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) CPU E5-2690 v4 @ 2.60GHz, 28 cores, 251 GB RAM RAxML-NG was called at 13-Jul-2021 16:35:30 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/2_msa/Q99758_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758 --seed 2 --threads 9 --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 (9 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/2_msa/Q99758_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 1230 sites WARNING: Sequences tr_A0A2I3RDT3_A0A2I3RDT3_PANTR_9598 and sp_P78363_ABCA4_HUMAN_9606 are exactly identical! WARNING: Sequences tr_G7NEL5_G7NEL5_MACMU_9544 and tr_G7PRR9_G7PRR9_MACFA_9541 are exactly identical! WARNING: Sequences tr_G7PLD2_G7PLD2_MACFA_9541 and tr_A0A2K6BQJ9_A0A2K6BQJ9_MACNE_9545 are exactly identical! WARNING: Sequences tr_W2QHM7_W2QHM7_PHYPN_761204 and tr_W2LQC9_W2LQC9_PHYPR_4792 are exactly identical! WARNING: Sequences tr_A0A1D1VFB8_A0A1D1VFB8_RAMVA_947166 and tr_A0A1D1VIP9_A0A1D1VIP9_RAMVA_947166 are exactly identical! WARNING: Sequences tr_A0A2D0QDU2_A0A2D0QDU2_ICTPU_7998 and tr_W5UFP9_W5UFP9_ICTPU_7998 are exactly identical! WARNING: Duplicate sequences found: 6 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/Q99758/3_mltree/Q99758.raxml.reduced.phy Alignment comprises 1 partitions and 1230 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 1230 / 1230 Gaps: 6.00 % Invariant sites: 0.16 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.rba Parallelization scheme autoconfig: 1 worker(s) x 9 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] Generating 20 random starting tree(s) with 1001 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 137 / 10960 [00:00:00] Data distribution: max. searches per worker: 20 Starting ML tree search with 20 distinct starting trees [00:00:00 -2085672.466642] Initial branch length optimization [00:00:05 -1745369.714145] Model parameter optimization (eps = 10.000000) [00:00:53 -1740252.151060] AUTODETECT spr round 1 (radius: 5) [00:03:43 -1275562.570130] AUTODETECT spr round 2 (radius: 10) [00:06:51 -966081.454259] AUTODETECT spr round 3 (radius: 15) [00:10:22 -783826.928972] AUTODETECT spr round 4 (radius: 20) [00:14:28 -716718.737572] AUTODETECT spr round 5 (radius: 25) [00:19:21 -711829.717970] SPR radius for FAST iterations: 25 (autodetect) [00:19:21 -711829.717970] Model parameter optimization (eps = 3.000000) [00:19:47 -711445.774235] FAST spr round 1 (radius: 25) [00:23:25 -638389.867646] FAST spr round 2 (radius: 25) [00:26:11 -635297.311420] FAST spr round 3 (radius: 25) [00:28:40 -635156.485586] FAST spr round 4 (radius: 25) [00:30:48 -635149.286477] FAST spr round 5 (radius: 25) [00:32:48 -635149.286366] Model parameter optimization (eps = 1.000000) [00:33:07 -635139.541244] SLOW spr round 1 (radius: 5) [00:36:03 -634953.509513] SLOW spr round 2 (radius: 5) [00:38:50 -634939.861716] SLOW spr round 3 (radius: 5) [00:41:29 -634939.857140] SLOW spr round 4 (radius: 10) [00:44:15 -634937.783951] SLOW spr round 5 (radius: 5) [00:47:34 -634937.780529] SLOW spr round 6 (radius: 10) [00:50:38 -634937.780345] SLOW spr round 7 (radius: 15) [00:54:59 -634937.780306] SLOW spr round 8 (radius: 20) [01:02:07 -634937.780296] SLOW spr round 9 (radius: 25) [01:11:07 -634937.780293] Model parameter optimization (eps = 0.100000) [01:11:12] ML tree search #1, logLikelihood: -634937.753007 [01:11:13 -2090614.332070] Initial branch length optimization [01:11:18 -1748221.090860] Model parameter optimization (eps = 10.000000) [01:12:02 -1743157.739821] AUTODETECT spr round 1 (radius: 5) [01:14:56 -1281169.114217] AUTODETECT spr round 2 (radius: 10) [01:18:04 -956850.396523] AUTODETECT spr round 3 (radius: 15) [01:21:30 -783427.852168] AUTODETECT spr round 4 (radius: 20) [01:25:23 -727383.869588] AUTODETECT spr round 5 (radius: 25) [01:29:47 -719850.908369] SPR radius for FAST iterations: 25 (autodetect) [01:29:47 -719850.908369] Model parameter optimization (eps = 3.000000) [01:29:57 -719828.771253] FAST spr round 1 (radius: 25) [01:33:44 -638285.064821] FAST spr round 2 (radius: 25) [01:36:37 -635660.189411] FAST spr round 3 (radius: 25) [01:39:06 -635511.204919] FAST spr round 4 (radius: 25) [01:41:16 -635494.989963] FAST spr round 5 (radius: 25) [01:43:20 -635491.557855] FAST spr round 6 (radius: 25) [01:45:22 -635491.557309] Model parameter optimization (eps = 1.000000) [01:45:43 -635105.304589] SLOW spr round 1 (radius: 5) [01:48:37 -634937.453326] SLOW spr round 2 (radius: 5) [01:51:26 -634914.988325] SLOW spr round 3 (radius: 5) [01:54:06 -634913.458045] SLOW spr round 4 (radius: 5) [01:56:45 -634913.458017] SLOW spr round 5 (radius: 10) [01:59:32 -634913.458014] SLOW spr round 6 (radius: 15) [02:04:09 -634913.458014] SLOW spr round 7 (radius: 20) [02:11:07 -634913.458014] SLOW spr round 8 (radius: 25) [02:20:10 -634913.458014] Model parameter optimization (eps = 0.100000) [02:20:14] ML tree search #2, logLikelihood: -634913.443659 [02:20:14 -2081470.566255] Initial branch length optimization [02:20:20 -1746362.224806] Model parameter optimization (eps = 10.000000) [02:21:10 -1740872.722163] AUTODETECT spr round 1 (radius: 5) [02:24:00 -1264740.492922] AUTODETECT spr round 2 (radius: 10) [02:27:06 -1027047.993178] AUTODETECT spr round 3 (radius: 15) [02:30:43 -851435.560164] AUTODETECT spr round 4 (radius: 20) [02:34:49 -784913.211646] AUTODETECT spr round 5 (radius: 25) [02:39:45 -759009.165247] SPR radius for FAST iterations: 25 (autodetect) [02:39:45 -759009.165247] Model parameter optimization (eps = 3.000000) [02:39:56 -758990.788049] FAST spr round 1 (radius: 25) [02:44:06 -642020.537099] FAST spr round 2 (radius: 25) [02:47:01 -635649.509400] FAST spr round 3 (radius: 25) [02:49:34 -635396.688690] FAST spr round 4 (radius: 25) [02:51:45 -635371.589804] FAST spr round 5 (radius: 25) [02:53:49 -635369.981277] FAST spr round 6 (radius: 25) [02:55:50 -635369.981263] Model parameter optimization (eps = 1.000000) [02:56:10 -635038.370931] SLOW spr round 1 (radius: 5) [02:59:05 -634917.168015] SLOW spr round 2 (radius: 5) [03:01:52 -634909.585861] SLOW spr round 3 (radius: 5) [03:04:31 -634909.585831] SLOW spr round 4 (radius: 10) [03:07:18 -634909.585829] SLOW spr round 5 (radius: 15) [03:11:56 -634909.585829] SLOW spr round 6 (radius: 20) [03:18:43 -634909.585829] SLOW spr round 7 (radius: 25) [03:27:42 -634909.585829] Model parameter optimization (eps = 0.100000) [03:27:54] ML tree search #3, logLikelihood: -634909.435480 [03:27:54 -2101839.792423] Initial branch length optimization [03:27:59 -1749694.621335] Model parameter optimization (eps = 10.000000) [03:28:43 -1744416.692911] AUTODETECT spr round 1 (radius: 5) [03:31:34 -1280287.781430] AUTODETECT spr round 2 (radius: 10) [03:34:46 -942338.689173] AUTODETECT spr round 3 (radius: 15) [03:38:09 -768416.237995] AUTODETECT spr round 4 (radius: 20) [03:42:16 -717741.715623] AUTODETECT spr round 5 (radius: 25) [03:47:08 -713967.801958] SPR radius for FAST iterations: 25 (autodetect) [03:47:08 -713967.801958] Model parameter optimization (eps = 3.000000) [03:47:17 -713948.109062] FAST spr round 1 (radius: 25) [03:51:11 -637764.553838] FAST spr round 2 (radius: 25) [03:54:03 -635530.039556] FAST spr round 3 (radius: 25) [03:56:24 -635413.896413] FAST spr round 4 (radius: 25) [03:58:29 -635413.896027] Model parameter optimization (eps = 1.000000) [03:58:50 -635073.382277] SLOW spr round 1 (radius: 5) [04:01:53 -634934.698170] SLOW spr round 2 (radius: 5) [04:04:40 -634931.404546] SLOW spr round 3 (radius: 5) [04:07:19 -634931.404253] SLOW spr round 4 (radius: 10) [04:10:07 -634931.202324] SLOW spr round 5 (radius: 5) [04:13:25 -634929.059565] SLOW spr round 6 (radius: 5) [04:16:21 -634926.426858] SLOW spr round 7 (radius: 5) [04:19:07 -634925.042983] SLOW spr round 8 (radius: 5) [04:21:47 -634925.042397] SLOW spr round 9 (radius: 10) [04:24:35 -634925.007651] SLOW spr round 10 (radius: 15) [04:29:07 -634925.006746] SLOW spr round 11 (radius: 20) [04:35:51 -634925.006531] SLOW spr round 12 (radius: 25) [04:44:35 -634925.006471] Model parameter optimization (eps = 0.100000) [04:44:52] ML tree search #4, logLikelihood: -634923.849112 [04:44:52 -2088812.989151] Initial branch length optimization [04:44:58 -1749793.319670] Model parameter optimization (eps = 10.000000) [04:46:05 -1744549.922467] AUTODETECT spr round 1 (radius: 5) [04:48:57 -1268571.002980] AUTODETECT spr round 2 (radius: 10) [04:52:07 -963445.605834] AUTODETECT spr round 3 (radius: 15) [04:55:24 -793827.031206] AUTODETECT spr round 4 (radius: 20) [04:59:05 -730310.406904] AUTODETECT spr round 5 (radius: 25) [05:03:46 -716688.558720] SPR radius for FAST iterations: 25 (autodetect) [05:03:46 -716688.558720] Model parameter optimization (eps = 3.000000) [05:04:13 -716315.180950] FAST spr round 1 (radius: 25) [05:07:53 -638808.221385] FAST spr round 2 (radius: 25) [05:10:40 -635260.746631] FAST spr round 3 (radius: 25) [05:13:09 -635082.570257] FAST spr round 4 (radius: 25) [05:15:20 -635061.783994] FAST spr round 5 (radius: 25) [05:17:28 -635043.404516] FAST spr round 6 (radius: 25) [05:19:30 -635042.378731] FAST spr round 7 (radius: 25) [05:21:29 -635042.378430] Model parameter optimization (eps = 1.000000) [05:21:53 -635034.370402] SLOW spr round 1 (radius: 5) [05:24:46 -634932.276838] SLOW spr round 2 (radius: 5) [05:27:31 -634918.559394] SLOW spr round 3 (radius: 5) [05:30:11 -634918.559280] SLOW spr round 4 (radius: 10) [05:32:57 -634912.239488] SLOW spr round 5 (radius: 5) [05:36:17 -634910.980634] SLOW spr round 6 (radius: 5) [05:39:14 -634910.980530] SLOW spr round 7 (radius: 10) [05:42:05 -634910.980514] SLOW spr round 8 (radius: 15) [05:46:29 -634910.980511] SLOW spr round 9 (radius: 20) [05:53:11 -634910.980511] SLOW spr round 10 (radius: 25) [06:01:48 -634910.980511] Model parameter optimization (eps = 0.100000) [06:02:04] ML tree search #5, logLikelihood: -634910.093371 [06:02:04 -2080761.266735] Initial branch length optimization [06:02:11 -1743457.620988] Model parameter optimization (eps = 10.000000) [06:02:59 -1738192.803764] AUTODETECT spr round 1 (radius: 5) [06:05:51 -1309027.482827] AUTODETECT spr round 2 (radius: 10) [06:09:01 -1007081.909188] AUTODETECT spr round 3 (radius: 15) [06:12:45 -799829.878111] AUTODETECT spr round 4 (radius: 20) [06:16:47 -737831.221642] AUTODETECT spr round 5 (radius: 25) [06:21:00 -733615.276025] SPR radius for FAST iterations: 25 (autodetect) [06:21:00 -733615.276025] Model parameter optimization (eps = 3.000000) [06:21:26 -733239.126478] FAST spr round 1 (radius: 25) [06:25:16 -638448.532295] FAST spr round 2 (radius: 25) [06:28:06 -635417.072452] FAST spr round 3 (radius: 25) [06:30:35 -635204.003622] FAST spr round 4 (radius: 25) [06:32:44 -635122.797166] FAST spr round 5 (radius: 25) [06:34:47 -635116.815437] FAST spr round 6 (radius: 25) [06:36:48 -635116.815435] Model parameter optimization (eps = 1.000000) [06:37:11 -635091.098555] SLOW spr round 1 (radius: 5) [06:40:06 -634918.652085] SLOW spr round 2 (radius: 5) [06:42:51 -634913.520735] SLOW spr round 3 (radius: 5) [06:45:30 -634913.520397] SLOW spr round 4 (radius: 10) [06:48:19 -634913.520393] SLOW spr round 5 (radius: 15) [06:53:00 -634913.520393] SLOW spr round 6 (radius: 20) [07:00:03 -634913.520393] SLOW spr round 7 (radius: 25) [07:09:10 -634913.520393] Model parameter optimization (eps = 0.100000) [07:09:26] ML tree search #6, logLikelihood: -634913.000356 [07:09:26 -2095118.181143] Initial branch length optimization [07:09:31 -1752402.404426] Model parameter optimization (eps = 10.000000) [07:10:18 -1746961.199953] AUTODETECT spr round 1 (radius: 5) [07:13:12 -1306176.410835] AUTODETECT spr round 2 (radius: 10) [07:16:29 -961433.721714] AUTODETECT spr round 3 (radius: 15) [07:19:51 -785694.882809] AUTODETECT spr round 4 (radius: 20) [07:23:55 -733227.392704] AUTODETECT spr round 5 (radius: 25) [07:28:56 -724995.823330] SPR radius for FAST iterations: 25 (autodetect) [07:28:56 -724995.823330] Model parameter optimization (eps = 3.000000) [07:29:07 -724973.639568] FAST spr round 1 (radius: 25) [07:32:58 -638897.235814] FAST spr round 2 (radius: 25) [07:35:45 -635592.395887] FAST spr round 3 (radius: 25) [07:38:12 -635473.498727] FAST spr round 4 (radius: 25) [07:40:20 -635472.619313] FAST spr round 5 (radius: 25) [07:42:22 -635472.619312] Model parameter optimization (eps = 1.000000) [07:42:43 -635103.856657] SLOW spr round 1 (radius: 5) [07:45:36 -634931.452290] SLOW spr round 2 (radius: 5) [07:48:26 -634916.759739] SLOW spr round 3 (radius: 5) [07:51:07 -634916.758533] SLOW spr round 4 (radius: 10) [07:53:55 -634916.758310] SLOW spr round 5 (radius: 15) [07:58:32 -634916.758259] SLOW spr round 6 (radius: 20) [08:05:30 -634916.758247] SLOW spr round 7 (radius: 25) [08:14:37 -634916.758244] Model parameter optimization (eps = 0.100000) [08:14:45] ML tree search #7, logLikelihood: -634916.712900 [08:14:45 -2088553.783355] Initial branch length optimization [08:14:51 -1751265.574586] Model parameter optimization (eps = 10.000000) [08:15:47 -1746039.158338] AUTODETECT spr round 1 (radius: 5) [08:18:38 -1254225.739737] AUTODETECT spr round 2 (radius: 10) [08:21:45 -956741.256413] AUTODETECT spr round 3 (radius: 15) [08:25:10 -743740.931705] AUTODETECT spr round 4 (radius: 20) [08:29:13 -706848.737932] AUTODETECT spr round 5 (radius: 25) [08:33:55 -703059.691315] SPR radius for FAST iterations: 25 (autodetect) [08:33:55 -703059.691315] Model parameter optimization (eps = 3.000000) [08:34:04 -703039.753357] FAST spr round 1 (radius: 25) [08:37:57 -638716.045342] FAST spr round 2 (radius: 25) [08:40:57 -635627.562114] FAST spr round 3 (radius: 25) [08:43:31 -635467.884529] FAST spr round 4 (radius: 25) [08:45:46 -635441.888426] FAST spr round 5 (radius: 25) [08:47:51 -635431.228190] FAST spr round 6 (radius: 25) [08:49:54 -635431.228098] Model parameter optimization (eps = 1.000000) [08:50:17 -635070.044773] SLOW spr round 1 (radius: 5) [08:53:13 -634931.570684] SLOW spr round 2 (radius: 5) [08:56:00 -634922.470899] SLOW spr round 3 (radius: 5) [08:58:42 -634922.389316] SLOW spr round 4 (radius: 10) [09:01:32 -634922.389028] SLOW spr round 5 (radius: 15) [09:06:12 -634922.388967] SLOW spr round 6 (radius: 20) [09:13:12 -634922.388954] SLOW spr round 7 (radius: 25) [09:22:18 -634922.388950] Model parameter optimization (eps = 0.100000) [09:22:26] ML tree search #8, logLikelihood: -634922.308391 [09:22:27 -2090018.230005] Initial branch length optimization [09:22:35 -1745627.002120] Model parameter optimization (eps = 10.000000) [09:23:22 -1740389.278529] AUTODETECT spr round 1 (radius: 5) [09:26:15 -1283011.640522] AUTODETECT spr round 2 (radius: 10) [09:29:31 -929744.084504] AUTODETECT spr round 3 (radius: 15) [09:33:05 -739704.108246] AUTODETECT spr round 4 (radius: 20) [09:36:40 -708095.421805] AUTODETECT spr round 5 (radius: 25) [09:40:42 -704102.073491] SPR radius for FAST iterations: 25 (autodetect) [09:40:42 -704102.073491] Model parameter optimization (eps = 3.000000) [09:40:53 -704079.772164] FAST spr round 1 (radius: 25) [09:44:42 -637803.932444] FAST spr round 2 (radius: 25) [09:47:36 -635666.129545] FAST spr round 3 (radius: 25) [09:50:09 -635540.746750] FAST spr round 4 (radius: 25) [09:52:18 -635531.586167] FAST spr round 5 (radius: 25) [09:54:21 -635531.585792] Model parameter optimization (eps = 1.000000) [09:54:46 -635072.809687] SLOW spr round 1 (radius: 5) [09:57:49 -634945.772977] SLOW spr round 2 (radius: 5) [10:00:36 -634937.035822] SLOW spr round 3 (radius: 5) [10:03:19 -634935.352059] SLOW spr round 4 (radius: 5) [10:05:58 -634935.352055] SLOW spr round 5 (radius: 10) [10:08:45 -634935.352054] SLOW spr round 6 (radius: 15) [10:13:21 -634935.352054] SLOW spr round 7 (radius: 20) [10:20:06 -634935.352054] SLOW spr round 8 (radius: 25) [10:28:51 -634935.352054] Model parameter optimization (eps = 0.100000) [10:29:00] ML tree search #9, logLikelihood: -634935.262510 [10:29:00 -2095721.191510] Initial branch length optimization [10:29:06 -1749004.540656] Model parameter optimization (eps = 10.000000) [10:30:00 -1743739.872055] AUTODETECT spr round 1 (radius: 5) [10:32:52 -1291447.437135] AUTODETECT spr round 2 (radius: 10) [10:36:07 -969969.641695] AUTODETECT spr round 3 (radius: 15) [10:39:37 -817970.470177] AUTODETECT spr round 4 (radius: 20) [10:43:19 -763378.220555] AUTODETECT spr round 5 (radius: 25) [10:47:08 -752769.182460] SPR radius for FAST iterations: 25 (autodetect) [10:47:09 -752769.182460] Model parameter optimization (eps = 3.000000) [10:47:19 -752750.149611] FAST spr round 1 (radius: 25) [10:51:14 -639657.881556] FAST spr round 2 (radius: 25) [10:54:07 -635671.528907] FAST spr round 3 (radius: 25) [10:56:40 -635457.683867] FAST spr round 4 (radius: 25) [10:58:50 -635415.787249] FAST spr round 5 (radius: 25) [11:00:53 -635415.786223] Model parameter optimization (eps = 1.000000) [11:01:14 -635076.811214] SLOW spr round 1 (radius: 5) [11:04:10 -634919.460740] SLOW spr round 2 (radius: 5) [11:06:56 -634915.034312] SLOW spr round 3 (radius: 5) [11:09:40 -634906.277698] SLOW spr round 4 (radius: 5) [11:12:20 -634905.865600] SLOW spr round 5 (radius: 5) [11:15:00 -634905.864917] SLOW spr round 6 (radius: 10) [11:17:49 -634896.857091] SLOW spr round 7 (radius: 5) [11:21:09 -634896.856915] SLOW spr round 8 (radius: 10) [11:24:14 -634896.856902] SLOW spr round 9 (radius: 15) [11:28:31 -634896.856901] SLOW spr round 10 (radius: 20) [11:35:23 -634896.856901] SLOW spr round 11 (radius: 25) [11:44:12 -634896.856901] Model parameter optimization (eps = 0.100000) [11:44:22] ML tree search #10, logLikelihood: -634896.519616 [11:44:22 -2094733.400569] Initial branch length optimization [11:44:29 -1750940.794449] Model parameter optimization (eps = 10.000000) [11:45:29 -1745597.490054] AUTODETECT spr round 1 (radius: 5) [11:48:20 -1276230.950437] AUTODETECT spr round 2 (radius: 10) [11:51:28 -969095.910137] AUTODETECT spr round 3 (radius: 15) [11:54:54 -783300.094432] AUTODETECT spr round 4 (radius: 20) [11:58:18 -739022.116154] AUTODETECT spr round 5 (radius: 25) [12:03:03 -725345.029318] SPR radius for FAST iterations: 25 (autodetect) [12:03:03 -725345.029318] Model parameter optimization (eps = 3.000000) [12:03:13 -725325.743102] FAST spr round 1 (radius: 25) [12:07:01 -638388.865192] FAST spr round 2 (radius: 25) [12:09:45 -635646.560824] FAST spr round 3 (radius: 25) [12:12:11 -635503.852785] FAST spr round 4 (radius: 25) [12:14:18 -635503.852122] Model parameter optimization (eps = 1.000000) [12:14:41 -635121.188610] SLOW spr round 1 (radius: 5) [12:17:45 -634933.361200] SLOW spr round 2 (radius: 5) [12:20:36 -634924.161029] SLOW spr round 3 (radius: 5) [12:23:21 -634915.069324] SLOW spr round 4 (radius: 5) [12:26:02 -634915.068311] SLOW spr round 5 (radius: 10) [12:28:51 -634915.068238] SLOW spr round 6 (radius: 15) [12:33:29 -634915.068233] SLOW spr round 7 (radius: 20) [12:40:22 -634915.068232] SLOW spr round 8 (radius: 25) [12:49:29 -634915.068232] Model parameter optimization (eps = 0.100000) [12:49:40] ML tree search #11, logLikelihood: -634914.907171 [12:49:40 -2083342.596880] Initial branch length optimization [12:49:45 -1746002.757131] Model parameter optimization (eps = 10.000000) [12:50:45 -1740878.504453] AUTODETECT spr round 1 (radius: 5) [12:53:36 -1278586.673697] AUTODETECT spr round 2 (radius: 10) [12:56:43 -965966.127121] AUTODETECT spr round 3 (radius: 15) [13:00:04 -835173.445046] AUTODETECT spr round 4 (radius: 20) [13:04:42 -747755.241695] AUTODETECT spr round 5 (radius: 25) [13:09:03 -739783.920107] SPR radius for FAST iterations: 25 (autodetect) [13:09:03 -739783.920107] Model parameter optimization (eps = 3.000000) [13:09:28 -739359.348528] FAST spr round 1 (radius: 25) [13:13:27 -639619.145493] FAST spr round 2 (radius: 25) [13:16:24 -635490.658559] FAST spr round 3 (radius: 25) [13:18:54 -635102.482360] FAST spr round 4 (radius: 25) [13:21:01 -635102.480102] Model parameter optimization (eps = 1.000000) [13:21:08 -635102.116545] SLOW spr round 1 (radius: 5) [13:24:11 -634956.015216] SLOW spr round 2 (radius: 5) [13:27:03 -634946.862143] SLOW spr round 3 (radius: 5) [13:29:44 -634946.831506] SLOW spr round 4 (radius: 10) [13:32:33 -634945.566021] SLOW spr round 5 (radius: 5) [13:35:56 -634940.652010] SLOW spr round 6 (radius: 5) [13:38:53 -634940.651924] SLOW spr round 7 (radius: 10) [13:41:47 -634940.651918] SLOW spr round 8 (radius: 15) [13:46:14 -634940.651918] SLOW spr round 9 (radius: 20) [13:53:15 -634940.651918] SLOW spr round 10 (radius: 25) [14:02:11 -634940.651918] Model parameter optimization (eps = 0.100000) [14:02:17] ML tree search #12, logLikelihood: -634940.639879 [14:02:17 -2089945.033775] Initial branch length optimization [14:02:22 -1753175.072579] Model parameter optimization (eps = 10.000000) [14:03:09 -1747774.770911] AUTODETECT spr round 1 (radius: 5) [14:06:00 -1265608.503596] AUTODETECT spr round 2 (radius: 10) [14:09:05 -988678.198332] AUTODETECT spr round 3 (radius: 15) [14:12:37 -856395.242894] AUTODETECT spr round 4 (radius: 20) [14:16:43 -767747.779221] AUTODETECT spr round 5 (radius: 25) [14:21:04 -753624.067221] SPR radius for FAST iterations: 25 (autodetect) [14:21:04 -753624.067221] Model parameter optimization (eps = 3.000000) [14:21:31 -753220.181880] FAST spr round 1 (radius: 25) [14:25:23 -638930.610415] FAST spr round 2 (radius: 25) [14:28:10 -635422.192409] FAST spr round 3 (radius: 25) [14:30:44 -635102.659431] FAST spr round 4 (radius: 25) [14:32:53 -635087.619431] FAST spr round 5 (radius: 25) [14:34:57 -635087.618977] Model parameter optimization (eps = 1.000000) [14:35:16 -635075.155143] SLOW spr round 1 (radius: 5) [14:38:14 -634927.796563] SLOW spr round 2 (radius: 5) [14:41:03 -634913.747655] SLOW spr round 3 (radius: 5) [14:43:44 -634912.212491] SLOW spr round 4 (radius: 5) [14:46:24 -634912.212304] SLOW spr round 5 (radius: 10) [14:49:10 -634912.212304] SLOW spr round 6 (radius: 15) [14:53:43 -634912.212304] SLOW spr round 7 (radius: 20) [15:00:17 -634912.212304] SLOW spr round 8 (radius: 25) [15:08:45 -634912.212304] Model parameter optimization (eps = 0.100000) [15:09:06] ML tree search #13, logLikelihood: -634911.724137 [15:09:06 -2085259.580817] Initial branch length optimization [15:09:11 -1748743.118065] Model parameter optimization (eps = 10.000000) [15:10:03 -1743492.911360] AUTODETECT spr round 1 (radius: 5) [15:12:56 -1286840.756471] AUTODETECT spr round 2 (radius: 10) [15:16:05 -971105.810110] AUTODETECT spr round 3 (radius: 15) [15:19:32 -846758.465456] AUTODETECT spr round 4 (radius: 20) [15:23:40 -752288.407624] AUTODETECT spr round 5 (radius: 25) [15:28:41 -742896.622490] SPR radius for FAST iterations: 25 (autodetect) [15:28:41 -742896.622490] Model parameter optimization (eps = 3.000000) [15:28:51 -742877.401895] FAST spr round 1 (radius: 25) [15:32:59 -638350.831080] FAST spr round 2 (radius: 25) [15:35:58 -635654.893701] FAST spr round 3 (radius: 25) [15:38:31 -635447.561501] FAST spr round 4 (radius: 25) [15:40:45 -635422.655051] FAST spr round 5 (radius: 25) [15:42:48 -635422.654987] Model parameter optimization (eps = 1.000000) [15:43:10 -635069.350857] SLOW spr round 1 (radius: 5) [15:46:14 -634947.193301] SLOW spr round 2 (radius: 5) [15:49:10 -634923.969155] SLOW spr round 3 (radius: 5) [15:51:56 -634917.817596] SLOW spr round 4 (radius: 5) [15:54:37 -634917.816960] SLOW spr round 5 (radius: 10) [15:57:27 -634917.816880] SLOW spr round 6 (radius: 15) [16:02:08 -634917.816870] SLOW spr round 7 (radius: 20) [16:09:05 -634917.816869] SLOW spr round 8 (radius: 25) [16:18:04 -634917.816869] Model parameter optimization (eps = 0.100000) [16:18:15] ML tree search #14, logLikelihood: -634917.486903 [16:18:16 -2090045.490952] Initial branch length optimization [16:18:21 -1753055.893139] Model parameter optimization (eps = 10.000000) [16:19:07 -1747972.135850] AUTODETECT spr round 1 (radius: 5) [16:22:00 -1287391.422695] AUTODETECT spr round 2 (radius: 10) [16:25:08 -983672.028660] AUTODETECT spr round 3 (radius: 15) [16:28:43 -820487.959459] AUTODETECT spr round 4 (radius: 20) [16:32:31 -759890.085411] AUTODETECT spr round 5 (radius: 25) [16:36:59 -737893.344306] SPR radius for FAST iterations: 25 (autodetect) [16:36:59 -737893.344306] Model parameter optimization (eps = 3.000000) [16:37:33 -737488.874191] FAST spr round 1 (radius: 25) [16:41:27 -639246.013717] FAST spr round 2 (radius: 25) [16:44:22 -635364.653261] FAST spr round 3 (radius: 25) [16:46:56 -635182.595667] FAST spr round 4 (radius: 25) [16:49:14 -635069.890307] FAST spr round 5 (radius: 25) [16:51:19 -635062.100731] FAST spr round 6 (radius: 25) [16:53:23 -635056.326119] FAST spr round 7 (radius: 25) [16:55:24 -635056.326004] Model parameter optimization (eps = 1.000000) [16:55:38 -635051.876170] SLOW spr round 1 (radius: 5) [16:58:32 -634908.907468] SLOW spr round 2 (radius: 5) [17:01:15 -634906.246177] SLOW spr round 3 (radius: 5) [17:03:55 -634906.246021] SLOW spr round 4 (radius: 10) [17:06:43 -634906.246019] SLOW spr round 5 (radius: 15) [17:11:21 -634906.246019] SLOW spr round 6 (radius: 20) [17:18:07 -634906.246019] SLOW spr round 7 (radius: 25) [17:26:57 -634906.246019] Model parameter optimization (eps = 0.100000) [17:27:11] ML tree search #15, logLikelihood: -634906.021427 [17:27:11 -2093069.574535] Initial branch length optimization [17:27:18 -1755191.656653] Model parameter optimization (eps = 10.000000) [17:28:09 -1749931.445107] AUTODETECT spr round 1 (radius: 5) [17:31:01 -1294638.682687] AUTODETECT spr round 2 (radius: 10) [17:34:12 -995913.089082] AUTODETECT spr round 3 (radius: 15) [17:37:44 -819046.948266] AUTODETECT spr round 4 (radius: 20) [17:41:39 -740339.602540] AUTODETECT spr round 5 (radius: 25) [17:45:52 -733273.183760] SPR radius for FAST iterations: 25 (autodetect) [17:45:52 -733273.183760] Model parameter optimization (eps = 3.000000) [17:46:21 -732802.438575] FAST spr round 1 (radius: 25) [17:50:13 -641726.294821] FAST spr round 2 (radius: 25) [17:53:08 -635521.776970] FAST spr round 3 (radius: 25) [17:55:39 -635118.366010] FAST spr round 4 (radius: 25) [17:57:46 -635109.642239] FAST spr round 5 (radius: 25) [17:59:47 -635109.642215] Model parameter optimization (eps = 1.000000) [18:00:10 -635099.501480] SLOW spr round 1 (radius: 5) [18:03:09 -634937.023511] SLOW spr round 2 (radius: 5) [18:05:57 -634920.022012] SLOW spr round 3 (radius: 5) [18:08:39 -634920.021929] SLOW spr round 4 (radius: 10) [18:11:25 -634920.021928] SLOW spr round 5 (radius: 15) [18:15:59 -634920.021927] SLOW spr round 6 (radius: 20) [18:22:31 -634920.021927] SLOW spr round 7 (radius: 25) [18:30:59 -634920.021927] Model parameter optimization (eps = 0.100000) [18:31:10] ML tree search #16, logLikelihood: -634919.425145 [18:31:10 -2097725.965554] Initial branch length optimization [18:31:16 -1759093.530778] Model parameter optimization (eps = 10.000000) [18:32:07 -1753621.799937] AUTODETECT spr round 1 (radius: 5) [18:34:59 -1289360.294709] AUTODETECT spr round 2 (radius: 10) [18:38:09 -949400.196047] AUTODETECT spr round 3 (radius: 15) [18:41:41 -772043.943035] AUTODETECT spr round 4 (radius: 20) [18:45:23 -725949.622166] AUTODETECT spr round 5 (radius: 25) [18:49:40 -719834.311846] SPR radius for FAST iterations: 25 (autodetect) [18:49:40 -719834.311846] Model parameter optimization (eps = 3.000000) [18:49:51 -719811.063056] FAST spr round 1 (radius: 25) [18:53:43 -638488.277284] FAST spr round 2 (radius: 25) [18:56:35 -635944.946437] FAST spr round 3 (radius: 25) [18:59:04 -635607.658174] FAST spr round 4 (radius: 25) [19:01:15 -635598.117866] FAST spr round 5 (radius: 25) [19:03:18 -635598.117814] Model parameter optimization (eps = 1.000000) [19:03:40 -635124.353189] SLOW spr round 1 (radius: 5) [19:06:43 -634963.069368] SLOW spr round 2 (radius: 5) [19:09:34 -634950.155959] SLOW spr round 3 (radius: 5) [19:12:15 -634947.441524] SLOW spr round 4 (radius: 5) [19:14:56 -634937.922298] SLOW spr round 5 (radius: 5) [19:17:35 -634937.922223] SLOW spr round 6 (radius: 10) [19:20:22 -634937.922220] SLOW spr round 7 (radius: 15) [19:24:59 -634937.922220] SLOW spr round 8 (radius: 20) [19:31:55 -634937.922220] SLOW spr round 9 (radius: 25) [19:40:54 -634937.922220] Model parameter optimization (eps = 0.100000) [19:41:05] ML tree search #17, logLikelihood: -634937.784412 [19:41:06 -2097521.754749] Initial branch length optimization [19:41:11 -1757120.638395] Model parameter optimization (eps = 10.000000) [19:42:04 -1751691.112159] AUTODETECT spr round 1 (radius: 5) [19:44:55 -1265200.587167] AUTODETECT spr round 2 (radius: 10) [19:48:04 -985104.177354] AUTODETECT spr round 3 (radius: 15) [19:51:30 -833086.925793] AUTODETECT spr round 4 (radius: 20) [19:55:17 -745272.040545] AUTODETECT spr round 5 (radius: 25) [19:59:40 -734795.206972] SPR radius for FAST iterations: 25 (autodetect) [19:59:40 -734795.206972] Model parameter optimization (eps = 3.000000) [19:59:50 -734776.107002] FAST spr round 1 (radius: 25) [20:03:42 -639642.407686] FAST spr round 2 (radius: 25) [20:06:38 -635583.121214] FAST spr round 3 (radius: 25) [20:09:05 -635488.611937] FAST spr round 4 (radius: 25) [20:11:13 -635478.033248] FAST spr round 5 (radius: 25) [20:13:15 -635478.033221] Model parameter optimization (eps = 1.000000) [20:13:39 -635101.946170] SLOW spr round 1 (radius: 5) [20:16:34 -634912.548537] SLOW spr round 2 (radius: 5) [20:19:23 -634893.873503] SLOW spr round 3 (radius: 5) [20:22:05 -634888.406802] SLOW spr round 4 (radius: 5) [20:24:44 -634888.406765] SLOW spr round 5 (radius: 10) [20:27:30 -634888.406765] SLOW spr round 6 (radius: 15) [20:32:04 -634888.406765] SLOW spr round 7 (radius: 20) [20:38:32 -634888.406765] SLOW spr round 8 (radius: 25) [20:47:08 -634888.406765] Model parameter optimization (eps = 0.100000) [20:47:20] ML tree search #18, logLikelihood: -634887.914980 [20:47:20 -2100644.123794] Initial branch length optimization [20:47:25 -1759360.921582] Model parameter optimization (eps = 10.000000) [20:48:22 -1754173.645759] AUTODETECT spr round 1 (radius: 5) [20:51:17 -1276386.376941] AUTODETECT spr round 2 (radius: 10) [20:54:28 -953680.606967] AUTODETECT spr round 3 (radius: 15) [20:57:58 -825347.110399] AUTODETECT spr round 4 (radius: 20) [21:01:34 -773592.395191] AUTODETECT spr round 5 (radius: 25) [21:05:58 -745801.914496] SPR radius for FAST iterations: 25 (autodetect) [21:05:58 -745801.914496] Model parameter optimization (eps = 3.000000) [21:06:41 -745453.646597] FAST spr round 1 (radius: 25) [21:10:39 -638857.444471] FAST spr round 2 (radius: 25) [21:13:34 -635271.618282] FAST spr round 3 (radius: 25) [21:16:01 -635108.521538] FAST spr round 4 (radius: 25) [21:18:09 -635108.521276] Model parameter optimization (eps = 1.000000) [21:18:25 -635103.211846] SLOW spr round 1 (radius: 5) [21:21:29 -634967.791527] SLOW spr round 2 (radius: 5) [21:24:23 -634941.139943] SLOW spr round 3 (radius: 5) [21:27:10 -634925.214363] SLOW spr round 4 (radius: 5) [21:29:50 -634925.214183] SLOW spr round 5 (radius: 10) [21:32:38 -634925.214181] SLOW spr round 6 (radius: 15) [21:37:11 -634925.214181] SLOW spr round 7 (radius: 20) [21:43:46 -634925.214181] SLOW spr round 8 (radius: 25) [21:52:12 -634925.214181] Model parameter optimization (eps = 0.100000) [21:52:26] ML tree search #19, logLikelihood: -634924.589260 [21:52:26 -2077111.049754] Initial branch length optimization [21:52:31 -1733594.070303] Model parameter optimization (eps = 10.000000) [21:53:27 -1728575.108024] AUTODETECT spr round 1 (radius: 5) [21:56:19 -1266149.374516] AUTODETECT spr round 2 (radius: 10) [21:59:30 -953383.136548] AUTODETECT spr round 3 (radius: 15) [22:03:05 -792343.114083] AUTODETECT spr round 4 (radius: 20) [22:06:57 -726315.282766] AUTODETECT spr round 5 (radius: 25) [22:11:40 -712315.634693] SPR radius for FAST iterations: 25 (autodetect) [22:11:40 -712315.634693] Model parameter optimization (eps = 3.000000) [22:12:05 -711921.056329] FAST spr round 1 (radius: 25) [22:15:59 -637288.875502] FAST spr round 2 (radius: 25) [22:18:52 -635194.845672] FAST spr round 3 (radius: 25) [22:21:21 -635103.332216] FAST spr round 4 (radius: 25) [22:23:31 -635097.050641] FAST spr round 5 (radius: 25) [22:25:35 -635097.050601] Model parameter optimization (eps = 1.000000) [22:25:54 -635088.022945] SLOW spr round 1 (radius: 5) [22:28:49 -634941.533832] SLOW spr round 2 (radius: 5) [22:31:38 -634919.555220] SLOW spr round 3 (radius: 5) [22:34:19 -634919.554871] SLOW spr round 4 (radius: 10) [22:37:09 -634915.021138] SLOW spr round 5 (radius: 5) [22:40:29 -634915.021113] SLOW spr round 6 (radius: 10) [22:43:37 -634915.021112] SLOW spr round 7 (radius: 15) [22:47:55 -634915.021112] SLOW spr round 8 (radius: 20) [22:55:03 -634915.021112] SLOW spr round 9 (radius: 25) [23:04:02 -634915.021112] Model parameter optimization (eps = 0.100000) [23:04:20] ML tree search #20, logLikelihood: -634914.853924 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.201364,0.376909) (0.305885,0.592433) (0.367748,1.186084) (0.125003,2.453610) 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: -634887.914980 AIC score: 1273785.829961 / AICc score: 9317845.829961 / BIC score: 1284040.942705 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=1230). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 45 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q99758/3_mltree/Q99758.raxml.log Analysis started: 13-Jul-2021 16:35:30 / finished: 14-Jul-2021 15:39:51 Elapsed time: 83060.860 seconds Consumed energy: 5700.722 Wh (= 29 km in an electric car, or 143 km with an e-scooter!)