RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab. Developed by: Alexey M. Kozlov and Alexandros Stamatakis. Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth. Latest version: https://github.com/amkozlov/raxml-ng Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml System: Intel(R) Xeon(R) CPU E5-2690 v4 @ 2.60GHz, 28 cores, 251 GB RAM RAxML-NG was called at 07-Jul-2021 20:40:48 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/2_msa/Q9NSE4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4 --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/Q9NSE4/2_msa/Q9NSE4_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 849 sites WARNING: Sequences tr_F1P399_F1P399_CHICK_9031 and sp_Q5ZKA2_SYIM_CHICK_9031 are exactly identical! WARNING: Sequences tr_B8NW47_B8NW47_ASPFN_332952 and tr_Q2TXA8_Q2TXA8_ASPOR_510516 are exactly identical! WARNING: Sequences tr_A0A179V2H5_A0A179V2H5_BLAGS_559298 and tr_C5GRX6_C5GRX6_AJEDR_559297 are exactly identical! WARNING: Sequences tr_C6HH11_C6HH11_AJECH_544712 and tr_F0US03_F0US03_AJEC8_544711 are exactly identical! WARNING: Sequences tr_A0A0E0GDK8_A0A0E0GDK8_ORYNI_4536 and tr_A0A0E0CS75_A0A0E0CS75_9ORYZ_40149 are exactly identical! WARNING: Sequences tr_A0A0E0GDK8_A0A0E0GDK8_ORYNI_4536 and tr_A0A0E0NLP1_A0A0E0NLP1_ORYRU_4529 are exactly identical! WARNING: Sequences tr_G7XZW4_G7XZW4_ASPKW_1033177 and tr_A0A146FFT6_A0A146FFT6_9EURO_1069201 are exactly identical! WARNING: Sequences tr_B8AJH5_B8AJH5_ORYSI_39946 and tr_A0A0D9YZ62_A0A0D9YZ62_9ORYZ_40148 are exactly identical! WARNING: Sequences tr_B8AJH5_B8AJH5_ORYSI_39946 and tr_Q6ZGC2_Q6ZGC2_ORYSJ_39947 are exactly identical! WARNING: Sequences tr_F9WZA2_F9WZA2_ZYMTI_336722 and tr_A0A1X7RFV3_A0A1X7RFV3_ZYMTR_1276538 are exactly identical! WARNING: Sequences tr_F2STS1_F2STS1_TRIRC_559305 and tr_A0A178EUZ5_A0A178EUZ5_TRIRU_5551 are exactly identical! WARNING: Sequences tr_A0A015L5W9_A0A015L5W9_9GLOM_1432141 and tr_A0A2H5SVD0_A0A2H5SVD0_RHIID_747089 are exactly identical! WARNING: Sequences tr_A0A0F8UI89_A0A0F8UI89_9EURO_308745 and tr_A0A2T5M0P5_A0A2T5M0P5_9EURO_1392256 are exactly identical! WARNING: Sequences tr_A0A226MSF0_A0A226MSF0_CALSU_9009 and tr_A0A226P2Z3_A0A226P2Z3_COLVI_9014 are exactly identical! WARNING: Sequences tr_A0A2D0RLX4_A0A2D0RLX4_ICTPU_7998 and tr_A0A2D0RMH1_A0A2D0RMH1_ICTPU_7998 are exactly identical! WARNING: Duplicate sequences found: 15 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/Q9NSE4/3_mltree/Q9NSE4.raxml.reduced.phy Alignment comprises 1 partitions and 849 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 849 / 849 Gaps: 11.56 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.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 / 213 / 17040 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -1348216.257552] Initial branch length optimization [00:00:13 -1167001.216991] Model parameter optimization (eps = 10.000000) [00:02:09 -1164026.316493] AUTODETECT spr round 1 (radius: 5) [00:09:49 -887890.078553] AUTODETECT spr round 2 (radius: 10) [00:17:32 -669873.177469] AUTODETECT spr round 3 (radius: 15) [00:26:05 -596050.991678] AUTODETECT spr round 4 (radius: 20) [00:36:31 -570749.518232] AUTODETECT spr round 5 (radius: 25) [00:50:20 -567467.514381] SPR radius for FAST iterations: 25 (autodetect) [00:50:20 -567467.514381] Model parameter optimization (eps = 3.000000) [00:51:27 -567396.455717] FAST spr round 1 (radius: 25) [01:04:17 -513516.463024] FAST spr round 2 (radius: 25) [01:11:56 -511976.137786] FAST spr round 3 (radius: 25) [01:19:00 -511655.068705] FAST spr round 4 (radius: 25) [01:25:02 -511635.936712] FAST spr round 5 (radius: 25) [01:30:26 -511635.866868] Model parameter optimization (eps = 1.000000) [01:31:06 -511626.962398] SLOW spr round 1 (radius: 5) [01:39:05 -511495.638161] SLOW spr round 2 (radius: 5) [01:46:30 -511473.175009] SLOW spr round 3 (radius: 5) [01:53:32 -511471.667320] SLOW spr round 4 (radius: 5) [02:00:25 -511471.666814] SLOW spr round 5 (radius: 10) [02:07:51 -511470.039480] SLOW spr round 6 (radius: 5) [02:16:44 -511470.039448] SLOW spr round 7 (radius: 10) [02:24:56 -511470.039433] SLOW spr round 8 (radius: 15) [02:37:20 -511470.039426] SLOW spr round 9 (radius: 20) [02:58:31 -511470.039422] SLOW spr round 10 (radius: 25) [03:27:00 -511470.039419] Model parameter optimization (eps = 0.100000) [03:27:43] [worker #0] ML tree search #1, logLikelihood: -511469.227275 [03:27:43 -1346297.848823] Initial branch length optimization [03:27:57 -1164499.280498] Model parameter optimization (eps = 10.000000) [03:29:36 -1161651.870335] AUTODETECT spr round 1 (radius: 5) [03:36:37 -911231.779878] AUTODETECT spr round 2 (radius: 10) [03:44:05 -683169.472107] AUTODETECT spr round 3 (radius: 15) [03:52:43 -586984.247988] AUTODETECT spr round 4 (radius: 20) [04:01:28 -566544.003845] AUTODETECT spr round 5 (radius: 25) [04:09:07 -565062.952771] SPR radius for FAST iterations: 25 (autodetect) [04:09:07 -565062.952771] Model parameter optimization (eps = 3.000000) [04:09:38 -564962.514736] FAST spr round 1 (radius: 25) [04:16:06 -513303.043398] FAST spr round 2 (radius: 25) [04:20:53 -511700.339640] FAST spr round 3 (radius: 25) [04:24:49 -511623.519379] FAST spr round 4 (radius: 25) [04:28:13 -511614.037104] FAST spr round 5 (radius: 25) [04:31:15 -511606.149623] FAST spr round 6 (radius: 25) [04:34:16 -511605.888658] FAST spr round 7 (radius: 25) [04:37:16 -511605.887324] Model parameter optimization (eps = 1.000000) [04:37:38 -511600.868711] SLOW spr round 1 (radius: 5) [04:44:15 -511487.167898] SLOW spr round 2 (radius: 5) [04:51:15 -511468.010676] SLOW spr round 3 (radius: 5) [04:58:01 -511467.999328] SLOW spr round 4 (radius: 10) [05:05:23 -511467.998097] SLOW spr round 5 (radius: 15) [05:16:19] [worker #1] ML tree search #2, logLikelihood: -511466.566150 [05:19:22 -511467.996865] SLOW spr round 6 (radius: 20) [05:40:34 -511467.661883] SLOW spr round 7 (radius: 5) [05:49:56 -511467.649757] SLOW spr round 8 (radius: 10) [05:58:41 -511467.649197] SLOW spr round 9 (radius: 15) [06:11:11 -511467.648829] SLOW spr round 10 (radius: 20) [06:31:58 -511467.648463] SLOW spr round 11 (radius: 25) [06:57:35 -511467.648098] Model parameter optimization (eps = 0.100000) [06:57:53] [worker #0] ML tree search #3, logLikelihood: -511467.616725 [06:57:54 -1350015.897198] Initial branch length optimization [06:58:05 -1167365.680043] Model parameter optimization (eps = 10.000000) [07:00:49 -1164617.441379] AUTODETECT spr round 1 (radius: 5) [07:08:13 -901383.021697] AUTODETECT spr round 2 (radius: 10) [07:16:18 -675101.260619] AUTODETECT spr round 3 (radius: 15) [07:25:07 -585006.806049] AUTODETECT spr round 4 (radius: 20) [07:36:34 -564406.867370] AUTODETECT spr round 5 (radius: 25) [07:49:11 -561222.064459] SPR radius for FAST iterations: 25 (autodetect) [07:49:11 -561222.064459] Model parameter optimization (eps = 3.000000) [07:50:00 -561160.101641] FAST spr round 1 (radius: 25) [08:02:00 -513575.666683] FAST spr round 2 (radius: 25) [08:10:46 -511787.091641] FAST spr round 3 (radius: 25) [08:17:38 -511640.905433] FAST spr round 4 (radius: 25) [08:23:26 -511625.350147] FAST spr round 5 (radius: 25) [08:28:51 -511622.491512] FAST spr round 6 (radius: 25) [08:34:05 -511622.479972] Model parameter optimization (eps = 1.000000) [08:34:34 -511621.200993] SLOW spr round 1 (radius: 5) [08:42:22 -511484.045135] SLOW spr round 2 (radius: 5) [08:49:25 -511476.768744] SLOW spr round 3 (radius: 5) [08:56:19 -511476.756963] SLOW spr round 4 (radius: 10) [09:04:06 -511473.810048] SLOW spr round 5 (radius: 5) [09:13:38 -511473.797743] SLOW spr round 6 (radius: 10) [09:18:29 -511473.796506] SLOW spr round 7 (radius: 15) [09:20:49] [worker #1] ML tree search #4, logLikelihood: -511469.538039 [09:25:47 -511473.795268] SLOW spr round 8 (radius: 20) [09:38:20 -511473.794029] SLOW spr round 9 (radius: 25) [09:54:25 -511473.792789] Model parameter optimization (eps = 0.100000) [09:54:37] [worker #0] ML tree search #5, logLikelihood: -511473.459765 [09:54:37 -1341726.874412] Initial branch length optimization [09:54:44 -1161973.305447] Model parameter optimization (eps = 10.000000) [09:55:28 -1159262.422366] AUTODETECT spr round 1 (radius: 5) [09:59:14 -891231.645332] AUTODETECT spr round 2 (radius: 10) [10:03:45 -670472.268910] AUTODETECT spr round 3 (radius: 15) [10:08:53 -587897.635763] AUTODETECT spr round 4 (radius: 20) [10:14:47 -566673.590122] AUTODETECT spr round 5 (radius: 25) [10:21:40 -562133.895005] SPR radius for FAST iterations: 25 (autodetect) [10:21:40 -562133.895005] Model parameter optimization (eps = 3.000000) [10:22:08 -562040.775018] FAST spr round 1 (radius: 25) [10:31:21 -513643.716771] FAST spr round 2 (radius: 25) [10:36:00 -511754.067850] FAST spr round 3 (radius: 25) [10:40:01 -511599.094716] FAST spr round 4 (radius: 25) [10:43:23 -511587.814757] FAST spr round 5 (radius: 25) [10:46:36 -511585.869330] FAST spr round 6 (radius: 25) [10:52:03 -511585.858098] Model parameter optimization (eps = 1.000000) [10:52:41 -511582.781649] SLOW spr round 1 (radius: 5) [11:00:43 -511459.992774] SLOW spr round 2 (radius: 5) [11:08:07 -511453.723777] SLOW spr round 3 (radius: 5) [11:15:17 -511453.712116] SLOW spr round 4 (radius: 10) [11:22:52 -511450.176739] SLOW spr round 5 (radius: 5) [11:32:02 -511450.165035] SLOW spr round 6 (radius: 10) [11:40:44 -511449.728709] SLOW spr round 7 (radius: 5) [11:49:35 -511449.727459] SLOW spr round 8 (radius: 10) [11:57:58 -511449.726221] SLOW spr round 9 (radius: 15) [12:11:30 -511449.724982] SLOW spr round 10 (radius: 20) [12:35:00 -511449.723741] SLOW spr round 11 (radius: 25) [12:57:24] [worker #1] ML tree search #6, logLikelihood: -511453.018548 [13:05:25 -511449.722499] Model parameter optimization (eps = 0.100000) [13:05:46] [worker #0] ML tree search #7, logLikelihood: -511449.590124 [13:05:46 -1350008.138335] Initial branch length optimization [13:06:02 -1167503.266678] Model parameter optimization (eps = 10.000000) [13:07:42 -1164631.807047] AUTODETECT spr round 1 (radius: 5) [13:15:18 -912401.494174] AUTODETECT spr round 2 (radius: 10) [13:23:42 -690542.690269] AUTODETECT spr round 3 (radius: 15) [13:33:35 -588030.628686] AUTODETECT spr round 4 (radius: 20) [13:45:06 -569886.835562] AUTODETECT spr round 5 (radius: 25) [13:57:05 -565580.054817] SPR radius for FAST iterations: 25 (autodetect) [13:57:05 -565580.054817] Model parameter optimization (eps = 3.000000) [13:58:03 -565508.102920] FAST spr round 1 (radius: 25) [14:10:36 -513532.934881] FAST spr round 2 (radius: 25) [14:19:57 -511771.662621] FAST spr round 3 (radius: 25) [14:27:55 -511619.083732] FAST spr round 4 (radius: 25) [14:34:17 -511595.540008] FAST spr round 5 (radius: 25) [14:40:05 -511595.539148] Model parameter optimization (eps = 1.000000) [14:40:47 -511589.609879] SLOW spr round 1 (radius: 5) [14:49:11 -511480.574468] SLOW spr round 2 (radius: 5) [14:56:25 -511466.537407] SLOW spr round 3 (radius: 5) [15:00:26 -511460.863140] SLOW spr round 4 (radius: 5) [15:04:25 -511459.956446] SLOW spr round 5 (radius: 5) [15:08:19 -511459.955916] SLOW spr round 6 (radius: 10) [15:12:34 -511459.955553] SLOW spr round 7 (radius: 15) [15:21:02 -511459.749946] SLOW spr round 8 (radius: 5) [15:26:27 -511459.744468] SLOW spr round 9 (radius: 10) [15:31:31 -511459.743675] SLOW spr round 10 (radius: 15) [15:39:17 -511459.743301] SLOW spr round 11 (radius: 20) [15:53:24 -511459.305246] SLOW spr round 12 (radius: 5) [15:58:54 -511459.304755] SLOW spr round 13 (radius: 10) [16:04:05 -511459.304438] SLOW spr round 14 (radius: 15) [16:11:47 -511459.304133] SLOW spr round 15 (radius: 20) [16:22:47] [worker #1] ML tree search #8, logLikelihood: -511447.161312 [16:25:51 -511459.303831] SLOW spr round 16 (radius: 25) [16:43:20 -511459.303531] Model parameter optimization (eps = 0.100000) [16:43:39] [worker #0] ML tree search #9, logLikelihood: -511459.092195 [16:43:39 -1350734.464045] Initial branch length optimization [16:43:47 -1169001.087882] Model parameter optimization (eps = 10.000000) [16:44:48 -1166067.775033] AUTODETECT spr round 1 (radius: 5) [16:48:35 -923225.792365] AUTODETECT spr round 2 (radius: 10) [16:52:50 -741671.216263] AUTODETECT spr round 3 (radius: 15) [16:57:51 -652996.827308] AUTODETECT spr round 4 (radius: 20) [17:03:55 -602525.775957] AUTODETECT spr round 5 (radius: 25) [17:10:17 -585264.749047] SPR radius for FAST iterations: 25 (autodetect) [17:10:17 -585264.749047] Model parameter optimization (eps = 3.000000) [17:10:44 -585217.038721] FAST spr round 1 (radius: 25) [17:17:34 -514229.855750] FAST spr round 2 (radius: 25) [17:22:26 -511736.085396] FAST spr round 3 (radius: 25) [17:26:11 -511661.224614] FAST spr round 4 (radius: 25) [17:29:17 -511656.035749] FAST spr round 5 (radius: 25) [17:32:13 -511655.496676] FAST spr round 6 (radius: 25) [17:35:03 -511655.485025] Model parameter optimization (eps = 1.000000) [17:35:27 -511645.347299] SLOW spr round 1 (radius: 5) [17:39:48 -511508.567005] SLOW spr round 2 (radius: 5) [17:44:02 -511494.617115] SLOW spr round 3 (radius: 5) [17:47:59 -511494.594084] SLOW spr round 4 (radius: 10) [17:52:17 -511490.561817] SLOW spr round 5 (radius: 5) [17:57:27 -511490.549339] SLOW spr round 6 (radius: 10) [18:02:22 -511490.053928] SLOW spr round 7 (radius: 5) [18:07:24 -511490.051809] SLOW spr round 8 (radius: 10) [18:12:15 -511490.050325] SLOW spr round 9 (radius: 15) [18:20:39 -511489.916349] SLOW spr round 10 (radius: 5) [18:26:06 -511489.828099] SLOW spr round 11 (radius: 10) [18:31:18 -511489.826770] SLOW spr round 12 (radius: 15) [18:39:11 -511489.826272] SLOW spr round 13 (radius: 20) [18:48:33] [worker #1] ML tree search #10, logLikelihood: -511458.991647 [18:53:47 -511489.825906] SLOW spr round 14 (radius: 25) [19:11:51 -511489.825571] Model parameter optimization (eps = 0.100000) [19:12:03] [worker #0] ML tree search #11, logLikelihood: -511489.430673 [19:12:03 -1347760.427582] Initial branch length optimization [19:12:16 -1167707.575531] Model parameter optimization (eps = 10.000000) [19:13:01 -1164946.104451] AUTODETECT spr round 1 (radius: 5) [19:16:46 -898734.130695] AUTODETECT spr round 2 (radius: 10) [19:21:01 -694235.918334] AUTODETECT spr round 3 (radius: 15) [19:25:35 -594612.114095] AUTODETECT spr round 4 (radius: 20) [19:31:11 -576724.798811] AUTODETECT spr round 5 (radius: 25) [19:38:13 -572419.968507] SPR radius for FAST iterations: 25 (autodetect) [19:38:13 -572419.968507] Model parameter optimization (eps = 3.000000) [19:38:26 -572416.625237] FAST spr round 1 (radius: 25) [19:45:20 -514471.424636] FAST spr round 2 (radius: 25) [19:50:08 -511844.643945] FAST spr round 3 (radius: 25) [19:53:55 -511664.780311] FAST spr round 4 (radius: 25) [19:56:59 -511658.860305] FAST spr round 5 (radius: 25) [19:59:49 -511658.295213] FAST spr round 6 (radius: 25) [20:02:34 -511658.283827] Model parameter optimization (eps = 1.000000) [20:02:57 -511585.144767] SLOW spr round 1 (radius: 5) [20:07:18 -511487.375398] SLOW spr round 2 (radius: 5) [20:11:21 -511482.487378] SLOW spr round 3 (radius: 5) [20:15:20 -511480.367934] SLOW spr round 4 (radius: 5) [20:19:16 -511480.356309] SLOW spr round 5 (radius: 10) [20:23:28 -511480.355080] SLOW spr round 6 (radius: 15) [20:31:49 -511480.170722] SLOW spr round 7 (radius: 5) [20:37:14 -511480.155095] SLOW spr round 8 (radius: 10) [20:42:16 -511480.153850] SLOW spr round 9 (radius: 15) [20:45:42] [worker #1] ML tree search #12, logLikelihood: -511469.946929 [20:49:56 -511480.152605] SLOW spr round 10 (radius: 20) [21:03:55 -511480.151700] SLOW spr round 11 (radius: 25) [21:21:28 -511480.151696] Model parameter optimization (eps = 0.100000) [21:21:40] [worker #0] ML tree search #13, logLikelihood: -511479.844749 [21:21:40 -1346863.761590] Initial branch length optimization [21:21:49 -1163470.760922] Model parameter optimization (eps = 10.000000) [21:22:45 -1160677.876925] AUTODETECT spr round 1 (radius: 5) [21:28:40 -895747.452282] AUTODETECT spr round 2 (radius: 10) [21:37:24 -690000.548468] AUTODETECT spr round 3 (radius: 15) [21:47:05 -611679.978849] AUTODETECT spr round 4 (radius: 20) [21:59:27 -568877.706289] AUTODETECT spr round 5 (radius: 25) [22:12:43 -566763.332079] SPR radius for FAST iterations: 25 (autodetect) [22:12:43 -566763.332079] Model parameter optimization (eps = 3.000000) [22:13:09 -566758.896778] FAST spr round 1 (radius: 25) [22:26:32 -513491.118153] FAST spr round 2 (radius: 25) [22:36:04 -511903.997562] FAST spr round 3 (radius: 25) [22:43:34 -511775.455450] FAST spr round 4 (radius: 25) [22:49:51 -511758.140381] FAST spr round 5 (radius: 25) [22:55:48 -511756.201660] FAST spr round 6 (radius: 25) [23:01:32 -511756.190368] Model parameter optimization (eps = 1.000000) [23:02:19 -511627.878959] SLOW spr round 1 (radius: 5) [23:10:56 -511489.342774] SLOW spr round 2 (radius: 5) [23:18:46 -511480.285654] SLOW spr round 3 (radius: 5) [23:19:17] [worker #1] ML tree search #14, logLikelihood: -511502.942173 [23:26:34 -511466.171104] SLOW spr round 4 (radius: 5) [23:34:10 -511466.159154] SLOW spr round 5 (radius: 10) [23:42:27 -511460.180942] SLOW spr round 6 (radius: 5) [23:52:35 -511450.618903] SLOW spr round 7 (radius: 5) [24:01:08 -511449.573598] SLOW spr round 8 (radius: 5) [24:09:04 -511449.572345] SLOW spr round 9 (radius: 10) [24:17:23 -511449.571673] SLOW spr round 10 (radius: 15) [24:32:51 -511449.571672] SLOW spr round 11 (radius: 20) [24:57:40 -511448.588118] SLOW spr round 12 (radius: 5) [25:08:07 -511448.581348] SLOW spr round 13 (radius: 10) [25:18:10 -511448.580305] SLOW spr round 14 (radius: 15) [25:32:39 -511448.579871] SLOW spr round 15 (radius: 20) [25:40:39] [worker #1] ML tree search #16, logLikelihood: -511455.107319 [25:58:11 -511448.579486] SLOW spr round 16 (radius: 25) [26:30:23 -511448.579106] Model parameter optimization (eps = 0.100000) [26:30:39] [worker #0] ML tree search #15, logLikelihood: -511448.551950 [26:30:39 -1347314.770222] Initial branch length optimization [26:30:51 -1164780.188550] Model parameter optimization (eps = 10.000000) [26:32:43 -1161935.546288] AUTODETECT spr round 1 (radius: 5) [26:40:40 -891809.608551] AUTODETECT spr round 2 (radius: 10) [26:49:33 -673147.177133] AUTODETECT spr round 3 (radius: 15) [26:58:47 -605564.889695] AUTODETECT spr round 4 (radius: 20) [27:09:32 -569261.365950] AUTODETECT spr round 5 (radius: 25) [27:23:22 -558813.563277] SPR radius for FAST iterations: 25 (autodetect) [27:23:22 -558813.563277] Model parameter optimization (eps = 3.000000) [27:24:15 -558724.142684] FAST spr round 1 (radius: 25) [27:36:56 -513289.544330] FAST spr round 2 (radius: 25) [27:45:56 -511709.909848] FAST spr round 3 (radius: 25) [27:53:25 -511614.003381] FAST spr round 4 (radius: 25) [27:59:24 -511613.995823] Model parameter optimization (eps = 1.000000) [28:00:05 -511609.114193] SLOW spr round 1 (radius: 5) [28:08:39 -511470.527951] SLOW spr round 2 (radius: 5) [28:17:10 -511454.382153] SLOW spr round 3 (radius: 5) [28:25:07 -511454.369991] SLOW spr round 4 (radius: 10) [28:33:30 -511453.963146] SLOW spr round 5 (radius: 5) [28:43:23 -511453.951379] SLOW spr round 6 (radius: 10) [28:52:43 -511453.945234] SLOW spr round 7 (radius: 15) [28:55:19] [worker #1] ML tree search #18, logLikelihood: -511465.342396 [29:07:08 -511453.943609] SLOW spr round 8 (radius: 20) [29:31:24 -511453.941986] SLOW spr round 9 (radius: 25) [30:02:39 -511453.940363] Model parameter optimization (eps = 0.100000) [30:03:04] [worker #0] ML tree search #17, logLikelihood: -511453.771073 [30:03:04 -1345030.765797] Initial branch length optimization [30:03:16 -1166514.983584] Model parameter optimization (eps = 10.000000) [30:04:20 -1163534.200459] AUTODETECT spr round 1 (radius: 5) [30:08:14 -903691.728543] AUTODETECT spr round 2 (radius: 10) [30:12:25 -734301.465900] AUTODETECT spr round 3 (radius: 15) [30:17:00 -628803.217276] AUTODETECT spr round 4 (radius: 20) [30:22:34 -591108.326116] AUTODETECT spr round 5 (radius: 25) [30:29:06 -575274.680138] SPR radius for FAST iterations: 25 (autodetect) [30:29:06 -575274.680138] Model parameter optimization (eps = 3.000000) [30:29:46 -575167.958760] FAST spr round 1 (radius: 25) [30:36:31 -513882.666756] FAST spr round 2 (radius: 25) [30:41:12 -511848.569881] FAST spr round 3 (radius: 25) [30:43:37] [worker #1] ML tree search #20, logLikelihood: -511468.383735 [30:45:02 -511703.517326] FAST spr round 4 (radius: 25) [30:48:08 -511683.979822] FAST spr round 5 (radius: 25) [30:51:04 -511675.319491] FAST spr round 6 (radius: 25) [30:53:55 -511669.472811] FAST spr round 7 (radius: 25) [30:56:41 -511666.255598] FAST spr round 8 (radius: 25) [30:59:23 -511666.255328] Model parameter optimization (eps = 1.000000) [30:59:46 -511657.418474] SLOW spr round 1 (radius: 5) [31:04:05 -511526.628125] SLOW spr round 2 (radius: 5) [31:08:08 -511518.380653] SLOW spr round 3 (radius: 5) [31:12:07 -511511.588397] SLOW spr round 4 (radius: 5) [31:16:04 -511509.347218] SLOW spr round 5 (radius: 5) [31:19:58 -511509.334924] SLOW spr round 6 (radius: 10) [31:24:03 -511508.962899] SLOW spr round 7 (radius: 5) [31:29:10 -511508.497230] SLOW spr round 8 (radius: 5) [31:33:37 -511504.683477] SLOW spr round 9 (radius: 5) [31:37:42 -511504.681924] SLOW spr round 10 (radius: 10) [31:41:52 -511504.680371] SLOW spr round 11 (radius: 15) [31:49:59 -511503.990042] SLOW spr round 12 (radius: 5) [31:55:21 -511503.872817] SLOW spr round 13 (radius: 5) [31:59:53 -511503.860305] SLOW spr round 14 (radius: 10) [32:04:14 -511503.859578] SLOW spr round 15 (radius: 15) [32:12:04 -511503.858957] SLOW spr round 16 (radius: 20) [32:25:16 -511503.858416] SLOW spr round 17 (radius: 25) [32:41:51 -511503.857936] Model parameter optimization (eps = 0.100000) [32:42:06] [worker #0] ML tree search #19, logLikelihood: -511503.468106 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.165100,0.295798) (0.283675,0.464119) (0.299958,0.902582) (0.251267,2.184004) 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: -511447.161312 AIC score: 1026904.322623 / AICc score: 9070964.322623 / BIC score: 1036416.161292 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=849). This might lead to overfitting and compromise tree inference results! WARNING: Best ML tree contains 22 near-zero branches! Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.raxml.bestTreeCollapsed Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NSE4/3_mltree/Q9NSE4.raxml.log Analysis started: 07-Jul-2021 20:40:48 / finished: 09-Jul-2021 05:22:55 Elapsed time: 117726.698 seconds Consumed energy: 8695.500 Wh (= 43 km in an electric car, or 217 km with an e-scooter!)