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 6140 CPU @ 2.30GHz, 36 cores, 251 GB RAM RAxML-NG was called at 19-Jul-2021 03:07:51 as follows: raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/2_msa/Q8TB22_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22 --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: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/2_msa/Q8TB22_trimmed_msa.fasta [00:00:00] Loaded alignment with 699 taxa and 771 sites WARNING: Sequences tr_J3K969_J3K969_COCIM_246410 and tr_A0A0J6YB93_A0A0J6YB93_COCIT_404692 are exactly identical! WARNING: Sequences tr_B2W2Y5_B2W2Y5_PYRTR_426418 and tr_A0A2W1H5T1_A0A2W1H5T1_9PLEO_45151 are exactly identical! WARNING: Sequences tr_K7AN05_K7AN05_PANTR_9598 and tr_A0A2R9AIE4_A0A2R9AIE4_PANPA_9597 are exactly identical! WARNING: Sequences tr_C6HII8_C6HII8_AJECH_544712 and tr_F0UCN0_F0UCN0_AJEC8_544711 are exactly identical! WARNING: Sequences tr_F7H9M1_F7H9M1_MACMU_9544 and tr_G7PUB0_G7PUB0_MACFA_9541 are exactly identical! WARNING: Sequences tr_F7H9M1_F7H9M1_MACMU_9544 and tr_A0A2K5NTB0_A0A2K5NTB0_CERAT_9531 are exactly identical! WARNING: Sequences tr_F7H9M1_F7H9M1_MACMU_9544 and tr_A0A2K6CWI9_A0A2K6CWI9_MACNE_9545 are exactly identical! WARNING: Sequences tr_G2YQM9_G2YQM9_BOTF4_999810 and tr_M7URD8_M7URD8_BOTF1_1290391 are exactly identical! WARNING: Sequences tr_N4UED5_N4UED5_FUSC1_1229664 and tr_X0CUQ5_X0CUQ5_FUSOX_1089458 are exactly identical! WARNING: Sequences tr_A0A015NAE6_A0A015NAE6_9GLOM_1432141 and tr_A0A2H5UGC1_A0A2H5UGC1_RHIID_747089 are exactly identical! WARNING: Sequences tr_A0A2D0S9J4_A0A2D0S9J4_ICTPU_7998 and tr_W5UE01_W5UE01_ICTPU_7998 are exactly identical! WARNING: Duplicate sequences found: 11 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.reduced.phy Alignment comprises 1 partitions and 771 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 771 / 771 Gaps: 11.77 % Invariant sites: 0.13 % NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.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 699 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 193 / 15440 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -873947.499556] Initial branch length optimization [00:00:06 -752969.567938] Model parameter optimization (eps = 10.000000) [00:00:33 -750301.820166] AUTODETECT spr round 1 (radius: 5) [00:02:12 -536212.777506] AUTODETECT spr round 2 (radius: 10) [00:04:01 -393286.067935] AUTODETECT spr round 3 (radius: 15) [00:06:06 -342485.062522] AUTODETECT spr round 4 (radius: 20) [00:09:14 -326530.243476] AUTODETECT spr round 5 (radius: 25) [00:12:41 -326213.340844] SPR radius for FAST iterations: 25 (autodetect) [00:12:41 -326213.340844] Model parameter optimization (eps = 3.000000) [00:13:04 -326125.989837] FAST spr round 1 (radius: 25) [00:15:09 -290030.310787] FAST spr round 2 (radius: 25) [00:16:47 -288433.716317] FAST spr round 3 (radius: 25) [00:18:13 -288324.399038] FAST spr round 4 (radius: 25) [00:19:28 -288317.839489] FAST spr round 5 (radius: 25) [00:20:37 -288309.677910] FAST spr round 6 (radius: 25) [00:21:45 -288309.677041] Model parameter optimization (eps = 1.000000) [00:22:00 -288302.404017] SLOW spr round 1 (radius: 5) [00:23:48 -288211.596324] SLOW spr round 2 (radius: 5) [00:25:28 -288210.857125] SLOW spr round 3 (radius: 5) [00:27:06 -288207.516952] SLOW spr round 4 (radius: 5) [00:28:42 -288207.515784] SLOW spr round 5 (radius: 10) [00:30:27 -288202.346129] SLOW spr round 6 (radius: 5) [00:32:39 -288202.133521] SLOW spr round 7 (radius: 5) [00:34:31 -288202.132314] SLOW spr round 8 (radius: 10) [00:36:21 -288202.132003] SLOW spr round 9 (radius: 15) [00:39:35 -288202.131866] SLOW spr round 10 (radius: 20) [00:44:36 -288202.131781] SLOW spr round 11 (radius: 25) [00:48:51] [worker #1] ML tree search #2, logLikelihood: -288201.765112 [00:50:17 -288202.131723] Model parameter optimization (eps = 0.100000) [00:50:24] [worker #0] ML tree search #1, logLikelihood: -288202.081270 [00:50:24 -881680.384812] Initial branch length optimization [00:50:30 -761790.358059] Model parameter optimization (eps = 10.000000) [00:51:00 -758992.693103] AUTODETECT spr round 1 (radius: 5) [00:52:39 -534570.491802] AUTODETECT spr round 2 (radius: 10) [00:54:34 -397985.394180] AUTODETECT spr round 3 (radius: 15) [00:56:39 -342145.796474] AUTODETECT spr round 4 (radius: 20) [00:58:52 -333351.679471] AUTODETECT spr round 5 (radius: 25) [01:01:41 -328216.131168] SPR radius for FAST iterations: 25 (autodetect) [01:01:41 -328216.131168] Model parameter optimization (eps = 3.000000) [01:02:02 -328071.808062] FAST spr round 1 (radius: 25) [01:04:07 -289667.908894] FAST spr round 2 (radius: 25) [01:05:42 -288419.273299] FAST spr round 3 (radius: 25) [01:07:09 -288325.306107] FAST spr round 4 (radius: 25) [01:08:27 -288295.489211] FAST spr round 5 (radius: 25) [01:09:37 -288287.915954] FAST spr round 6 (radius: 25) [01:10:44 -288287.911256] Model parameter optimization (eps = 1.000000) [01:10:54 -288280.908397] SLOW spr round 1 (radius: 5) [01:12:44 -288200.766460] SLOW spr round 2 (radius: 5) [01:14:27 -288192.143117] SLOW spr round 3 (radius: 5) [01:16:04 -288192.142536] SLOW spr round 4 (radius: 10) [01:17:50 -288191.750285] SLOW spr round 5 (radius: 5) [01:20:03 -288191.750144] SLOW spr round 6 (radius: 10) [01:22:05 -288191.750140] SLOW spr round 7 (radius: 15) [01:25:16 -288191.335141] SLOW spr round 8 (radius: 5) [01:27:44 -288187.099438] SLOW spr round 9 (radius: 5) [01:29:46 -288185.243884] SLOW spr round 10 (radius: 5) [01:31:32 -288185.243870] SLOW spr round 11 (radius: 10) [01:33:19 -288185.243867] SLOW spr round 12 (radius: 15) [01:36:34 -288185.243864] SLOW spr round 13 (radius: 20) [01:41:31 -288185.243863] SLOW spr round 14 (radius: 25) [01:46:06] [worker #1] ML tree search #4, logLikelihood: -288183.118194 [01:47:24 -288185.243862] Model parameter optimization (eps = 0.100000) [01:47:28] [worker #0] ML tree search #3, logLikelihood: -288185.178801 [01:47:28 -876160.874945] Initial branch length optimization [01:47:35 -756958.776683] Model parameter optimization (eps = 10.000000) [01:48:07 -754127.930608] AUTODETECT spr round 1 (radius: 5) [01:49:46 -539668.794235] AUTODETECT spr round 2 (radius: 10) [01:51:40 -406775.856344] AUTODETECT spr round 3 (radius: 15) [01:53:46 -351472.225958] AUTODETECT spr round 4 (radius: 20) [01:56:36 -326165.473251] AUTODETECT spr round 5 (radius: 25) [01:59:34 -325036.901146] SPR radius for FAST iterations: 25 (autodetect) [01:59:34 -325036.901146] Model parameter optimization (eps = 3.000000) [01:59:52 -324869.887438] FAST spr round 1 (radius: 25) [02:01:53 -289761.552937] FAST spr round 2 (radius: 25) [02:03:32 -288401.648690] FAST spr round 3 (radius: 25) [02:04:57 -288278.890272] FAST spr round 4 (radius: 25) [02:06:11 -288236.106901] FAST spr round 5 (radius: 25) [02:07:19 -288236.010566] Model parameter optimization (eps = 1.000000) [02:07:33 -288233.417610] SLOW spr round 1 (radius: 5) [02:09:23 -288194.673846] SLOW spr round 2 (radius: 5) [02:11:06 -288191.951184] SLOW spr round 3 (radius: 5) [02:12:44 -288191.951125] SLOW spr round 4 (radius: 10) [02:14:29 -288191.951123] SLOW spr round 5 (radius: 15) [02:17:45 -288191.951122] SLOW spr round 6 (radius: 20) [02:22:36 -288191.951122] SLOW spr round 7 (radius: 25) [02:26:57] [worker #1] ML tree search #6, logLikelihood: -288177.776109 [02:28:15 -288191.951122] Model parameter optimization (eps = 0.100000) [02:28:21] [worker #0] ML tree search #5, logLikelihood: -288191.839459 [02:28:21 -885840.572039] Initial branch length optimization [02:28:27 -760984.605508] Model parameter optimization (eps = 10.000000) [02:28:59 -757982.797163] AUTODETECT spr round 1 (radius: 5) [02:30:38 -527608.697622] AUTODETECT spr round 2 (radius: 10) [02:32:32 -388638.578087] AUTODETECT spr round 3 (radius: 15) [02:34:44 -326732.604209] AUTODETECT spr round 4 (radius: 20) [02:37:21 -320074.290311] AUTODETECT spr round 5 (radius: 25) [02:40:12 -318884.552877] SPR radius for FAST iterations: 25 (autodetect) [02:40:12 -318884.552877] Model parameter optimization (eps = 3.000000) [02:40:30 -318784.613693] FAST spr round 1 (radius: 25) [02:42:38 -289656.208755] FAST spr round 2 (radius: 25) [02:44:17 -288351.025870] FAST spr round 3 (radius: 25) [02:45:46 -288290.433283] FAST spr round 4 (radius: 25) [02:46:58 -288287.177628] FAST spr round 5 (radius: 25) [02:48:07 -288287.171688] Model parameter optimization (eps = 1.000000) [02:48:21 -288276.633414] SLOW spr round 1 (radius: 5) [02:50:13 -288205.322254] SLOW spr round 2 (radius: 5) [02:51:58 -288198.190481] SLOW spr round 3 (radius: 5) [02:53:37 -288197.144366] SLOW spr round 4 (radius: 5) [02:55:15 -288197.144351] SLOW spr round 5 (radius: 10) [02:57:02 -288196.756011] SLOW spr round 6 (radius: 5) [02:59:16 -288196.755889] SLOW spr round 7 (radius: 10) [03:01:18 -288196.755889] SLOW spr round 8 (radius: 15) [03:04:31 -288195.165400] SLOW spr round 9 (radius: 5) [03:06:56 -288191.960367] SLOW spr round 10 (radius: 5) [03:08:06] [worker #1] ML tree search #8, logLikelihood: -288208.293468 [03:08:58 -288186.816658] SLOW spr round 11 (radius: 5) [03:10:47 -288182.792456] SLOW spr round 12 (radius: 5) [03:12:29 -288182.631468] SLOW spr round 13 (radius: 5) [03:14:09 -288182.630466] SLOW spr round 14 (radius: 10) [03:15:55 -288182.630459] SLOW spr round 15 (radius: 15) [03:19:14 -288182.630459] SLOW spr round 16 (radius: 20) [03:24:07 -288182.630459] SLOW spr round 17 (radius: 25) [03:29:46 -288182.630459] Model parameter optimization (eps = 0.100000) [03:29:55] [worker #0] ML tree search #7, logLikelihood: -288181.815986 [03:29:55 -870525.070213] Initial branch length optimization [03:30:00 -751230.737585] Model parameter optimization (eps = 10.000000) [03:30:31 -748408.381146] AUTODETECT spr round 1 (radius: 5) [03:32:10 -542682.992395] AUTODETECT spr round 2 (radius: 10) [03:34:04 -416154.279246] AUTODETECT spr round 3 (radius: 15) [03:36:18 -348704.764902] AUTODETECT spr round 4 (radius: 20) [03:39:01 -329083.034225] AUTODETECT spr round 5 (radius: 25) [03:42:16 -327289.787938] SPR radius for FAST iterations: 25 (autodetect) [03:42:16 -327289.787938] Model parameter optimization (eps = 3.000000) [03:42:32 -327187.481350] FAST spr round 1 (radius: 25) [03:44:49 -289980.235330] FAST spr round 2 (radius: 25) [03:46:27 -288400.888785] FAST spr round 3 (radius: 25) [03:47:54 -288306.355384] FAST spr round 4 (radius: 25) [03:49:10 -288277.276508] FAST spr round 5 (radius: 25) [03:49:38] [worker #1] ML tree search #10, logLikelihood: -288180.838204 [03:50:21 -288274.203663] FAST spr round 6 (radius: 25) [03:51:29 -288273.924313] FAST spr round 7 (radius: 25) [03:52:37 -288273.922989] Model parameter optimization (eps = 1.000000) [03:52:50 -288268.757244] SLOW spr round 1 (radius: 5) [03:54:39 -288221.722693] SLOW spr round 2 (radius: 5) [03:56:25 -288208.944014] SLOW spr round 3 (radius: 5) [03:58:03 -288208.793326] SLOW spr round 4 (radius: 5) [03:59:42 -288208.791775] SLOW spr round 5 (radius: 10) [04:01:28 -288208.205653] SLOW spr round 6 (radius: 5) [04:03:41 -288208.205622] SLOW spr round 7 (radius: 10) [04:05:43 -288208.205575] SLOW spr round 8 (radius: 15) [04:08:53 -288208.205573] SLOW spr round 9 (radius: 20) [04:13:59 -288208.205572] SLOW spr round 10 (radius: 25) [04:19:39 -288208.205571] Model parameter optimization (eps = 0.100000) [04:19:48] [worker #0] ML tree search #9, logLikelihood: -288207.862020 [04:19:48 -879484.873946] Initial branch length optimization [04:19:54 -757978.880175] Model parameter optimization (eps = 10.000000) [04:20:27 -755223.690629] AUTODETECT spr round 1 (radius: 5) [04:22:05 -542333.444341] AUTODETECT spr round 2 (radius: 10) [04:23:54 -415984.438288] AUTODETECT spr round 3 (radius: 15) [04:25:54 -351817.800977] AUTODETECT spr round 4 (radius: 20) [04:28:22 -328635.981068] AUTODETECT spr round 5 (radius: 25) [04:31:03] [worker #1] ML tree search #12, logLikelihood: -288186.296935 [04:31:05 -327742.810569] SPR radius for FAST iterations: 25 (autodetect) [04:31:05 -327742.810569] Model parameter optimization (eps = 3.000000) [04:31:25 -327622.748512] FAST spr round 1 (radius: 25) [04:33:23 -289247.630472] FAST spr round 2 (radius: 25) [04:34:56 -288300.177633] FAST spr round 3 (radius: 25) [04:36:19 -288275.906284] FAST spr round 4 (radius: 25) [04:37:30 -288273.710097] FAST spr round 5 (radius: 25) [04:38:38 -288273.709756] Model parameter optimization (eps = 1.000000) [04:38:51 -288271.887430] SLOW spr round 1 (radius: 5) [04:40:41 -288200.880674] SLOW spr round 2 (radius: 5) [04:42:26 -288190.138591] SLOW spr round 3 (radius: 5) [04:44:05 -288190.031421] SLOW spr round 4 (radius: 5) [04:45:44 -288190.030760] SLOW spr round 5 (radius: 10) [04:47:29 -288190.030738] SLOW spr round 6 (radius: 15) [04:50:50 -288189.705767] SLOW spr round 7 (radius: 5) [04:53:15 -288183.381467] SLOW spr round 8 (radius: 5) [04:55:14 -288183.381095] SLOW spr round 9 (radius: 10) [04:57:08 -288183.380969] SLOW spr round 10 (radius: 15) [05:00:23 -288183.380907] SLOW spr round 11 (radius: 20) [05:05:34 -288183.380873] SLOW spr round 12 (radius: 25) [05:11:21 -288183.380853] Model parameter optimization (eps = 0.100000) [05:11:31] [worker #0] ML tree search #11, logLikelihood: -288182.976269 [05:11:31 -870519.857630] Initial branch length optimization [05:11:36 -750500.866892] Model parameter optimization (eps = 10.000000) [05:12:11 -747831.160249] AUTODETECT spr round 1 (radius: 5) [05:13:51 -533285.151690] AUTODETECT spr round 2 (radius: 10) [05:15:39 -410623.730930] AUTODETECT spr round 3 (radius: 15) [05:17:11] [worker #1] ML tree search #14, logLikelihood: -288181.291647 [05:17:36 -357960.234560] AUTODETECT spr round 4 (radius: 20) [05:19:56 -337603.693522] AUTODETECT spr round 5 (radius: 25) [05:22:44 -335629.723539] SPR radius for FAST iterations: 25 (autodetect) [05:22:44 -335629.723539] Model parameter optimization (eps = 3.000000) [05:23:02 -335414.725872] FAST spr round 1 (radius: 25) [05:25:08 -290311.613883] FAST spr round 2 (radius: 25) [05:26:46 -288404.156023] FAST spr round 3 (radius: 25) [05:28:15 -288270.436584] FAST spr round 4 (radius: 25) [05:29:28 -288253.676339] FAST spr round 5 (radius: 25) [05:30:36 -288253.674709] Model parameter optimization (eps = 1.000000) [05:30:50 -288244.042409] SLOW spr round 1 (radius: 5) [05:32:43 -288208.657191] SLOW spr round 2 (radius: 5) [05:34:29 -288205.308344] SLOW spr round 3 (radius: 5) [05:36:13 -288202.878049] SLOW spr round 4 (radius: 5) [05:37:51 -288202.712500] SLOW spr round 5 (radius: 5) [05:39:29 -288202.689125] SLOW spr round 6 (radius: 10) [05:41:17 -288199.051520] SLOW spr round 7 (radius: 5) [05:43:36 -288181.786938] SLOW spr round 8 (radius: 5) [05:45:33 -288175.621018] SLOW spr round 9 (radius: 5) [05:47:17 -288175.620953] SLOW spr round 10 (radius: 10) [05:49:04 -288175.620947] SLOW spr round 11 (radius: 15) [05:52:20 -288175.620944] SLOW spr round 12 (radius: 20) [05:57:16] [worker #1] ML tree search #16, logLikelihood: -288191.057233 [05:57:17 -288175.620943] SLOW spr round 13 (radius: 25) [06:02:59 -288175.620942] Model parameter optimization (eps = 0.100000) [06:03:07] [worker #0] ML tree search #13, logLikelihood: -288175.511607 [06:03:07 -878324.980240] Initial branch length optimization [06:03:13 -756152.485008] Model parameter optimization (eps = 10.000000) [06:03:42 -753421.360152] AUTODETECT spr round 1 (radius: 5) [06:05:23 -545028.922066] AUTODETECT spr round 2 (radius: 10) [06:07:15 -395496.522448] AUTODETECT spr round 3 (radius: 15) [06:09:30 -330549.210819] AUTODETECT spr round 4 (radius: 20) [06:11:57 -323720.201397] AUTODETECT spr round 5 (radius: 25) [06:14:46 -322591.564803] SPR radius for FAST iterations: 25 (autodetect) [06:14:46 -322591.564803] Model parameter optimization (eps = 3.000000) [06:15:05 -322489.571075] FAST spr round 1 (radius: 25) [06:17:11 -289516.632066] FAST spr round 2 (radius: 25) [06:18:46 -288404.721343] FAST spr round 3 (radius: 25) [06:20:15 -288303.349295] FAST spr round 4 (radius: 25) [06:21:36 -288272.708368] FAST spr round 5 (radius: 25) [06:22:46 -288262.907945] FAST spr round 6 (radius: 25) [06:23:55 -288262.907911] Model parameter optimization (eps = 1.000000) [06:24:05 -288261.403962] SLOW spr round 1 (radius: 5) [06:25:55 -288208.253220] SLOW spr round 2 (radius: 5) [06:27:36 -288205.733375] SLOW spr round 3 (radius: 5) [06:29:16 -288205.584407] SLOW spr round 4 (radius: 5) [06:30:55 -288205.583117] SLOW spr round 5 (radius: 10) [06:32:42 -288195.746721] SLOW spr round 6 (radius: 5) [06:35:00 -288179.892634] SLOW spr round 7 (radius: 5) [06:36:54 -288179.892622] SLOW spr round 8 (radius: 10) [06:38:44 -288179.892590] SLOW spr round 9 (radius: 15) [06:42:01 -288179.236162] SLOW spr round 10 (radius: 5) [06:44:25 -288176.877010] SLOW spr round 11 (radius: 5) [06:46:24 -288175.076497] SLOW spr round 12 (radius: 5) [06:48:11 -288175.076386] SLOW spr round 13 (radius: 10) [06:48:56] [worker #1] ML tree search #18, logLikelihood: -288190.503448 [06:49:59 -288175.076341] SLOW spr round 14 (radius: 15) [06:53:13 -288175.076314] SLOW spr round 15 (radius: 20) [06:58:06 -288175.076298] SLOW spr round 16 (radius: 25) [07:03:42 -288175.076289] Model parameter optimization (eps = 0.100000) [07:03:46] [worker #0] ML tree search #15, logLikelihood: -288175.002237 [07:03:47 -877351.893206] Initial branch length optimization [07:03:54 -756666.279479] Model parameter optimization (eps = 10.000000) [07:04:21 -753870.137434] AUTODETECT spr round 1 (radius: 5) [07:06:01 -545078.057245] AUTODETECT spr round 2 (radius: 10) [07:07:54 -407675.365905] AUTODETECT spr round 3 (radius: 15) [07:10:12 -335214.574808] AUTODETECT spr round 4 (radius: 20) [07:12:46 -324561.884477] AUTODETECT spr round 5 (radius: 25) [07:15:51 -324318.513608] SPR radius for FAST iterations: 25 (autodetect) [07:15:51 -324318.513608] Model parameter optimization (eps = 3.000000) [07:16:09 -324155.610783] FAST spr round 1 (radius: 25) [07:18:18 -289788.463455] FAST spr round 2 (radius: 25) [07:19:59 -288311.027539] FAST spr round 3 (radius: 25) [07:21:21 -288259.897514] FAST spr round 4 (radius: 25) [07:22:33 -288251.577049] FAST spr round 5 (radius: 25) [07:23:46 -288246.656366] FAST spr round 6 (radius: 25) [07:24:54 -288246.656168] Model parameter optimization (eps = 1.000000) [07:25:05 -288245.292737] SLOW spr round 1 (radius: 5) [07:26:52 -288211.026487] SLOW spr round 2 (radius: 5) [07:28:35 -288201.742727] SLOW spr round 3 (radius: 5) [07:30:15 -288200.343748] SLOW spr round 4 (radius: 5) [07:31:53 -288200.343333] SLOW spr round 5 (radius: 10) [07:33:39 -288200.343164] SLOW spr round 6 (radius: 15) [07:37:03 -288200.343093] SLOW spr round 7 (radius: 20) [07:42:10 -288200.343063] SLOW spr round 8 (radius: 25) [07:48:03 -288200.343050] Model parameter optimization (eps = 0.100000) [07:48:10] [worker #0] ML tree search #17, logLikelihood: -288200.246395 [07:48:10 -877783.135577] Initial branch length optimization [07:48:16 -756457.813207] Model parameter optimization (eps = 10.000000) [07:49:02 -753733.874482] AUTODETECT spr round 1 (radius: 5) [07:50:42 -533132.024420] AUTODETECT spr round 2 (radius: 10) [07:52:30 -418163.942213] AUTODETECT spr round 3 (radius: 15) [07:53:40] [worker #1] ML tree search #20, logLikelihood: -288169.895963 [07:54:32 -350019.024691] AUTODETECT spr round 4 (radius: 20) [07:56:46 -329422.573220] AUTODETECT spr round 5 (radius: 25) [07:59:36 -323912.449463] SPR radius for FAST iterations: 25 (autodetect) [07:59:36 -323912.449463] Model parameter optimization (eps = 3.000000) [07:59:57 -323849.068878] FAST spr round 1 (radius: 25) [08:01:57 -289579.830811] FAST spr round 2 (radius: 25) [08:03:34 -288337.973896] FAST spr round 3 (radius: 25) [08:04:56 -288301.523994] FAST spr round 4 (radius: 25) [08:06:10 -288290.549227] FAST spr round 5 (radius: 25) [08:07:23 -288279.718044] FAST spr round 6 (radius: 25) [08:08:29 -288279.718026] Model parameter optimization (eps = 1.000000) [08:08:44 -288271.879117] SLOW spr round 1 (radius: 5) [08:10:34 -288201.640954] SLOW spr round 2 (radius: 5) [08:12:14 -288199.206980] SLOW spr round 3 (radius: 5) [08:13:52 -288194.193082] SLOW spr round 4 (radius: 5) [08:15:30 -288194.087152] SLOW spr round 5 (radius: 5) [08:17:08 -288194.086776] SLOW spr round 6 (radius: 10) [08:18:53 -288189.430931] SLOW spr round 7 (radius: 5) [08:21:09 -288183.801763] SLOW spr round 8 (radius: 5) [08:23:02 -288183.801705] SLOW spr round 9 (radius: 10) [08:24:53 -288183.801681] SLOW spr round 10 (radius: 15) [08:28:08 -288183.801670] SLOW spr round 11 (radius: 20) [08:33:11 -288183.801665] SLOW spr round 12 (radius: 25) [08:38:53 -288183.801664] Model parameter optimization (eps = 0.100000) [08:39:01] [worker #0] ML tree search #19, logLikelihood: -288183.417743 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.152800,0.251269) (0.247499,0.375940) (0.299209,0.910061) (0.300493,1.984286) 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: -288169.895963 AIC score: 579141.791925 / AICc score: 4507545.791925 / BIC score: 585653.203337 Free parameters (model + branch lengths): 1401 WARNING: Number of free parameters (K=1401) is larger than alignment size (n=771). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 17 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.bestTreeCollapsed Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.bestTree All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.mlTrees Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.bestModel Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q8TB22/3_mltree/Q8TB22.raxml.log Analysis started: 19-Jul-2021 03:07:51 / finished: 19-Jul-2021 11:46:53 Elapsed time: 31141.871 seconds