RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab. Developed by: Alexey M. Kozlov and Alexandros Stamatakis. Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth. Latest version: https://github.com/amkozlov/raxml-ng Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml System: Intel(R) Xeon(R) Gold 6258R CPU @ 2.70GHz, 56 cores, 187 GB RAM RAxML-NG was called at 26-Jul-2021 00:10:20 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/2_msa/A0A0K0K1C4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4 --seed 2 --threads 2 --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 (2 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/2_msa/A0A0K0K1C4_trimmed_msa.fasta [00:00:00] Loaded alignment with 599 taxa and 91 sites WARNING: Sequences tr_A0A075B5J0_A0A075B5J0_MOUSE_10090 and sp_P01734_TVB1_MOUSE_10090 are exactly identical! WARNING: Sequences tr_A0A0B4J1H2_A0A0B4J1H2_MOUSE_10090 and sp_P04213_TVB5_MOUSE_10090 are exactly identical! WARNING: Sequences tr_A0A0B4J1H3_A0A0B4J1H3_MOUSE_10090 and sp_P06320_TVB7_MOUSE_10090 are exactly identical! WARNING: Sequences tr_A0A2I2Y6H0_A0A2I2Y6H0_GORGO_9595 and tr_A0A2I3TNY1_A0A2I3TNY1_PANTR_9598 are exactly identical! WARNING: Sequences tr_A0A2I2Y6H0_A0A2I2Y6H0_GORGO_9595 and tr_A0A2R8ZB88_A0A2R8ZB88_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I2YDX5_A0A2I2YDX5_GORGO_9595 and tr_A0A2I3SG84_A0A2I3SG84_PANTR_9598 are exactly identical! WARNING: Sequences tr_A0A2I2YDX5_A0A2I2YDX5_GORGO_9595 and tr_A0A2R8ZPP1_A0A2R8ZPP1_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I2YNL5_A0A2I2YNL5_GORGO_9595 and sp_A0A0A6YYD4_TVB13_HUMAN_9606 are exactly identical! WARNING: Sequences tr_G3SJ64_G3SJ64_GORGO_9595 and sp_P01733_TVBL3_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A2I3RA64_A0A2I3RA64_PANTR_9598 and tr_A0A2R8Z5W9_A0A2R8Z5W9_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3RKN7_A0A2I3RKN7_PANTR_9598 and tr_A0A2R8ZBA5_A0A2R8ZBA5_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3RXP8_A0A2I3RXP8_PANTR_9598 and tr_A0A2R8ZM38_A0A2R8ZM38_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3SFL4_A0A2I3SFL4_PANTR_9598 and tr_A0A2R8ZH29_A0A2R8ZH29_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3SRN4_A0A2I3SRN4_PANTR_9598 and tr_A0A2R8ZPA5_A0A2R8ZPA5_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3SZE5_A0A2I3SZE5_PANTR_9598 and tr_A0A2R9CRM5_A0A2R9CRM5_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2I3T9H8_A0A2I3T9H8_PANTR_9598 and tr_A0A2R8ZA91_A0A2R8ZA91_PANPA_9597 are exactly identical! WARNING: Sequences sp_A0A075B6N4_TVBY1_HUMAN_9606 and tr_A0A2R8Z9N9_A0A2R8Z9N9_PANPA_9597 are exactly identical! WARNING: Sequences sp_A0A0J9YXY3_TVB62_HUMAN_9606 and sp_P0DPF7_TVB63_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A1D5QLX5_A0A1D5QLX5_MACMU_9544 and tr_A0A2K6ARE7_A0A2K6ARE7_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A1D5QMZ3_A0A1D5QMZ3_MACMU_9544 and tr_G8F2F6_G8F2F6_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A1D5QMZ3_A0A1D5QMZ3_MACMU_9544 and tr_A0A2K6AM41_A0A2K6AM41_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A1D5QWP8_A0A1D5QWP8_MACMU_9544 and tr_G8F2F0_G8F2F0_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A1D5QWP8_A0A1D5QWP8_MACMU_9544 and tr_A0A2K5KHN7_A0A2K5KHN7_CERAT_9531 are exactly identical! WARNING: Sequences tr_A0A1D5QWP8_A0A1D5QWP8_MACMU_9544 and tr_A0A2K6B5F2_A0A2K6B5F2_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A1D5R3T4_A0A1D5R3T4_MACMU_9544 and tr_G8F465_G8F465_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A1D5REJ3_A0A1D5REJ3_MACMU_9544 and tr_A0A2K6DR57_A0A2K6DR57_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A1D5RFK0_A0A1D5RFK0_MACMU_9544 and tr_G8F2F3_G8F2F3_MACFA_9541 are exactly identical! WARNING: Sequences tr_A0A287A9C1_A0A287A9C1_PIG_9823 and tr_A0A287AM90_A0A287AM90_PIG_9823 are exactly identical! WARNING: Sequences tr_A0A2I3LFR1_A0A2I3LFR1_PAPAN_9555 and tr_A0A2K5L243_A0A2K5L243_CERAT_9531 are exactly identical! WARNING: Duplicate sequences found: 29 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.reduced.phy Alignment comprises 1 partitions and 91 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 91 / 91 Gaps: 0.62 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.rba Parallelization scheme autoconfig: 2 worker(s) x 1 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] Generating 20 random starting tree(s) with 599 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 91 / 7280 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -107481.379958] Initial branch length optimization [00:00:02 -93619.334601] Model parameter optimization (eps = 10.000000) [00:00:28 -93427.064376] AUTODETECT spr round 1 (radius: 5) [00:01:42 -66622.422336] AUTODETECT spr round 2 (radius: 10) [00:03:10 -49130.086324] AUTODETECT spr round 3 (radius: 15) [00:04:41 -44410.058467] AUTODETECT spr round 4 (radius: 20) [00:06:31 -42061.255316] AUTODETECT spr round 5 (radius: 25) [00:08:30 -41419.177068] SPR radius for FAST iterations: 25 (autodetect) [00:08:30 -41419.177068] Model parameter optimization (eps = 3.000000) [00:08:46 -41415.028730] FAST spr round 1 (radius: 25) [00:10:15 -36019.235776] FAST spr round 2 (radius: 25) [00:11:26 -35523.543726] FAST spr round 3 (radius: 25) [00:12:33 -35467.690347] FAST spr round 4 (radius: 25) [00:13:33 -35456.524195] FAST spr round 5 (radius: 25) [00:14:36 -35446.624670] FAST spr round 6 (radius: 25) [00:15:34 -35446.301011] FAST spr round 7 (radius: 25) [00:16:32 -35446.300904] Model parameter optimization (eps = 1.000000) [00:16:40 -35445.451035] SLOW spr round 1 (radius: 5) [00:18:09 -35433.055012] SLOW spr round 2 (radius: 5) [00:19:32 -35431.015435] SLOW spr round 3 (radius: 5) [00:20:50 -35431.014415] SLOW spr round 4 (radius: 10) [00:22:12 -35425.806367] SLOW spr round 5 (radius: 5) [00:23:58 -35425.460521] SLOW spr round 6 (radius: 5) [00:25:27 -35425.460511] SLOW spr round 7 (radius: 10) [00:26:49 -35425.379706] SLOW spr round 8 (radius: 15) [00:29:02 -35425.379689] SLOW spr round 9 (radius: 20) [00:29:39] [worker #1] ML tree search #2, logLikelihood: -35392.836787 [00:31:49 -35425.379689] SLOW spr round 10 (radius: 25) [00:34:43 -35424.815167] SLOW spr round 11 (radius: 5) [00:36:36 -35423.777276] SLOW spr round 12 (radius: 5) [00:38:11 -35423.777100] SLOW spr round 13 (radius: 10) [00:39:34 -35423.777099] SLOW spr round 14 (radius: 15) [00:41:46 -35423.777098] SLOW spr round 15 (radius: 20) [00:44:33 -35423.777098] SLOW spr round 16 (radius: 25) [00:47:19 -35423.777098] Model parameter optimization (eps = 0.100000) [00:47:36] [worker #0] ML tree search #1, logLikelihood: -35423.497150 [00:47:36 -107935.238742] Initial branch length optimization [00:47:38 -93768.336026] Model parameter optimization (eps = 10.000000) [00:48:06 -93591.798172] AUTODETECT spr round 1 (radius: 5) [00:49:22 -66232.712793] AUTODETECT spr round 2 (radius: 10) [00:50:48 -49706.816971] AUTODETECT spr round 3 (radius: 15) [00:52:24 -42225.424047] AUTODETECT spr round 4 (radius: 20) [00:54:11 -40575.515434] AUTODETECT spr round 5 (radius: 25) [00:56:13 -40190.642584] SPR radius for FAST iterations: 25 (autodetect) [00:56:13 -40190.642584] Model parameter optimization (eps = 3.000000) [00:56:30 -40168.607913] FAST spr round 1 (radius: 25) [00:57:56 -35685.245621] FAST spr round 2 (radius: 25) [00:59:06 -35461.396969] FAST spr round 3 (radius: 25) [01:00:12 -35437.428169] FAST spr round 4 (radius: 25) [01:01:13 -35430.724279] FAST spr round 5 (radius: 25) [01:02:12 -35427.738799] FAST spr round 6 (radius: 25) [01:03:10 -35427.738792] Model parameter optimization (eps = 1.000000) [01:03:25 -35424.020831] SLOW spr round 1 (radius: 5) [01:03:55] [worker #1] ML tree search #4, logLikelihood: -35455.253169 [01:04:53 -35412.592978] SLOW spr round 2 (radius: 5) [01:06:14 -35411.813370] SLOW spr round 3 (radius: 5) [01:07:32 -35411.813099] SLOW spr round 4 (radius: 10) [01:08:53 -35410.936412] SLOW spr round 5 (radius: 5) [01:10:39 -35407.384539] SLOW spr round 6 (radius: 5) [01:12:10 -35407.384538] SLOW spr round 7 (radius: 10) [01:13:32 -35407.384538] SLOW spr round 8 (radius: 15) [01:15:45 -35407.384538] SLOW spr round 9 (radius: 20) [01:18:32 -35404.663827] SLOW spr round 10 (radius: 5) [01:20:26 -35402.957654] SLOW spr round 11 (radius: 5) [01:22:03 -35401.612209] SLOW spr round 12 (radius: 5) [01:23:29 -35401.612115] SLOW spr round 13 (radius: 10) [01:24:50 -35401.612114] SLOW spr round 14 (radius: 15) [01:27:05 -35401.612114] SLOW spr round 15 (radius: 20) [01:29:57 -35399.161002] SLOW spr round 16 (radius: 5) [01:31:50 -35397.776715] SLOW spr round 17 (radius: 5) [01:33:24 -35397.776687] SLOW spr round 18 (radius: 10) [01:34:47 -35397.776687] SLOW spr round 19 (radius: 15) [01:36:58 -35397.776687] SLOW spr round 20 (radius: 20) [01:39:52 -35397.776687] SLOW spr round 21 (radius: 25) [01:42:54 -35397.776687] Model parameter optimization (eps = 0.100000) [01:43:02] [worker #0] ML tree search #3, logLikelihood: -35397.625766 [01:43:03 -108429.080307] Initial branch length optimization [01:43:04 -94509.608022] Model parameter optimization (eps = 10.000000) [01:43:27 -94342.182505] AUTODETECT spr round 1 (radius: 5) [01:44:42 -66495.101848] AUTODETECT spr round 2 (radius: 10) [01:46:05 -51611.436537] AUTODETECT spr round 3 (radius: 15) [01:47:43 -44839.349294] AUTODETECT spr round 4 (radius: 20) [01:49:50 -42745.356470] AUTODETECT spr round 5 (radius: 25) [01:52:02 -42673.767560] SPR radius for FAST iterations: 25 (autodetect) [01:52:02 -42673.767560] Model parameter optimization (eps = 3.000000) [01:52:11 -42670.584149] FAST spr round 1 (radius: 25) [01:53:37 -37285.430618] FAST spr round 2 (radius: 25) [01:54:51 -36006.229928] FAST spr round 3 (radius: 25) [01:56:00 -35435.076869] FAST spr round 4 (radius: 25) [01:57:04 -35405.122348] FAST spr round 5 (radius: 25) [01:58:02 -35405.121769] Model parameter optimization (eps = 1.000000) [01:58:09 -35404.836929] SLOW spr round 1 (radius: 5) [01:59:39 -35396.213265] SLOW spr round 2 (radius: 5) [02:01:02 -35390.470807] SLOW spr round 3 (radius: 5) [02:02:23 -35387.238956] SLOW spr round 4 (radius: 5) [02:03:42 -35386.869089] SLOW spr round 5 (radius: 5) [02:04:59 -35386.868925] SLOW spr round 6 (radius: 10) [02:06:21 -35384.094150] SLOW spr round 7 (radius: 5) [02:08:06 -35384.093882] SLOW spr round 8 (radius: 10) [02:09:35 -35384.093861] SLOW spr round 9 (radius: 15) [02:11:44 -35384.093849] SLOW spr round 10 (radius: 20) [02:14:18] [worker #1] ML tree search #6, logLikelihood: -35373.590815 [02:14:40 -35384.093841] SLOW spr round 11 (radius: 25) [02:17:27 -35384.093836] Model parameter optimization (eps = 0.100000) [02:17:35] [worker #0] ML tree search #5, logLikelihood: -35383.916169 [02:17:35 -108175.326986] Initial branch length optimization [02:17:37 -94256.811036] Model parameter optimization (eps = 10.000000) [02:18:07 -94097.157066] AUTODETECT spr round 1 (radius: 5) [02:19:23 -67134.769282] AUTODETECT spr round 2 (radius: 10) [02:20:47 -50588.515474] AUTODETECT spr round 3 (radius: 15) [02:22:22 -46239.966146] AUTODETECT spr round 4 (radius: 20) [02:24:08 -44726.456169] AUTODETECT spr round 5 (radius: 25) [02:26:10 -42961.789141] SPR radius for FAST iterations: 25 (autodetect) [02:26:10 -42961.789141] Model parameter optimization (eps = 3.000000) [02:26:29 -42946.970635] FAST spr round 1 (radius: 25) [02:27:58 -36879.819047] FAST spr round 2 (radius: 25) [02:29:08 -36547.383769] FAST spr round 3 (radius: 25) [02:30:17 -36501.439547] FAST spr round 4 (radius: 25) [02:31:18 -36495.197572] FAST spr round 5 (radius: 25) [02:32:18 -36493.641719] FAST spr round 6 (radius: 25) [02:33:16 -36493.641718] Model parameter optimization (eps = 1.000000) [02:33:27 -36491.245878] SLOW spr round 1 (radius: 5) [02:34:55 -36470.006450] SLOW spr round 2 (radius: 5) [02:36:20 -36458.668841] SLOW spr round 3 (radius: 5) [02:37:40 -36456.474910] SLOW spr round 4 (radius: 5) [02:38:59 -36456.474906] SLOW spr round 5 (radius: 10) [02:40:23 -36455.523673] SLOW spr round 6 (radius: 5) [02:42:09 -36455.090037] SLOW spr round 7 (radius: 5) [02:43:40 -36455.090010] SLOW spr round 8 (radius: 10) [02:45:05 -36455.090010] SLOW spr round 9 (radius: 15) [02:47:18 -36455.090010] SLOW spr round 10 (radius: 20) [02:50:06 -36454.285407] SLOW spr round 11 (radius: 5) [02:52:02 -36447.570600] SLOW spr round 12 (radius: 5) [02:53:38 -36446.691148] SLOW spr round 13 (radius: 5) [02:55:05 -36446.690632] SLOW spr round 14 (radius: 10) [02:55:41] [worker #1] ML tree search #8, logLikelihood: -35410.070472 [02:56:28 -36445.381909] SLOW spr round 15 (radius: 5) [02:58:15 -36444.167540] SLOW spr round 16 (radius: 5) [02:59:47 -36442.486481] SLOW spr round 17 (radius: 5) [03:01:13 -36440.378063] SLOW spr round 18 (radius: 5) [03:02:34 -36440.118074] SLOW spr round 19 (radius: 5) [03:03:53 -36440.118073] SLOW spr round 20 (radius: 10) [03:05:16 -36439.643554] SLOW spr round 21 (radius: 5) [03:07:05 -36438.759814] SLOW spr round 22 (radius: 5) [03:08:36 -36438.759805] SLOW spr round 23 (radius: 10) [03:10:00 -36438.759805] SLOW spr round 24 (radius: 15) [03:12:14 -36434.139170] SLOW spr round 25 (radius: 5) [03:14:05 -36433.592378] SLOW spr round 26 (radius: 5) [03:15:39 -36433.592332] SLOW spr round 27 (radius: 10) [03:17:04 -36433.592331] SLOW spr round 28 (radius: 15) [03:19:17 -36433.592331] SLOW spr round 29 (radius: 20) [03:22:09 -36433.592331] SLOW spr round 30 (radius: 25) [03:25:04 -36427.932877] SLOW spr round 31 (radius: 5) [03:25:51] [worker #1] ML tree search #10, logLikelihood: -35396.459070 [03:26:58 -36427.316708] SLOW spr round 32 (radius: 5) [03:28:35 -36425.044627] SLOW spr round 33 (radius: 5) [03:30:01 -36425.044350] SLOW spr round 34 (radius: 10) [03:31:24 -36425.044347] SLOW spr round 35 (radius: 15) [03:33:38 -36425.044347] SLOW spr round 36 (radius: 20) [03:36:31 -36425.044347] SLOW spr round 37 (radius: 25) [03:39:30 -36425.044347] Model parameter optimization (eps = 0.100000) [03:39:37] [worker #0] ML tree search #7, logLikelihood: -36424.926455 [03:39:37 -107356.016797] Initial branch length optimization [03:39:39 -93595.208717] Model parameter optimization (eps = 10.000000) [03:40:06 -93368.946533] AUTODETECT spr round 1 (radius: 5) [03:41:21 -66327.885555] AUTODETECT spr round 2 (radius: 10) [03:42:45 -49299.040135] AUTODETECT spr round 3 (radius: 15) [03:44:20 -42542.941623] AUTODETECT spr round 4 (radius: 20) [03:46:10 -41601.460917] AUTODETECT spr round 5 (radius: 25) [03:48:09 -40553.800631] SPR radius for FAST iterations: 25 (autodetect) [03:48:09 -40553.800631] Model parameter optimization (eps = 3.000000) [03:48:22 -40548.789923] FAST spr round 1 (radius: 25) [03:49:48 -35705.400444] FAST spr round 2 (radius: 25) [03:50:59 -35396.663286] FAST spr round 3 (radius: 25) [03:52:07 -35381.479005] FAST spr round 4 (radius: 25) [03:53:06 -35381.478729] Model parameter optimization (eps = 1.000000) [03:53:14 -35380.857628] SLOW spr round 1 (radius: 5) [03:54:44 -35369.271641] SLOW spr round 2 (radius: 5) [03:56:10 -35362.562593] SLOW spr round 3 (radius: 5) [03:57:31 -35360.994290] SLOW spr round 4 (radius: 5) [03:58:50 -35360.993931] SLOW spr round 5 (radius: 10) [04:00:13 -35359.030806] SLOW spr round 6 (radius: 5) [04:02:00 -35358.726471] SLOW spr round 7 (radius: 5) [04:02:19] [worker #1] ML tree search #12, logLikelihood: -35441.506246 [04:03:32 -35358.726383] SLOW spr round 8 (radius: 10) [04:04:58 -35358.726317] SLOW spr round 9 (radius: 15) [04:07:18 -35357.850034] SLOW spr round 10 (radius: 5) [04:09:09 -35357.666767] SLOW spr round 11 (radius: 5) [04:10:42 -35357.666719] SLOW spr round 12 (radius: 10) [04:12:08 -35357.666706] SLOW spr round 13 (radius: 15) [04:14:29 -35357.666696] SLOW spr round 14 (radius: 20) [04:17:36 -35357.666687] SLOW spr round 15 (radius: 25) [04:20:57 -35357.666681] Model parameter optimization (eps = 0.100000) [04:21:01] [worker #0] ML tree search #9, logLikelihood: -35357.657709 [04:21:01 -108019.852262] Initial branch length optimization [04:21:04 -94301.508869] Model parameter optimization (eps = 10.000000) [04:21:30 -94075.742158] AUTODETECT spr round 1 (radius: 5) [04:22:45 -65027.587979] AUTODETECT spr round 2 (radius: 10) [04:24:08 -51313.506280] AUTODETECT spr round 3 (radius: 15) [04:25:45 -44244.663516] AUTODETECT spr round 4 (radius: 20) [04:27:38 -42197.056890] AUTODETECT spr round 5 (radius: 25) [04:29:42 -41680.507697] SPR radius for FAST iterations: 25 (autodetect) [04:29:42 -41680.507697] Model parameter optimization (eps = 3.000000) [04:30:00 -41676.476528] FAST spr round 1 (radius: 25) [04:31:29 -35838.333297] FAST spr round 2 (radius: 25) [04:32:43 -35471.574991] FAST spr round 3 (radius: 25) [04:33:49 -35436.198061] FAST spr round 4 (radius: 25) [04:34:51 -35422.145133] FAST spr round 5 (radius: 25) [04:35:49 -35418.760461] FAST spr round 6 (radius: 25) [04:36:47 -35416.775089] FAST spr round 7 (radius: 25) [04:37:45 -35416.774942] Model parameter optimization (eps = 1.000000) [04:38:01 -35414.743796] SLOW spr round 1 (radius: 5) [04:38:36] [worker #1] ML tree search #14, logLikelihood: -35365.996595 [04:39:29 -35405.806475] SLOW spr round 2 (radius: 5) [04:40:52 -35402.084453] SLOW spr round 3 (radius: 5) [04:42:10 -35402.084085] SLOW spr round 4 (radius: 10) [04:43:31 -35402.002310] SLOW spr round 5 (radius: 15) [04:45:46 -35402.002310] SLOW spr round 6 (radius: 20) [04:48:37 -35402.002310] SLOW spr round 7 (radius: 25) [04:51:23 -35402.002310] Model parameter optimization (eps = 0.100000) [04:51:27] [worker #0] ML tree search #11, logLikelihood: -35401.999505 [04:51:28 -108011.094837] Initial branch length optimization [04:51:30 -94378.808896] Model parameter optimization (eps = 10.000000) [04:52:01 -94184.111111] AUTODETECT spr round 1 (radius: 5) [04:53:16 -64903.514709] AUTODETECT spr round 2 (radius: 10) [04:54:42 -47986.541454] AUTODETECT spr round 3 (radius: 15) [04:56:16 -45177.736319] AUTODETECT spr round 4 (radius: 20) [04:58:10 -43502.547943] AUTODETECT spr round 5 (radius: 25) [05:00:26 -42128.244886] SPR radius for FAST iterations: 25 (autodetect) [05:00:26 -42128.244886] Model parameter optimization (eps = 3.000000) [05:00:47 -42103.464698] FAST spr round 1 (radius: 25) [05:02:17 -35743.372750] FAST spr round 2 (radius: 25) [05:03:30 -35469.476378] FAST spr round 3 (radius: 25) [05:04:41 -35421.271615] FAST spr round 4 (radius: 25) [05:05:42 -35418.688352] FAST spr round 5 (radius: 25) [05:06:41 -35418.688344] Model parameter optimization (eps = 1.000000) [05:06:55 -35413.275981] SLOW spr round 1 (radius: 5) [05:08:27 -35401.728146] SLOW spr round 2 (radius: 5) [05:09:50 -35400.189722] SLOW spr round 3 (radius: 5) [05:11:11 -35399.542835] SLOW spr round 4 (radius: 5) [05:12:30 -35399.542835] SLOW spr round 5 (radius: 10) [05:13:54 -35391.586683] SLOW spr round 6 (radius: 5) [05:14:27] [worker #1] ML tree search #16, logLikelihood: -35397.277525 [05:15:42 -35385.751573] SLOW spr round 7 (radius: 5) [05:17:13 -35385.749921] SLOW spr round 8 (radius: 10) [05:18:38 -35385.037426] SLOW spr round 9 (radius: 5) [05:20:24 -35384.820813] SLOW spr round 10 (radius: 5) [05:21:55 -35384.820606] SLOW spr round 11 (radius: 10) [05:23:20 -35384.820592] SLOW spr round 12 (radius: 15) [05:25:37 -35384.820584] SLOW spr round 13 (radius: 20) [05:28:39 -35384.820578] SLOW spr round 14 (radius: 25) [05:31:43 -35384.820574] Model parameter optimization (eps = 0.100000) [05:31:48] [worker #0] ML tree search #13, logLikelihood: -35384.777019 [05:31:48 -108503.577212] Initial branch length optimization [05:31:50 -94585.337900] Model parameter optimization (eps = 10.000000) [05:32:12 -94397.678182] AUTODETECT spr round 1 (radius: 5) [05:33:28 -67052.095398] AUTODETECT spr round 2 (radius: 10) [05:34:53 -51351.143955] AUTODETECT spr round 3 (radius: 15) [05:36:30 -44534.170749] AUTODETECT spr round 4 (radius: 20) [05:38:20 -41438.567604] AUTODETECT spr round 5 (radius: 25) [05:40:23 -41029.829201] SPR radius for FAST iterations: 25 (autodetect) [05:40:23 -41029.829201] Model parameter optimization (eps = 3.000000) [05:40:42 -41022.217777] FAST spr round 1 (radius: 25) [05:42:09 -35653.129046] FAST spr round 2 (radius: 25) [05:43:18 -35430.720261] FAST spr round 3 (radius: 25) [05:44:22 -35416.908157] FAST spr round 4 (radius: 25) [05:45:23 -35405.845199] FAST spr round 5 (radius: 25) [05:46:21 -35405.845081] Model parameter optimization (eps = 1.000000) [05:46:33 -35402.013807] SLOW spr round 1 (radius: 5) [05:48:03 -35388.902027] SLOW spr round 2 (radius: 5) [05:49:26 -35385.350727] SLOW spr round 3 (radius: 5) [05:50:15] [worker #1] ML tree search #18, logLikelihood: -35365.061551 [05:50:45 -35385.350561] SLOW spr round 4 (radius: 10) [05:52:09 -35384.405977] SLOW spr round 5 (radius: 5) [05:53:56 -35383.765675] SLOW spr round 6 (radius: 5) [05:55:26 -35383.765662] SLOW spr round 7 (radius: 10) [05:56:52 -35382.896391] SLOW spr round 8 (radius: 5) [05:58:37 -35382.709877] SLOW spr round 9 (radius: 5) [06:00:07 -35382.709843] SLOW spr round 10 (radius: 10) [06:01:32 -35382.709843] SLOW spr round 11 (radius: 15) [06:04:00 -35382.709843] SLOW spr round 12 (radius: 20) [06:07:29 -35382.709843] SLOW spr round 13 (radius: 25) [06:11:22 -35382.709843] Model parameter optimization (eps = 0.100000) [06:11:27] [worker #0] ML tree search #15, logLikelihood: -35382.664238 [06:11:27 -106760.783940] Initial branch length optimization [06:11:29 -93296.688874] Model parameter optimization (eps = 10.000000) [06:11:51 -93147.508994] AUTODETECT spr round 1 (radius: 5) [06:13:05 -64227.352086] AUTODETECT spr round 2 (radius: 10) [06:14:31 -45140.159764] AUTODETECT spr round 3 (radius: 15) [06:16:09 -40233.106299] AUTODETECT spr round 4 (radius: 20) [06:18:15 -39591.977394] AUTODETECT spr round 5 (radius: 25) [06:20:27 -39405.321769] SPR radius for FAST iterations: 25 (autodetect) [06:20:27 -39405.321769] Model parameter optimization (eps = 3.000000) [06:20:47 -39381.460458] FAST spr round 1 (radius: 25) [06:22:11 -35621.113629] FAST spr round 2 (radius: 25) [06:23:25 -35410.691605] FAST spr round 3 (radius: 25) [06:24:16] [worker #1] ML tree search #20, logLikelihood: -35374.540959 [06:24:30 -35392.904121] FAST spr round 4 (radius: 25) [06:25:29 -35392.904085] Model parameter optimization (eps = 1.000000) [06:25:39 -35390.890362] SLOW spr round 1 (radius: 5) [06:27:09 -35384.169542] SLOW spr round 2 (radius: 5) [06:28:30 -35383.131033] SLOW spr round 3 (radius: 5) [06:29:49 -35383.130982] SLOW spr round 4 (radius: 10) [06:31:10 -35382.338200] SLOW spr round 5 (radius: 5) [06:32:59 -35380.184615] SLOW spr round 6 (radius: 5) [06:34:31 -35380.184463] SLOW spr round 7 (radius: 10) [06:35:54 -35379.349506] SLOW spr round 8 (radius: 5) [06:37:39 -35379.220987] SLOW spr round 9 (radius: 5) [06:39:10 -35379.220986] SLOW spr round 10 (radius: 10) [06:40:33 -35379.128395] SLOW spr round 11 (radius: 15) [06:42:49 -35379.128372] SLOW spr round 12 (radius: 20) [06:45:48 -35379.128372] SLOW spr round 13 (radius: 25) [06:49:05 -35379.128372] Model parameter optimization (eps = 0.100000) [06:49:12] [worker #0] ML tree search #17, logLikelihood: -35379.033867 [06:49:13 -108510.885930] Initial branch length optimization [06:49:15 -94400.434131] Model parameter optimization (eps = 10.000000) [06:49:41 -94138.346047] AUTODETECT spr round 1 (radius: 5) [06:50:55 -66984.854760] AUTODETECT spr round 2 (radius: 10) [06:52:21 -48946.276766] AUTODETECT spr round 3 (radius: 15) [06:54:06 -40708.194958] AUTODETECT spr round 4 (radius: 20) [06:56:05 -39742.179561] AUTODETECT spr round 5 (radius: 25) [06:58:14 -39526.182510] SPR radius for FAST iterations: 25 (autodetect) [06:58:14 -39526.182510] Model parameter optimization (eps = 3.000000) [06:58:37 -39514.104873] FAST spr round 1 (radius: 25) [07:00:00 -35642.474591] FAST spr round 2 (radius: 25) [07:01:13 -35415.529393] FAST spr round 3 (radius: 25) [07:02:17 -35400.475919] FAST spr round 4 (radius: 25) [07:03:17 -35398.506144] FAST spr round 5 (radius: 25) [07:04:16 -35396.737476] FAST spr round 6 (radius: 25) [07:05:14 -35396.737398] Model parameter optimization (eps = 1.000000) [07:05:25 -35395.919241] SLOW spr round 1 (radius: 5) [07:06:54 -35382.746970] SLOW spr round 2 (radius: 5) [07:08:15 -35380.986328] SLOW spr round 3 (radius: 5) [07:09:34 -35380.986292] SLOW spr round 4 (radius: 10) [07:10:57 -35380.764139] SLOW spr round 5 (radius: 5) [07:12:43 -35380.763981] SLOW spr round 6 (radius: 10) [07:14:13 -35380.763980] SLOW spr round 7 (radius: 15) [07:16:22 -35380.763980] SLOW spr round 8 (radius: 20) [07:19:23 -35380.763980] SLOW spr round 9 (radius: 25) [07:22:34 -35380.763980] Model parameter optimization (eps = 0.100000) [07:22:42] [worker #0] ML tree search #19, logLikelihood: -35380.705879 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.199195,0.367979) (0.116858,0.458717) (0.376181,0.876567) (0.307766,1.765457) 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: -35357.657709 AIC score: 73117.315418 / AICc score: 2960321.315418 / BIC score: 76132.857685 Free parameters (model + branch lengths): 1201 WARNING: Number of free parameters (K=1201) is larger than alignment size (n=91). This might lead to overfitting and compromise tree inference results! Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A0A0K0K1C4/3_mltree/A0A0K0K1C4.raxml.log Analysis started: 26-Jul-2021 00:10:20 / finished: 26-Jul-2021 07:33:02 Elapsed time: 26562.420 seconds Consumed energy: 1169.463 Wh (= 6 km in an electric car, or 29 km with an e-scooter!)