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 07-Jul-2021 02:17:26 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/2_msa/Q5JTZ9_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9 --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/Q5JTZ9/2_msa/Q5JTZ9_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 968 sites WARNING: Sequences tr_B6QMI2_B6QMI2_TALMQ_441960 and tr_A0A093UZR3_A0A093UZR3_TALMA_1077442 are exactly identical! WARNING: Sequences tr_B2WCE6_B2WCE6_PYRTR_426418 and tr_A0A2W1G399_A0A2W1G399_9PLEO_45151 are exactly identical! WARNING: Sequences tr_K7B2G8_K7B2G8_PANTR_9598 and tr_A0A2R9C0B8_A0A2R9C0B8_PANPA_9597 are exactly identical! WARNING: Sequences tr_F9FU27_F9FU27_FUSOF_660025 and tr_N4TFT3_N4TFT3_FUSC1_1229664 are exactly identical! WARNING: Sequences tr_F9FU27_F9FU27_FUSOF_660025 and tr_X0CYM3_X0CYM3_FUSOX_1089458 are exactly identical! WARNING: Sequences tr_A2R938_A2R938_ASPNC_425011 and tr_A0A318ZTK4_A0A318ZTK4_9EURO_1450533 are exactly identical! WARNING: Sequences tr_G7XQY3_G7XQY3_ASPKW_1033177 and tr_A0A146FUA6_A0A146FUA6_9EURO_1069201 are exactly identical! WARNING: Sequences tr_G2Y1S3_G2Y1S3_BOTF4_999810 and tr_M7TU49_M7TU49_BOTF1_1290391 are exactly identical! WARNING: Sequences tr_A0A015IJC5_A0A015IJC5_9GLOM_1432141 and tr_U9SGY1_U9SGY1_RHIID_747089 are exactly identical! WARNING: Sequences tr_A0A0F8UP93_A0A0F8UP93_9EURO_308745 and tr_A0A2T5M5H3_A0A2T5M5H3_9EURO_1392256 are exactly identical! WARNING: Sequences tr_A0A165A6R2_A0A165A6R2_9HOMO_1314777 and tr_A0A166I8V8_A0A166I8V8_9HOMO_1314776 are exactly identical! WARNING: Duplicate sequences found: 11 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/Q5JTZ9/3_mltree/Q5JTZ9.raxml.reduced.phy Alignment comprises 1 partitions and 967 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 968 / 967 Gaps: 3.22 % Invariant sites: 1.14 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9.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 / 242 / 19360 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -1440800.574149] Initial branch length optimization [00:00:09 -1246074.270190] Model parameter optimization (eps = 10.000000) [00:00:59 -1244270.851914] AUTODETECT spr round 1 (radius: 5) [00:04:49 -880639.801424] AUTODETECT spr round 2 (radius: 10) [00:09:10 -647716.411440] AUTODETECT spr round 3 (radius: 15) [00:14:10 -542885.373811] AUTODETECT spr round 4 (radius: 20) [00:19:28 -506737.123171] AUTODETECT spr round 5 (radius: 25) [00:25:40 -501705.343232] SPR radius for FAST iterations: 25 (autodetect) [00:25:40 -501705.343232] Model parameter optimization (eps = 3.000000) [00:26:05 -501493.129878] FAST spr round 1 (radius: 25) [00:30:59 -452071.801976] FAST spr round 2 (radius: 25) [00:34:28 -450734.813688] FAST spr round 3 (radius: 25) [00:37:33 -450451.242496] FAST spr round 4 (radius: 25) [00:40:18 -450344.770611] FAST spr round 5 (radius: 25) [00:42:47 -450321.287418] FAST spr round 6 (radius: 25) [00:45:10 -450321.287347] Model parameter optimization (eps = 1.000000) [00:45:25 -450317.939863] SLOW spr round 1 (radius: 5) [00:49:22 -450199.385832] SLOW spr round 2 (radius: 5) [00:52:58 -450180.062920] SLOW spr round 3 (radius: 5) [00:56:24 -450180.062816] SLOW spr round 4 (radius: 10) [00:59:55 -450180.062815] SLOW spr round 5 (radius: 15) [01:06:05 -450180.062815] SLOW spr round 6 (radius: 20) [01:15:12 -450180.062815] SLOW spr round 7 (radius: 25) [01:25:02] [worker #1] ML tree search #2, logLikelihood: -450162.734956 [01:26:09 -450180.062815] Model parameter optimization (eps = 0.100000) [01:26:16] [worker #0] ML tree search #1, logLikelihood: -450179.996550 [01:26:16 -1434867.465695] Initial branch length optimization [01:26:23 -1245257.624474] Model parameter optimization (eps = 10.000000) [01:27:24 -1243390.808843] AUTODETECT spr round 1 (radius: 5) [01:31:17 -896784.134759] AUTODETECT spr round 2 (radius: 10) [01:35:51 -647135.151958] AUTODETECT spr round 3 (radius: 15) [01:40:38 -559555.630459] AUTODETECT spr round 4 (radius: 20) [01:45:44 -528330.132633] AUTODETECT spr round 5 (radius: 25) [01:52:16 -512703.197315] SPR radius for FAST iterations: 25 (autodetect) [01:52:16 -512703.197315] Model parameter optimization (eps = 3.000000) [01:52:35 -512548.303978] FAST spr round 1 (radius: 25) [01:57:28 -452523.110982] FAST spr round 2 (radius: 25) [02:01:15 -450467.897930] FAST spr round 3 (radius: 25) [02:04:26 -450316.170185] FAST spr round 4 (radius: 25) [02:07:08 -450309.635497] FAST spr round 5 (radius: 25) [02:09:44 -450309.635223] Model parameter optimization (eps = 1.000000) [02:09:54 -450309.012088] SLOW spr round 1 (radius: 5) [02:14:09 -450200.240506] SLOW spr round 2 (radius: 5) [02:18:02 -450182.550184] SLOW spr round 3 (radius: 5) [02:21:44 -450175.961208] SLOW spr round 4 (radius: 5) [02:25:21 -450175.878457] SLOW spr round 5 (radius: 10) [02:29:05 -450175.878450] SLOW spr round 6 (radius: 15) [02:35:34 -450175.878450] SLOW spr round 7 (radius: 20) [02:45:16 -450175.878450] SLOW spr round 8 (radius: 25) [02:58:04 -450175.878450] Model parameter optimization (eps = 0.100000) [02:58:15] [worker #0] ML tree search #3, logLikelihood: -450175.685077 [02:58:15 -1422035.410842] Initial branch length optimization [02:58:24 -1233990.628962] Model parameter optimization (eps = 10.000000) [02:59:28 -1232265.998711] AUTODETECT spr round 1 (radius: 5) [03:03:24 -883638.411014] AUTODETECT spr round 2 (radius: 10) [03:08:01 -616058.686807] AUTODETECT spr round 3 (radius: 15) [03:09:10] [worker #1] ML tree search #4, logLikelihood: -450177.692714 [03:12:42 -544530.187452] AUTODETECT spr round 4 (radius: 20) [03:18:37 -515264.832831] AUTODETECT spr round 5 (radius: 25) [03:25:35 -509089.192399] SPR radius for FAST iterations: 25 (autodetect) [03:25:35 -509089.192399] Model parameter optimization (eps = 3.000000) [03:25:42 -509088.850055] FAST spr round 1 (radius: 25) [03:30:48 -452374.666123] FAST spr round 2 (radius: 25) [03:34:30 -450607.696281] FAST spr round 3 (radius: 25) [03:37:46 -450494.779963] FAST spr round 4 (radius: 25) [03:40:30 -450485.412197] FAST spr round 5 (radius: 25) [03:43:04 -450485.412190] Model parameter optimization (eps = 1.000000) [03:43:35 -450311.525976] SLOW spr round 1 (radius: 5) [03:47:58 -450181.179434] SLOW spr round 2 (radius: 5) [03:51:52 -450173.422048] SLOW spr round 3 (radius: 5) [03:55:30 -450173.421989] SLOW spr round 4 (radius: 10) [03:59:15 -450173.421989] SLOW spr round 5 (radius: 15) [04:05:40 -450173.421989] SLOW spr round 6 (radius: 20) [04:15:36 -450173.421989] SLOW spr round 7 (radius: 25) [04:28:26 -450173.421989] Model parameter optimization (eps = 0.100000) [04:28:37] [worker #0] ML tree search #5, logLikelihood: -450172.532131 [04:28:37 -1438818.502760] Initial branch length optimization [04:28:45 -1245914.304291] Model parameter optimization (eps = 10.000000) [04:29:52 -1244204.366555] AUTODETECT spr round 1 (radius: 5) [04:33:41 -883277.287606] AUTODETECT spr round 2 (radius: 10) [04:37:59 -626259.599174] AUTODETECT spr round 3 (radius: 15) [04:40:17] [worker #1] ML tree search #6, logLikelihood: -450176.620720 [04:42:18 -526972.112402] AUTODETECT spr round 4 (radius: 20) [04:47:32 -506284.693224] AUTODETECT spr round 5 (radius: 25) [04:54:01 -503378.122277] SPR radius for FAST iterations: 25 (autodetect) [04:54:01 -503378.122277] Model parameter optimization (eps = 3.000000) [04:54:25 -503217.964618] FAST spr round 1 (radius: 25) [04:59:12 -452192.189605] FAST spr round 2 (radius: 25) [05:02:42 -450467.567602] FAST spr round 3 (radius: 25) [05:05:53 -450334.947602] FAST spr round 4 (radius: 25) [05:08:42 -450321.704269] FAST spr round 5 (radius: 25) [05:11:15 -450318.154352] FAST spr round 6 (radius: 25) [05:13:42 -450318.154347] Model parameter optimization (eps = 1.000000) [05:13:55 -450314.545727] SLOW spr round 1 (radius: 5) [05:18:05 -450178.289494] SLOW spr round 2 (radius: 5) [05:21:52 -450163.000515] SLOW spr round 3 (radius: 5) [05:25:26 -450163.000478] SLOW spr round 4 (radius: 10) [05:29:05 -450163.000477] SLOW spr round 5 (radius: 15) [05:35:19 -450163.000477] SLOW spr round 6 (radius: 20) [05:44:52 -450163.000477] SLOW spr round 7 (radius: 25) [05:57:19 -450163.000477] Model parameter optimization (eps = 0.100000) [05:57:31] [worker #0] ML tree search #7, logLikelihood: -450162.808655 [05:57:31 -1429848.562707] Initial branch length optimization [05:57:37 -1234373.558081] Model parameter optimization (eps = 10.000000) [05:58:32 -1232649.769338] AUTODETECT spr round 1 (radius: 5) [06:02:15 -888133.824318] AUTODETECT spr round 2 (radius: 10) [06:06:39 -662574.181087] AUTODETECT spr round 3 (radius: 15) [06:11:36 -554005.034343] AUTODETECT spr round 4 (radius: 20) [06:14:20] [worker #1] ML tree search #8, logLikelihood: -450179.977906 [06:17:20 -526366.877316] AUTODETECT spr round 5 (radius: 25) [06:23:42 -508584.626188] SPR radius for FAST iterations: 25 (autodetect) [06:23:42 -508584.626188] Model parameter optimization (eps = 3.000000) [06:24:06 -508389.601997] FAST spr round 1 (radius: 25) [06:29:04 -452936.741984] FAST spr round 2 (radius: 25) [06:32:50 -450437.731215] FAST spr round 3 (radius: 25) [06:35:52 -450347.125552] FAST spr round 4 (radius: 25) [06:38:23 -450345.724833] FAST spr round 5 (radius: 25) [06:40:50 -450345.724793] Model parameter optimization (eps = 1.000000) [06:41:02 -450344.577367] SLOW spr round 1 (radius: 5) [06:45:09 -450198.486136] SLOW spr round 2 (radius: 5) [06:48:54 -450167.221745] SLOW spr round 3 (radius: 5) [06:52:24 -450164.761562] SLOW spr round 4 (radius: 5) [06:55:49 -450164.761519] SLOW spr round 5 (radius: 10) [06:59:22 -450164.761519] SLOW spr round 6 (radius: 15) [07:05:33 -450164.761519] SLOW spr round 7 (radius: 20) [07:15:13 -450164.761519] SLOW spr round 8 (radius: 25) [07:27:51 -450164.761519] Model parameter optimization (eps = 0.100000) [07:28:02] [worker #0] ML tree search #9, logLikelihood: -450164.499774 [07:28:02 -1421806.674443] Initial branch length optimization [07:28:10 -1233234.531926] Model parameter optimization (eps = 10.000000) [07:29:08 -1231506.918670] AUTODETECT spr round 1 (radius: 5) [07:32:54 -886969.004363] AUTODETECT spr round 2 (radius: 10) [07:37:22 -649490.154088] AUTODETECT spr round 3 (radius: 15) [07:42:07 -563375.093589] AUTODETECT spr round 4 (radius: 20) [07:44:04] [worker #1] ML tree search #10, logLikelihood: -450179.154705 [07:47:44 -524070.019304] AUTODETECT spr round 5 (radius: 25) [07:53:55 -511528.912663] SPR radius for FAST iterations: 25 (autodetect) [07:53:55 -511528.912663] Model parameter optimization (eps = 3.000000) [07:54:02 -511528.702389] FAST spr round 1 (radius: 25) [07:59:09 -452791.818989] FAST spr round 2 (radius: 25) [08:02:49 -450621.160843] FAST spr round 3 (radius: 25) [08:06:03 -450479.828870] FAST spr round 4 (radius: 25) [08:08:47 -450447.296059] FAST spr round 5 (radius: 25) [08:11:13 -450447.296041] Model parameter optimization (eps = 1.000000) [08:11:20 -450447.184662] SLOW spr round 1 (radius: 5) [08:15:27 -450378.396934] SLOW spr round 2 (radius: 5) [08:19:02 -450376.786877] SLOW spr round 3 (radius: 5) [08:22:28 -450376.786863] SLOW spr round 4 (radius: 10) [08:26:00 -450376.786863] SLOW spr round 5 (radius: 15) [08:32:04 -450376.786863] SLOW spr round 6 (radius: 20) [08:41:18 -450376.786863] SLOW spr round 7 (radius: 25) [08:53:42 -450376.786863] Model parameter optimization (eps = 0.100000) [08:53:47] [worker #0] ML tree search #11, logLikelihood: -450376.784357 [08:53:47 -1430711.571552] Initial branch length optimization [08:53:55 -1239930.403011] Model parameter optimization (eps = 10.000000) [08:54:38 -1238270.700649] AUTODETECT spr round 1 (radius: 5) [08:58:27 -896227.504587] AUTODETECT spr round 2 (radius: 10) [09:03:12 -648854.538951] AUTODETECT spr round 3 (radius: 15) [09:07:49 -550183.719616] AUTODETECT spr round 4 (radius: 20) [09:13:01] [worker #1] ML tree search #12, logLikelihood: -450165.053540 [09:13:46 -529333.801916] AUTODETECT spr round 5 (radius: 25) [09:21:27 -512683.204107] SPR radius for FAST iterations: 25 (autodetect) [09:21:27 -512683.204107] Model parameter optimization (eps = 3.000000) [09:21:34 -512682.627768] FAST spr round 1 (radius: 25) [09:26:56 -452841.267477] FAST spr round 2 (radius: 25) [09:30:35 -450617.125585] FAST spr round 3 (radius: 25) [09:33:39 -450504.270145] FAST spr round 4 (radius: 25) [09:36:10 -450431.896042] FAST spr round 5 (radius: 25) [09:38:35 -450431.896004] Model parameter optimization (eps = 1.000000) [09:38:56 -450252.708947] SLOW spr round 1 (radius: 5) [09:43:10 -450180.720100] SLOW spr round 2 (radius: 5) [09:47:04 -450171.189301] SLOW spr round 3 (radius: 5) [09:50:36 -450171.189256] SLOW spr round 4 (radius: 10) [09:54:15 -450171.189256] SLOW spr round 5 (radius: 15) [10:00:37 -450171.189256] SLOW spr round 6 (radius: 20) [10:10:37 -450171.189256] SLOW spr round 7 (radius: 25) [10:23:14 -450171.189256] Model parameter optimization (eps = 0.100000) [10:23:21] [worker #0] ML tree search #13, logLikelihood: -450171.174365 [10:23:21 -1434807.985723] Initial branch length optimization [10:23:28 -1240287.692827] Model parameter optimization (eps = 10.000000) [10:24:26 -1238496.831399] AUTODETECT spr round 1 (radius: 5) [10:28:14 -889124.288463] AUTODETECT spr round 2 (radius: 10) [10:32:31 -665823.668911] AUTODETECT spr round 3 (radius: 15) [10:37:28 -561042.515586] AUTODETECT spr round 4 (radius: 20) [10:38:48] [worker #1] ML tree search #14, logLikelihood: -450186.277469 [10:43:34 -526572.579170] AUTODETECT spr round 5 (radius: 25) [10:50:47 -517568.163272] SPR radius for FAST iterations: 25 (autodetect) [10:50:48 -517568.163272] Model parameter optimization (eps = 3.000000) [10:50:55 -517568.045786] FAST spr round 1 (radius: 25) [10:56:04 -452472.359664] FAST spr round 2 (radius: 25) [10:59:40 -450608.759470] FAST spr round 3 (radius: 25) [11:02:46 -450491.369008] FAST spr round 4 (radius: 25) [11:05:18 -450486.881090] FAST spr round 5 (radius: 25) [11:07:45 -450486.881036] Model parameter optimization (eps = 1.000000) [11:07:52 -450486.578968] SLOW spr round 1 (radius: 5) [11:12:03 -450401.137993] SLOW spr round 2 (radius: 5) [11:15:52 -450382.106363] SLOW spr round 3 (radius: 5) [11:19:22 -450378.808036] SLOW spr round 4 (radius: 5) [11:22:46 -450378.808026] SLOW spr round 5 (radius: 10) [11:26:16 -450378.808026] SLOW spr round 6 (radius: 15) [11:32:17 -450378.808026] SLOW spr round 7 (radius: 20) [11:41:34 -450378.808026] SLOW spr round 8 (radius: 25) [11:53:44 -450378.808026] Model parameter optimization (eps = 0.100000) [11:53:49] [worker #0] ML tree search #15, logLikelihood: -450378.804092 [11:53:49 -1432149.886711] Initial branch length optimization [11:53:56 -1241282.721306] Model parameter optimization (eps = 10.000000) [11:54:42 -1239454.035841] AUTODETECT spr round 1 (radius: 5) [11:58:26 -880700.891373] AUTODETECT spr round 2 (radius: 10) [12:02:46 -653598.807704] AUTODETECT spr round 3 (radius: 15) [12:07:26 -557362.202283] AUTODETECT spr round 4 (radius: 20) [12:08:09] [worker #1] ML tree search #16, logLikelihood: -450165.359379 [12:12:49 -520056.680867] AUTODETECT spr round 5 (radius: 25) [12:19:01 -512239.237966] SPR radius for FAST iterations: 25 (autodetect) [12:19:01 -512239.237966] Model parameter optimization (eps = 3.000000) [12:19:28 -512101.656459] FAST spr round 1 (radius: 25) [12:24:40 -452958.006397] FAST spr round 2 (radius: 25) [12:28:22 -450488.705710] FAST spr round 3 (radius: 25) [12:31:28 -450299.183930] FAST spr round 4 (radius: 25) [12:34:07 -450287.566128] FAST spr round 5 (radius: 25) [12:36:37 -450287.087023] FAST spr round 6 (radius: 25) [12:39:04 -450285.202570] FAST spr round 7 (radius: 25) [12:41:27 -450285.202570] Model parameter optimization (eps = 1.000000) [12:41:43 -450280.637475] SLOW spr round 1 (radius: 5) [12:45:49 -450176.469849] SLOW spr round 2 (radius: 5) [12:49:26 -450173.677162] SLOW spr round 3 (radius: 5) [12:53:00 -450173.677125] SLOW spr round 4 (radius: 10) [12:56:41 -450173.677125] SLOW spr round 5 (radius: 15) [13:02:58 -450173.677125] SLOW spr round 6 (radius: 20) [13:12:36 -450173.677125] SLOW spr round 7 (radius: 25) [13:25:05 -450173.677125] Model parameter optimization (eps = 0.100000) [13:25:12] [worker #0] ML tree search #17, logLikelihood: -450173.669225 [13:25:12 -1421835.671137] Initial branch length optimization [13:25:22 -1231123.387367] Model parameter optimization (eps = 10.000000) [13:26:18 -1229460.001451] AUTODETECT spr round 1 (radius: 5) [13:30:08 -898400.696323] AUTODETECT spr round 2 (radius: 10) [13:34:24 -659620.771304] AUTODETECT spr round 3 (radius: 15) [13:36:03] [worker #1] ML tree search #18, logLikelihood: -450162.315080 [13:39:08 -547019.961434] AUTODETECT spr round 4 (radius: 20) [13:44:40 -506197.518060] AUTODETECT spr round 5 (radius: 25) [13:50:48 -502788.315678] SPR radius for FAST iterations: 25 (autodetect) [13:50:48 -502788.315678] Model parameter optimization (eps = 3.000000) [13:51:14 -502572.044119] FAST spr round 1 (radius: 25) [13:55:56 -452196.171733] FAST spr round 2 (radius: 25) [13:59:26 -450465.784095] FAST spr round 3 (radius: 25) [14:02:23 -450306.291650] FAST spr round 4 (radius: 25) [14:04:49 -450300.947364] FAST spr round 5 (radius: 25) [14:07:07 -450300.947197] Model parameter optimization (eps = 1.000000) [14:07:23 -450293.803204] SLOW spr round 1 (radius: 5) [14:11:16 -450170.383568] SLOW spr round 2 (radius: 5) [14:14:47 -450163.518413] SLOW spr round 3 (radius: 5) [14:18:11 -450160.860655] SLOW spr round 4 (radius: 5) [14:21:30 -450160.860642] SLOW spr round 5 (radius: 10) [14:24:55 -450160.860642] SLOW spr round 6 (radius: 15) [14:30:47 -450160.860642] SLOW spr round 7 (radius: 20) [14:39:56 -450160.860642] SLOW spr round 8 (radius: 25) [14:51:43 -450160.860642] Model parameter optimization (eps = 0.100000) [14:51:55] [worker #0] ML tree search #19, logLikelihood: -450160.226103 [15:02:29] [worker #1] ML tree search #20, logLikelihood: -450174.581135 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.213991,0.298832) (0.290656,0.420088) (0.258004,1.011866) (0.237348,2.329426) 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: -450160.226103 AIC score: 904330.452206 / AICc score: 8948390.452206 / BIC score: 914105.292541 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=968). This might lead to overfitting and compromise tree inference results! Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5JTZ9/3_mltree/Q5JTZ9.raxml.log Analysis started: 07-Jul-2021 02:17:26 / finished: 07-Jul-2021 17:19:56 Elapsed time: 54149.779 seconds Consumed energy: 5014.982 Wh (= 25 km in an electric car, or 125 km with an e-scooter!)