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 02-Jul-2021 19:37:33 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/2_msa/Q7Z3V4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4 --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/Q7Z3V4/2_msa/Q7Z3V4_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 794 sites WARNING: Sequences tr_J3KEN9_J3KEN9_COCIM_246410 and tr_A0A0J6YE12_A0A0J6YE12_COCIT_404692 are exactly identical! WARNING: Sequences tr_B6QKP5_B6QKP5_TALMQ_441960 and tr_A0A093XEI8_A0A093XEI8_TALMA_1077442 are exactly identical! WARNING: Sequences tr_B2VWG4_B2VWG4_PYRTR_426418 and tr_A0A2W1G2J5_A0A2W1G2J5_9PLEO_45151 are exactly identical! WARNING: Sequences tr_Q28WT7_Q28WT7_DROPS_46245 and tr_B4H6A1_B4H6A1_DROPE_7234 are exactly identical! WARNING: Sequences tr_H2QVP1_H2QVP1_PANTR_9598 and sp_Q15386_UBE3C_HUMAN_9606 are exactly identical! WARNING: Sequences tr_H2QVP1_H2QVP1_PANTR_9598 and tr_A0A096MSA6_A0A096MSA6_PAPAN_9555 are exactly identical! WARNING: Sequences tr_A0A0E0H9X8_A0A0E0H9X8_ORYNI_4536 and tr_Q5W724_Q5W724_ORYSJ_39947 are exactly identical! WARNING: Sequences tr_A2Q849_A2Q849_ASPNC_425011 and tr_G3XRJ7_G3XRJ7_ASPNA_380704 are exactly identical! WARNING: Sequences tr_H9ERF3_H9ERF3_MACMU_9544 and tr_G7PI66_G7PI66_MACFA_9541 are exactly identical! WARNING: Sequences tr_I1PSN7_I1PSN7_ORYGL_4538 and tr_A0A0D3G3H9_A0A0D3G3H9_9ORYZ_65489 are exactly identical! WARNING: Sequences tr_H0ZAG8_H0ZAG8_TAEGU_59729 and tr_A0A218V5R3_A0A218V5R3_9PASE_299123 are exactly identical! WARNING: Sequences tr_W2Q7G7_W2Q7G7_PHYPN_761204 and tr_A0A0W8DLG3_A0A0W8DLG3_PHYNI_4790 are exactly identical! WARNING: Sequences tr_A0A096MWN6_A0A096MWN6_PAPAN_9555 and tr_A0A0D9S362_A0A0D9S362_CHLSB_60711 are exactly identical! WARNING: Sequences tr_V4RXS5_V4RXS5_9ROSI_85681 and tr_A0A2H5N5X2_A0A2H5N5X2_CITUN_55188 are exactly identical! WARNING: Duplicate sequences found: 14 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.reduced.phy Alignment comprises 1 partitions and 794 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 794 / 794 Gaps: 10.37 % Invariant sites: 0.25 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.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 1001 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 199 / 15920 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -1448039.853067] Initial branch length optimization [00:00:12 -1234691.204004] Model parameter optimization (eps = 10.000000) [00:01:04 -1232018.171437] AUTODETECT spr round 1 (radius: 5) [00:04:31 -888472.222741] AUTODETECT spr round 2 (radius: 10) [00:08:21 -646354.852311] AUTODETECT spr round 3 (radius: 15) [00:12:18 -533003.138980] AUTODETECT spr round 4 (radius: 20) [00:16:26 -502084.471847] AUTODETECT spr round 5 (radius: 25) [00:21:24 -494833.646601] SPR radius for FAST iterations: 25 (autodetect) [00:21:24 -494833.646601] Model parameter optimization (eps = 3.000000) [00:21:51 -494731.287193] FAST spr round 1 (radius: 25) [00:26:45 -435449.457119] FAST spr round 2 (radius: 25) [00:30:20 -433477.781026] FAST spr round 3 (radius: 25) [00:33:21 -433392.194518] FAST spr round 4 (radius: 25) [00:35:53 -433374.759724] FAST spr round 5 (radius: 25) [00:38:00 -433374.759715] Model parameter optimization (eps = 1.000000) [00:38:21 -433369.800989] SLOW spr round 1 (radius: 5) [00:41:53 -433302.137932] SLOW spr round 2 (radius: 5) [00:45:13 -433298.210355] SLOW spr round 3 (radius: 5) [00:48:25 -433295.442375] SLOW spr round 4 (radius: 5) [00:51:32 -433295.442315] SLOW spr round 5 (radius: 10) [00:54:49 -433290.445562] SLOW spr round 6 (radius: 5) [00:58:52 -433284.289075] SLOW spr round 7 (radius: 5) [01:02:21 -433284.288941] SLOW spr round 8 (radius: 10) [01:06:28 -433284.288940] SLOW spr round 9 (radius: 15) [01:13:12 -433284.288939] SLOW spr round 10 (radius: 20) [01:21:44 -433284.288939] SLOW spr round 11 (radius: 25) [01:26:00] [worker #1] ML tree search #2, logLikelihood: -433287.631686 [01:32:41 -433284.288939] Model parameter optimization (eps = 0.100000) [01:32:48] [worker #0] ML tree search #1, logLikelihood: -433284.257988 [01:32:48 -1468268.958688] Initial branch length optimization [01:32:59 -1244026.789816] Model parameter optimization (eps = 10.000000) [01:33:46 -1241376.913267] AUTODETECT spr round 1 (radius: 5) [01:37:12 -879241.697810] AUTODETECT spr round 2 (radius: 10) [01:41:00 -663546.995973] AUTODETECT spr round 3 (radius: 15) [01:44:57 -542250.489957] AUTODETECT spr round 4 (radius: 20) [01:49:10 -498955.905907] AUTODETECT spr round 5 (radius: 25) [01:54:03 -493372.886906] SPR radius for FAST iterations: 25 (autodetect) [01:54:03 -493372.886906] Model parameter optimization (eps = 3.000000) [01:54:28 -493245.612969] FAST spr round 1 (radius: 25) [01:59:17 -435215.989726] FAST spr round 2 (radius: 25) [02:02:46 -433479.929862] FAST spr round 3 (radius: 25) [02:05:42 -433387.646038] FAST spr round 4 (radius: 25) [02:08:18 -433383.939951] FAST spr round 5 (radius: 25) [02:10:39 -433383.939941] Model parameter optimization (eps = 1.000000) [02:10:59 -433349.792175] SLOW spr round 1 (radius: 5) [02:14:30 -433292.622852] SLOW spr round 2 (radius: 5) [02:17:55 -433281.564377] SLOW spr round 3 (radius: 5) [02:21:04 -433277.913135] SLOW spr round 4 (radius: 5) [02:24:10 -433277.913055] SLOW spr round 5 (radius: 10) [02:27:23 -433274.886416] SLOW spr round 6 (radius: 5) [02:31:24 -433273.464910] SLOW spr round 7 (radius: 5) [02:34:53 -433273.464778] SLOW spr round 8 (radius: 10) [02:38:14 -433273.464778] SLOW spr round 9 (radius: 15) [02:43:52 -433273.464778] SLOW spr round 10 (radius: 20) [02:52:23 -433273.464778] SLOW spr round 11 (radius: 25) [03:02:48] [worker #1] ML tree search #4, logLikelihood: -433281.985653 [03:03:16 -433273.464778] Model parameter optimization (eps = 0.100000) [03:03:22] [worker #0] ML tree search #3, logLikelihood: -433273.413557 [03:03:23 -1466739.888600] Initial branch length optimization [03:03:34 -1241121.291835] Model parameter optimization (eps = 10.000000) [03:04:23 -1238554.564551] AUTODETECT spr round 1 (radius: 5) [03:07:49 -878565.463527] AUTODETECT spr round 2 (radius: 10) [03:11:36 -657295.417649] AUTODETECT spr round 3 (radius: 15) [03:15:26 -558576.892101] AUTODETECT spr round 4 (radius: 20) [03:19:52 -509437.684795] AUTODETECT spr round 5 (radius: 25) [03:24:56 -498796.626262] SPR radius for FAST iterations: 25 (autodetect) [03:24:56 -498796.626262] Model parameter optimization (eps = 3.000000) [03:25:20 -498639.454241] FAST spr round 1 (radius: 25) [03:30:08 -436418.622406] FAST spr round 2 (radius: 25) [03:33:42 -433459.551337] FAST spr round 3 (radius: 25) [03:36:38 -433381.939262] FAST spr round 4 (radius: 25) [03:39:03 -433378.396205] FAST spr round 5 (radius: 25) [03:41:25 -433378.396035] Model parameter optimization (eps = 1.000000) [03:41:46 -433365.655018] SLOW spr round 1 (radius: 5) [03:45:10 -433298.750931] SLOW spr round 2 (radius: 5) [03:48:28 -433295.728510] SLOW spr round 3 (radius: 5) [03:51:38 -433295.728336] SLOW spr round 4 (radius: 10) [03:54:55 -433293.551212] SLOW spr round 5 (radius: 5) [03:58:57 -433291.892756] SLOW spr round 6 (radius: 5) [04:02:26 -433291.892632] SLOW spr round 7 (radius: 10) [04:05:55 -433291.892632] SLOW spr round 8 (radius: 15) [04:11:29 -433291.892632] SLOW spr round 9 (radius: 20) [04:19:41 -433291.892632] SLOW spr round 10 (radius: 25) [04:29:58 -433291.892632] Model parameter optimization (eps = 0.100000) [04:30:08] [worker #0] ML tree search #5, logLikelihood: -433291.540683 [04:30:08 -1452703.098833] Initial branch length optimization [04:30:18 -1233797.921484] Model parameter optimization (eps = 10.000000) [04:31:29] [worker #1] ML tree search #6, logLikelihood: -433299.895933 [04:31:29 -1231327.108384] AUTODETECT spr round 1 (radius: 5) [04:34:52 -866529.398180] AUTODETECT spr round 2 (radius: 10) [04:38:42 -656445.262548] AUTODETECT spr round 3 (radius: 15) [04:42:46 -517151.214126] AUTODETECT spr round 4 (radius: 20) [04:47:14 -485035.074883] AUTODETECT spr round 5 (radius: 25) [04:52:28 -483803.961194] SPR radius for FAST iterations: 25 (autodetect) [04:52:28 -483803.961194] Model parameter optimization (eps = 3.000000) [04:52:52 -483659.340927] FAST spr round 1 (radius: 25) [04:57:32 -435284.094083] FAST spr round 2 (radius: 25) [05:01:07 -433521.226326] FAST spr round 3 (radius: 25) [05:03:57 -433396.967184] FAST spr round 4 (radius: 25) [05:06:30 -433385.147572] FAST spr round 5 (radius: 25) [05:08:52 -433380.686645] FAST spr round 6 (radius: 25) [05:11:11 -433380.686615] Model parameter optimization (eps = 1.000000) [05:11:29 -433373.832382] SLOW spr round 1 (radius: 5) [05:14:52 -433304.106739] SLOW spr round 2 (radius: 5) [05:18:07 -433295.717355] SLOW spr round 3 (radius: 5) [05:21:14 -433295.716995] SLOW spr round 4 (radius: 10) [05:24:27 -433295.716986] SLOW spr round 5 (radius: 15) [05:30:14 -433295.716986] SLOW spr round 6 (radius: 20) [05:38:30 -433295.716985] SLOW spr round 7 (radius: 25) [05:46:44] [worker #1] ML tree search #8, logLikelihood: -433290.964711 [05:49:19 -433295.716985] Model parameter optimization (eps = 0.100000) [05:49:28] [worker #0] ML tree search #7, logLikelihood: -433295.667608 [05:49:28 -1452435.549357] Initial branch length optimization [05:49:37 -1230147.196089] Model parameter optimization (eps = 10.000000) [05:50:49 -1226862.333395] AUTODETECT spr round 1 (radius: 5) [05:54:10 -869008.276421] AUTODETECT spr round 2 (radius: 10) [05:57:55 -639503.943326] AUTODETECT spr round 3 (radius: 15) [06:01:44 -558653.439232] AUTODETECT spr round 4 (radius: 20) [06:06:07 -541427.474377] AUTODETECT spr round 5 (radius: 25) [06:11:13 -508206.688280] SPR radius for FAST iterations: 25 (autodetect) [06:11:13 -508206.688280] Model parameter optimization (eps = 3.000000) [06:11:24 -508202.092057] FAST spr round 1 (radius: 25) [06:16:27 -435617.300443] FAST spr round 2 (radius: 25) [06:19:59 -433654.852893] FAST spr round 3 (radius: 25) [06:22:56 -433510.902567] FAST spr round 4 (radius: 25) [06:25:24 -433510.902565] Model parameter optimization (eps = 1.000000) [06:25:49 -433398.232272] SLOW spr round 1 (radius: 5) [06:29:24 -433304.509564] SLOW spr round 2 (radius: 5) [06:32:50 -433287.001528] SLOW spr round 3 (radius: 5) [06:36:03 -433278.580952] SLOW spr round 4 (radius: 5) [06:39:13 -433278.580809] SLOW spr round 5 (radius: 10) [06:42:28 -433278.580775] SLOW spr round 6 (radius: 15) [06:48:20 -433278.580763] SLOW spr round 7 (radius: 20) [06:56:50 -433278.580759] SLOW spr round 8 (radius: 25) [07:02:07] [worker #1] ML tree search #10, logLikelihood: -433314.225918 [07:05:29 -433278.580758] Model parameter optimization (eps = 0.100000) [07:05:36] [worker #0] ML tree search #9, logLikelihood: -433278.438815 [07:05:36 -1445552.814607] Initial branch length optimization [07:05:44 -1225302.857007] Model parameter optimization (eps = 10.000000) [07:06:27 -1222707.668573] AUTODETECT spr round 1 (radius: 5) [07:09:41 -860572.028667] AUTODETECT spr round 2 (radius: 10) [07:13:07 -667276.805773] AUTODETECT spr round 3 (radius: 15) [07:16:41 -569641.361802] AUTODETECT spr round 4 (radius: 20) [07:20:27 -550977.582511] AUTODETECT spr round 5 (radius: 25) [07:24:57 -517582.773058] SPR radius for FAST iterations: 25 (autodetect) [07:24:57 -517582.773058] Model parameter optimization (eps = 3.000000) [07:25:20 -517418.233201] FAST spr round 1 (radius: 25) [07:30:02 -439832.937124] FAST spr round 2 (radius: 25) [07:33:20 -433726.840006] FAST spr round 3 (radius: 25) [07:36:15 -433384.046788] FAST spr round 4 (radius: 25) [07:38:43 -433369.999031] FAST spr round 5 (radius: 25) [07:40:57 -433366.639047] FAST spr round 6 (radius: 25) [07:43:08 -433366.638755] Model parameter optimization (eps = 1.000000) [07:43:31 -433353.145492] SLOW spr round 1 (radius: 5) [07:46:45 -433279.811906] SLOW spr round 2 (radius: 5) [07:49:50 -433270.865092] SLOW spr round 3 (radius: 5) [07:52:45 -433270.864836] SLOW spr round 4 (radius: 10) [07:55:50 -433270.864832] SLOW spr round 5 (radius: 15) [08:01:14 -433270.864831] SLOW spr round 6 (radius: 20) [08:08:50 -433270.864831] SLOW spr round 7 (radius: 25) [08:18:27 -433270.864831] Model parameter optimization (eps = 0.100000) [08:18:33] [worker #0] ML tree search #11, logLikelihood: -433270.841166 [08:18:34 -1462409.932201] Initial branch length optimization [08:18:41 -1241661.082352] Model parameter optimization (eps = 10.000000) [08:19:24 -1239054.745524] AUTODETECT spr round 1 (radius: 5) [08:22:31] [worker #1] ML tree search #12, logLikelihood: -433276.619706 [08:22:35 -868539.837293] AUTODETECT spr round 2 (radius: 10) [08:26:07 -680660.479614] AUTODETECT spr round 3 (radius: 15) [08:29:47 -591184.937482] AUTODETECT spr round 4 (radius: 20) [08:33:50 -518811.673517] AUTODETECT spr round 5 (radius: 25) [08:38:16 -506529.785133] SPR radius for FAST iterations: 25 (autodetect) [08:38:16 -506529.785133] Model parameter optimization (eps = 3.000000) [08:38:39 -506389.708331] FAST spr round 1 (radius: 25) [08:43:11 -435353.477213] FAST spr round 2 (radius: 25) [08:46:21 -433523.176797] FAST spr round 3 (radius: 25) [08:49:05 -433407.100356] FAST spr round 4 (radius: 25) [08:51:24 -433401.293402] FAST spr round 5 (radius: 25) [08:53:35 -433401.293401] Model parameter optimization (eps = 1.000000) [08:53:54 -433385.081191] SLOW spr round 1 (radius: 5) [08:57:18 -433295.311800] SLOW spr round 2 (radius: 5) [09:00:23 -433279.133490] SLOW spr round 3 (radius: 5) [09:03:18 -433278.942017] SLOW spr round 4 (radius: 5) [09:06:10 -433278.941662] SLOW spr round 5 (radius: 10) [09:09:10 -433278.941659] SLOW spr round 6 (radius: 15) [09:14:33 -433278.941659] SLOW spr round 7 (radius: 20) [09:22:16 -433278.941659] SLOW spr round 8 (radius: 25) [09:32:15 -433278.941659] Model parameter optimization (eps = 0.100000) [09:32:20] [worker #0] ML tree search #13, logLikelihood: -433278.911022 [09:32:20 -1457789.865207] Initial branch length optimization [09:32:28 -1237544.198426] Model parameter optimization (eps = 10.000000) [09:33:23 -1234759.964143] AUTODETECT spr round 1 (radius: 5) [09:36:25] [worker #1] ML tree search #14, logLikelihood: -433289.436341 [09:36:34 -862521.340867] AUTODETECT spr round 2 (radius: 10) [09:40:05 -656459.690255] AUTODETECT spr round 3 (radius: 15) [09:43:41 -556329.475700] AUTODETECT spr round 4 (radius: 20) [09:48:13 -504682.486340] AUTODETECT spr round 5 (radius: 25) [09:54:01 -503633.457892] SPR radius for FAST iterations: 25 (autodetect) [09:54:01 -503633.457892] Model parameter optimization (eps = 3.000000) [09:54:29 -503440.965030] FAST spr round 1 (radius: 25) [09:59:07 -435015.689568] FAST spr round 2 (radius: 25) [10:02:21 -433445.121693] FAST spr round 3 (radius: 25) [10:05:11 -433377.084116] FAST spr round 4 (radius: 25) [10:07:28 -433377.084114] Model parameter optimization (eps = 1.000000) [10:07:42 -433375.371292] SLOW spr round 1 (radius: 5) [10:11:06 -433292.585924] SLOW spr round 2 (radius: 5) [10:14:12 -433287.320710] SLOW spr round 3 (radius: 5) [10:17:07 -433287.320395] SLOW spr round 4 (radius: 10) [10:20:10 -433282.764761] SLOW spr round 5 (radius: 5) [10:23:56 -433277.492232] SLOW spr round 6 (radius: 5) [10:27:10 -433277.491476] SLOW spr round 7 (radius: 10) [10:30:20 -433277.221911] SLOW spr round 8 (radius: 5) [10:33:58 -433277.220736] SLOW spr round 9 (radius: 10) [10:37:20 -433277.220736] SLOW spr round 10 (radius: 15) [10:42:18 -433277.220736] SLOW spr round 11 (radius: 20) [10:50:17 -433277.220736] SLOW spr round 12 (radius: 25) [10:53:34] [worker #1] ML tree search #16, logLikelihood: -433291.429659 [11:00:04 -433277.220736] Model parameter optimization (eps = 0.100000) [11:00:09] [worker #0] ML tree search #15, logLikelihood: -433277.161465 [11:00:09 -1458903.169753] Initial branch length optimization [11:00:18 -1239268.858363] Model parameter optimization (eps = 10.000000) [11:00:59 -1236521.196138] AUTODETECT spr round 1 (radius: 5) [11:04:12 -867986.239786] AUTODETECT spr round 2 (radius: 10) [11:07:41 -657932.670716] AUTODETECT spr round 3 (radius: 15) [11:11:24 -560740.690844] AUTODETECT spr round 4 (radius: 20) [11:15:18 -515482.702390] AUTODETECT spr round 5 (radius: 25) [11:20:00 -502221.709025] SPR radius for FAST iterations: 25 (autodetect) [11:20:00 -502221.709025] Model parameter optimization (eps = 3.000000) [11:20:21 -502080.445759] FAST spr round 1 (radius: 25) [11:25:03 -435556.318761] FAST spr round 2 (radius: 25) [11:28:22 -433503.357500] FAST spr round 3 (radius: 25) [11:31:06 -433436.315600] FAST spr round 4 (radius: 25) [11:33:26 -433433.837792] FAST spr round 5 (radius: 25) [11:35:40 -433433.837298] Model parameter optimization (eps = 1.000000) [11:35:57 -433425.701671] SLOW spr round 1 (radius: 5) [11:39:21 -433297.215779] SLOW spr round 2 (radius: 5) [11:42:29 -433288.712983] SLOW spr round 3 (radius: 5) [11:45:27 -433284.147849] SLOW spr round 4 (radius: 5) [11:48:19 -433284.147826] SLOW spr round 5 (radius: 10) [11:51:18 -433284.147826] SLOW spr round 6 (radius: 15) [11:56:40 -433284.147826] SLOW spr round 7 (radius: 20) [12:04:16 -433284.147826] SLOW spr round 8 (radius: 25) [12:04:28] [worker #1] ML tree search #18, logLikelihood: -433288.388300 [12:13:57 -433284.147826] Model parameter optimization (eps = 0.100000) [12:14:09] [worker #0] ML tree search #17, logLikelihood: -433283.584627 [12:14:09 -1458541.155856] Initial branch length optimization [12:14:23 -1241181.284413] Model parameter optimization (eps = 10.000000) [12:15:19 -1238605.973544] AUTODETECT spr round 1 (radius: 5) [12:18:32 -874859.342533] AUTODETECT spr round 2 (radius: 10) [12:22:03 -646470.531860] AUTODETECT spr round 3 (radius: 15) [12:25:47 -527635.099510] AUTODETECT spr round 4 (radius: 20) [12:30:01 -492665.222193] AUTODETECT spr round 5 (radius: 25) [12:35:41 -489869.781741] SPR radius for FAST iterations: 25 (autodetect) [12:35:41 -489869.781741] Model parameter optimization (eps = 3.000000) [12:36:10 -489719.760777] FAST spr round 1 (radius: 25) [12:40:42 -435767.118363] FAST spr round 2 (radius: 25) [12:44:02 -433538.156590] FAST spr round 3 (radius: 25) [12:46:51 -433390.399170] FAST spr round 4 (radius: 25) [12:49:09 -433383.715607] FAST spr round 5 (radius: 25) [12:51:21 -433383.715266] Model parameter optimization (eps = 1.000000) [12:51:42 -433365.162312] SLOW spr round 1 (radius: 5) [12:54:57 -433290.069965] SLOW spr round 2 (radius: 5) [12:58:02 -433287.921462] SLOW spr round 3 (radius: 5) [13:01:00 -433286.878034] SLOW spr round 4 (radius: 5) [13:03:53 -433286.877564] SLOW spr round 5 (radius: 10) [13:06:58 -433286.877542] SLOW spr round 6 (radius: 15) [13:12:27 -433286.877538] SLOW spr round 7 (radius: 20) [13:20:16 -433286.877537] SLOW spr round 8 (radius: 25) [13:30:03] [worker #1] ML tree search #20, logLikelihood: -433287.509604 [13:30:07 -433286.877537] Model parameter optimization (eps = 0.100000) [13:30:16] [worker #0] ML tree search #19, logLikelihood: -433286.726980 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.132326,0.276618) (0.215885,0.369638) (0.405183,0.964281) (0.246606,1.998683) 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: -433270.841166 AIC score: 870551.682332 / AICc score: 8914611.682332 / BIC score: 879929.234671 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=794). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 30 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q7Z3V4/3_mltree/Q7Z3V4.raxml.log Analysis started: 02-Jul-2021 19:37:33 / finished: 03-Jul-2021 09:07:50 Elapsed time: 48616.966 seconds Consumed energy: 4513.525 Wh (= 23 km in an electric car, or 113 km with an e-scooter!)