3 (radius: 25) [02:27:46 -158605.118437] FAST spr round 4 (radius: 25) [02:28:26 -158602.334699] FAST spr round 5 (radius: 25) [02:29:04 -158600.042617] FAST spr round 6 (radius: 25) [02:29:41 -158600.042609] Model parameter optimization (eps = 1.000000) [02:29:52 -158596.288922] SLOW spr round 1 (radius: 5) [02:30:59 -158566.150914] SLOW spr round 2 (radius: 5) [02:32:03 -158563.320438] SLOW spr round 3 (radius: 5) [02:33:05 -158556.522590] SLOW spr round 4 (radius: 5) [02:34:06 -158556.522586] SLOW spr round 5 (radius: 10) [02:35:10 -158556.522585] SLOW spr round 6 (radius: 15) [02:36:57 -158556.522585] SLOW spr round 7 (radius: 20) [02:39:08 -158556.522585] SLOW spr round 8 (radius: 25) [02:41:46 -158556.522585] Model parameter optimization (eps = 0.100000) [02:41:54] [worker #0] ML tree search #13, logLikelihood: -158556.348388 [02:41:54 -640222.272872] Initial branch length optimization [02:41:58 -520670.830411] Model parameter optimization (eps = 10.000000) [02:42:25 -518186.655423] AUTODETECT spr round 1 (radius: 5) [02:42:57] [worker #1] ML tree search #14, logLikelihood: -158560.996481 [02:43:17 -311021.277670] AUTODETECT spr round 2 (radius: 10) [02:44:12 -239686.364004] AUTODETECT spr round 3 (radius: 15) [02:45:25 -198589.392508] AUTODETECT spr round 4 (radius: 20) [02:46:56 -183820.188387] AUTODETECT spr round 5 (radius: 25) [02:48:45 -183294.850052] SPR radius for FAST iterations: 25 (autodetect) [02:48:45 -183294.850052] Model parameter optimization (eps = 3.000000) [02:49:01 -183033.628565] FAST spr round 1 (radius: 25) [02:50:20 -159813.970779] FAST spr round 2 (radius: 25) [02:51:18 -158655.338081] FAST spr round 3 (radius: 25) [02:52:06 -158598.117092] FAST spr round 4 (radius: 25) [02:52:47 -158597.947216] FAST spr round 5 (radius: 25) [02:53:28 -158597.947165] Model parameter optimization (eps = 1.000000) [02:53:37 -158593.972755] SLOW spr round 1 (radius: 5) [02:54:46 -158570.637738] SLOW spr round 2 (radius: 5) [02:55:50 -158569.076579] SLOW spr round 3 (radius: 5) [02:56:52 -158569.075408] SLOW spr round 4 (radius: 10) [02:57:55 -158569.075294] SLOW spr round 5 (radius: 15) [02:59:40 -158569.075278] SLOW spr round 6 (radius: 20) [03:01:54 -158569.075274] SLOW spr round 7 (radius: 25) [03:04:41 -158569.075274] Model parameter optimization (eps = 0.100000) [03:04:46] [worker #0] ML tree search #15, logLikelihood: -158569.047969 [03:04:47 -624989.703807] Initial branch length optimization [03:04:50 -507980.731308] Model parameter optimization (eps = 10.000000) [03:05:16 -505618.062772] AUTODETECT spr round 1 (radius: 5) [03:06:05 -316176.086639] AUTODETECT spr round 2 (radius: 10) [03:06:59 -244334.393182] AUTODETECT spr round 3 (radius: 15) [03:08:03] [worker #1] ML tree search #16, logLikelihood: -158555.206607 [03:08:07 -208436.026503] AUTODETECT spr round 4 (radius: 20) [03:09:41 -183455.841349] AUTODETECT spr round 5 (radius: 25) [03:11:32 -182803.140383] SPR radius for FAST iterations: 25 (autodetect) [03:11:32 -182803.140383] Model parameter optimization (eps = 3.000000) [03:11:52 -182577.807285] FAST spr round 1 (radius: 25) [03:13:07 -159516.274841] FAST spr round 2 (radius: 25) [03:14:04 -158695.516591] FAST spr round 3 (radius: 25) [03:14:57 -158603.790847] FAST spr round 4 (radius: 25) [03:15:42 -158591.894035] FAST spr round 5 (radius: 25) [03:16:23 -158591.417351] FAST spr round 6 (radius: 25) [03:17:01 -158591.416943] Model parameter optimization (eps = 1.000000) [03:17:10 -158590.139170] SLOW spr round 1 (radius: 5) [03:18:22 -158567.944542] SLOW spr round 2 (radius: 5) [03:19:27 -158566.637699] SLOW spr round 3 (radius: 5) [03:20:30 -158566.637196] SLOW spr round 4 (radius: 10) [03:21:35 -158566.637100] SLOW spr round 5 (radius: 15) [03:23:25 -158566.637076] SLOW spr round 6 (radius: 20) [03:25:39 -158566.637070] SLOW spr round 7 (radius: 25) [03:28:21 -158566.637068] Model parameter optimization (eps = 0.100000) [03:28:26] [worker #0] ML tree search #17, logLikelihood: -158566.609509 [03:28:26 -640592.415711] Initial branch length optimization [03:28:29 -524979.690774] Model parameter optimization (eps = 10.000000) [03:29:00 -522535.667523] AUTODETECT spr round 1 (radius: 5) [03:29:50 -311854.548858] AUTODETECT spr round 2 (radius: 10) [03:30:38] [worker #1] ML tree search #18, logLikelihood: -158553.529436 [03:30:47 -241217.695403] AUTODETECT spr round 3 (radius: 15) [03:31:58 -200924.458349] AUTODETECT spr round 4 (radius: 20) [03:33:21 -183440.775878] AUTODETECT spr round 5 (radius: 25) [03:34:42 -183056.114111] SPR radius for FAST iterations: 25 (autodetect) [03:34:42 -183056.114111] Model parameter optimization (eps = 3.000000) [03:34:59 -182877.551412] FAST spr round 1 (radius: 25) [03:36:11 -159250.653879] FAST spr round 2 (radius: 25) [03:37:10 -158653.651343] FAST spr round 3 (radius: 25) [03:37:58 -158608.072910] FAST spr round 4 (radius: 25) [03:38:38 -158607.289527] FAST spr round 5 (radius: 25) [03:39:17 -158607.287641] Model parameter optimization (eps = 1.000000) [03:39:29 -158595.212886] SLOW spr round 1 (radius: 5) [03:40:38 -158565.919977] SLOW spr round 2 (radius: 5) [03:41:44 -158560.380918] SLOW spr round 3 (radius: 5) [03:42:45 -158560.379855] SLOW spr round 4 (radius: 10) [03:43:50 -158555.396542] SLOW spr round 5 (radius: 5) [03:45:17 -158555.396484] SLOW spr round 6 (radius: 10) [03:46:34 -158555.396468] SLOW spr round 7 (radius: 15) [03:48:16 -158555.396462] SLOW spr round 8 (radius: 20) [03:50:35 -158555.396460] SLOW spr round 9 (radius: 25) [03:53:19 -158555.396460] Model parameter optimization (eps = 0.100000) [03:53:23] [worker #0] ML tree search #19, logLikelihood: -158555.345938 [03:55:51] [worker #1] ML tree search #20, logLikelihood: -158554.293009 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.152868,0.598515) (0.255391,0.544460) (0.350498,0.804495) (0.241243,2.020707) 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: -158550.825471 AIC score: 318983.650943 / AICc score: 2091827.650943 / BIC score: 323417.398654 Free parameters (model + branch lengths): 941 WARNING: Number of free parameters (K=941) is larger than alignment size (n=822). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 20 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NCN5/3_mltree/Q8NCN5.raxml.log Analysis started: 06-Jul-2021 07:35:49 / finished: 06-Jul-2021 11:31:41 Elapsed time: 14151.332 seconds Consumed energy: 1239.352 Wh (= 6 km in an electric car, or 31 km with an e-scooter!)