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 01-Jul-2021 17:09:21 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/2_msa/Q68DY1_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/3_mltree/Q68DY1 --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/Q68DY1/2_msa/Q68DY1_trimmed_msa.fasta [00:00:00] Loaded alignment with 1001 taxa and 655 sites WARNING: Sequences tr_A0A2I2YQQ8_A0A2I2YQQ8_GORGO_9595 and sp_Q9Y2G7_ZFP30_HUMAN_9606 are exactly identical! WARNING: Sequences tr_A0A2I3T1I2_A0A2I3T1I2_PANTR_9598 and tr_A0A2R9C8X5_A0A2R9C8X5_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A2J8QIH1_A0A2J8QIH1_PANTR_9598 and tr_A0A2R9AKC8_A0A2R9AKC8_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A1D5R403_A0A1D5R403_MACMU_9544 and tr_A0A2K6CQR3_A0A2K6CQR3_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A1D5RCK4_A0A1D5RCK4_MACMU_9544 and tr_A0A2K6D1Z1_A0A2K6D1Z1_MACNE_9545 are exactly identical! WARNING: Sequences tr_F6UR85_F6UR85_MACMU_9544 and tr_A0A2K6ADH3_A0A2K6ADH3_MANLE_9568 are exactly identical! WARNING: Sequences tr_F6ZAL5_F6ZAL5_MACMU_9544 and tr_A0A2K5NSA5_A0A2K5NSA5_CERAT_9531 are exactly identical! WARNING: Sequences tr_F7C0K1_F7C0K1_MACMU_9544 and tr_A0A2K6B5R4_A0A2K6B5R4_MACNE_9545 are exactly identical! WARNING: Sequences tr_F7F0N9_F7F0N9_MACMU_9544 and tr_A0A2K5LZF8_A0A2K5LZF8_CERAT_9531 are exactly identical! WARNING: Sequences tr_F7F0N9_F7F0N9_MACMU_9544 and tr_A0A2K5YGT5_A0A2K5YGT5_MANLE_9568 are exactly identical! WARNING: Sequences tr_F7GB84_F7GB84_MACMU_9544 and tr_A0A2K6BN44_A0A2K6BN44_MACNE_9545 are exactly identical! WARNING: Sequences tr_F7GTJ8_F7GTJ8_MACMU_9544 and tr_A0A2K6BJH0_A0A2K6BJH0_MACNE_9545 are exactly identical! WARNING: Duplicate sequences found: 12 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/Q68DY1/3_mltree/Q68DY1.raxml.reduced.phy Alignment comprises 1 partitions and 655 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 655 / 655 Gaps: 19.48 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/3_mltree/Q68DY1.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 / 164 / 13120 [00:00:00] Data distribution: max. searches per worker: 10 Starting ML tree search with 20 distinct starting trees [00:00:00 -784833.982009] Initial branch length optimization [00:00:04 -694487.278258] Model parameter optimization (eps = 10.000000) [00:00:41 -691672.674783] AUTODETECT spr round 1 (radius: 5) [00:03:28 -555866.384432] AUTODETECT spr round 2 (radius: 10) [00:06:34 -356281.366219] AUTODETECT spr round 3 (radius: 15) [00:09:54 -268472.004293] AUTODETECT spr round 4 (radius: 20) [00:14:36 -257729.267766] AUTODETECT spr round 5 (radius: 25) [00:19:51 -255690.880796] SPR radius for FAST iterations: 25 (autodetect) [00:19:51 -255690.880796] Model parameter optimization (eps = 3.000000) [00:20:10 -255471.731663] FAST spr round 1 (radius: 25) [00:23:03 -228968.851851] FAST spr round 2 (radius: 25) [00:25:26 -227820.880685] FAST spr round 3 (radius: 25) [00:27:38 -227654.566815] FAST spr round 4 (radius: 25) [00:29:40 -227629.840732] FAST spr round 5 (radius: 25) [00:31:33 -227627.934293] FAST spr round 6 (radius: 25) [00:33:25 -227627.600940] FAST spr round 7 (radius: 25) [00:35:14 -227627.600871] Model parameter optimization (eps = 1.000000) [00:35:28 -227619.037950] SLOW spr round 1 (radius: 5) [00:38:05 -227552.676566] SLOW spr round 2 (radius: 5) [00:40:34 -227547.950900] SLOW spr round 3 (radius: 5) [00:42:55 -227547.938575] SLOW spr round 4 (radius: 10) [00:45:34 -227547.938429] SLOW spr round 5 (radius: 15) [00:51:29 -227547.938355] SLOW spr round 6 (radius: 20) [00:59:56 -227543.192764] SLOW spr round 7 (radius: 5) [01:03:03 -227543.108058] SLOW spr round 8 (radius: 10) [01:06:13 -227542.377963] SLOW spr round 9 (radius: 5) [01:09:03 -227542.334163] SLOW spr round 10 (radius: 10) [01:09:10] [worker #1] ML tree search #2, logLikelihood: -227544.178082 [01:11:52 -227542.334057] SLOW spr round 11 (radius: 15) [01:17:14 -227542.334045] SLOW spr round 12 (radius: 20) [01:25:50 -227542.334034] SLOW spr round 13 (radius: 25) [01:34:58 -227542.334023] Model parameter optimization (eps = 0.100000) [01:35:12] [worker #0] ML tree search #1, logLikelihood: -227541.288321 [01:35:12 -784566.819140] Initial branch length optimization [01:35:16 -693184.916369] Model parameter optimization (eps = 10.000000) [01:35:57 -690513.344480] AUTODETECT spr round 1 (radius: 5) [01:38:54 -564438.431826] AUTODETECT spr round 2 (radius: 10) [01:42:19 -364886.711564] AUTODETECT spr round 3 (radius: 15) [01:45:51 -273111.909286] AUTODETECT spr round 4 (radius: 20) [01:50:24 -260645.734165] AUTODETECT spr round 5 (radius: 25) [01:55:36 -259600.910845] SPR radius for FAST iterations: 25 (autodetect) [01:55:36 -259600.910845] Model parameter optimization (eps = 3.000000) [01:55:56 -259364.086369] FAST spr round 1 (radius: 25) [01:59:05 -228891.085003] FAST spr round 2 (radius: 25) [02:01:31 -227736.308857] FAST spr round 3 (radius: 25) [02:03:47 -227646.909224] FAST spr round 4 (radius: 25) [02:05:46 -227642.806282] FAST spr round 5 (radius: 25) [02:07:41 -227642.806201] Model parameter optimization (eps = 1.000000) [02:07:56 -227639.210235] SLOW spr round 1 (radius: 5) [02:10:42 -227571.944020] SLOW spr round 2 (radius: 5) [02:13:21 -227533.031542] SLOW spr round 3 (radius: 5) [02:15:54 -227530.746945] SLOW spr round 4 (radius: 5) [02:16:41] [worker #1] ML tree search #4, logLikelihood: -227518.958145 [02:18:24 -227530.746817] SLOW spr round 5 (radius: 10) [02:21:08 -227520.877071] SLOW spr round 6 (radius: 5) [02:24:16 -227519.319720] SLOW spr round 7 (radius: 5) [02:27:01 -227519.319532] SLOW spr round 8 (radius: 10) [02:29:49 -227519.319444] SLOW spr round 9 (radius: 15) [02:35:56 -227512.905888] SLOW spr round 10 (radius: 5) [02:39:13 -227509.978246] SLOW spr round 11 (radius: 5) [02:42:01 -227509.978139] SLOW spr round 12 (radius: 10) [02:44:50 -227509.978046] SLOW spr round 13 (radius: 15) [02:50:54 -227509.977954] SLOW spr round 14 (radius: 20) [02:59:48 -227509.977861] SLOW spr round 15 (radius: 25) [03:08:43 -227509.977768] Model parameter optimization (eps = 0.100000) [03:08:55] [worker #0] ML tree search #3, logLikelihood: -227509.680570 [03:08:55 -785280.032916] Initial branch length optimization [03:08:58 -693949.754764] Model parameter optimization (eps = 10.000000) [03:09:33 -691262.183531] AUTODETECT spr round 1 (radius: 5) [03:12:20 -562030.944268] AUTODETECT spr round 2 (radius: 10) [03:15:21 -380256.848061] AUTODETECT spr round 3 (radius: 15) [03:18:43 -294727.317095] AUTODETECT spr round 4 (radius: 20) [03:22:57 -269035.447965] AUTODETECT spr round 5 (radius: 25) [03:27:52 -267844.315587] SPR radius for FAST iterations: 25 (autodetect) [03:27:52 -267844.315587] Model parameter optimization (eps = 3.000000) [03:28:21 -267686.968890] FAST spr round 1 (radius: 25) [03:31:36 -229311.269892] FAST spr round 2 (radius: 25) [03:34:10 -227760.883953] FAST spr round 3 (radius: 25) [03:36:26 -227648.123146] FAST spr round 4 (radius: 25) [03:38:28 -227621.391361] FAST spr round 5 (radius: 25) [03:40:22 -227621.391222] Model parameter optimization (eps = 1.000000) [03:40:38 -227612.177148] SLOW spr round 1 (radius: 5) [03:41:28] [worker #1] ML tree search #6, logLikelihood: -227529.137636 [03:43:26 -227549.671068] SLOW spr round 2 (radius: 5) [03:46:22 -227532.568613] SLOW spr round 3 (radius: 5) [03:48:51 -227532.568193] SLOW spr round 4 (radius: 10) [03:51:42 -227530.616759] SLOW spr round 5 (radius: 5) [03:54:48 -227530.616583] SLOW spr round 6 (radius: 10) [03:57:23 -227530.616475] SLOW spr round 7 (radius: 15) [04:03:16 -227530.616367] SLOW spr round 8 (radius: 20) [04:12:26 -227530.616258] SLOW spr round 9 (radius: 25) [04:21:51 -227530.616150] Model parameter optimization (eps = 0.100000) [04:22:07] [worker #0] ML tree search #5, logLikelihood: -227529.969066 [04:22:07 -787460.189973] Initial branch length optimization [04:22:10 -696537.405244] Model parameter optimization (eps = 10.000000) [04:22:55 -693687.011721] AUTODETECT spr round 1 (radius: 5) [04:25:58 -560641.979706] AUTODETECT spr round 2 (radius: 10) [04:29:07 -364596.074578] AUTODETECT spr round 3 (radius: 15) [04:31:53 -290315.633863] AUTODETECT spr round 4 (radius: 20) [04:35:23 -266589.683826] AUTODETECT spr round 5 (radius: 25) [04:39:41 -265380.078065] SPR radius for FAST iterations: 25 (autodetect) [04:39:41 -265380.078065] Model parameter optimization (eps = 3.000000) [04:39:58 -265146.210944] FAST spr round 1 (radius: 25) [04:42:40 -229026.700825] FAST spr round 2 (radius: 25) [04:44:47 -227785.723435] FAST spr round 3 (radius: 25) [04:46:45 -227656.626958] FAST spr round 4 (radius: 25) [04:48:30 -227628.170816] FAST spr round 5 (radius: 25) [04:50:08 -227628.170586] Model parameter optimization (eps = 1.000000) [04:50:19 -227621.814464] SLOW spr round 1 (radius: 5) [04:52:40 -227571.187814] SLOW spr round 2 (radius: 5) [04:54:40] [worker #1] ML tree search #8, logLikelihood: -227566.486092 [04:54:55 -227561.462590] SLOW spr round 3 (radius: 5) [04:57:08 -227557.955815] SLOW spr round 4 (radius: 5) [04:59:15 -227557.955692] SLOW spr round 5 (radius: 10) [05:01:33 -227557.955599] SLOW spr round 6 (radius: 15) [05:06:52 -227548.007980] SLOW spr round 7 (radius: 5) [05:09:39 -227546.056649] SLOW spr round 8 (radius: 5) [05:12:03 -227544.966805] SLOW spr round 9 (radius: 5) [05:14:28 -227544.966643] SLOW spr round 10 (radius: 10) [05:17:18 -227541.852867] SLOW spr round 11 (radius: 5) [05:20:34 -227535.538016] SLOW spr round 12 (radius: 5) [05:23:25 -227535.273017] SLOW spr round 13 (radius: 5) [05:26:04 -227535.272976] SLOW spr round 14 (radius: 10) [05:28:52 -227535.272938] SLOW spr round 15 (radius: 15) [05:35:10 -227535.272899] SLOW spr round 16 (radius: 20) [05:44:23 -227535.272861] SLOW spr round 17 (radius: 25) [05:54:10 -227535.272822] Model parameter optimization (eps = 0.100000) [05:54:25] [worker #0] ML tree search #7, logLikelihood: -227534.296715 [05:54:25 -784320.524467] Initial branch length optimization [05:54:29 -693745.035313] Model parameter optimization (eps = 10.000000) [05:55:16 -690919.435811] AUTODETECT spr round 1 (radius: 5) [05:58:13 -555580.845848] AUTODETECT spr round 2 (radius: 10) [06:01:31 -359568.582445] AUTODETECT spr round 3 (radius: 15) [06:05:05 -278554.768718] AUTODETECT spr round 4 (radius: 20) [06:07:52] [worker #1] ML tree search #10, logLikelihood: -227562.541322 [06:09:28 -258576.638745] AUTODETECT spr round 5 (radius: 25) [06:14:29 -256905.268944] SPR radius for FAST iterations: 25 (autodetect) [06:14:29 -256905.268944] Model parameter optimization (eps = 3.000000) [06:14:52 -256705.603459] FAST spr round 1 (radius: 25) [06:18:10 -228632.058637] FAST spr round 2 (radius: 25) [06:20:49 -227719.706328] FAST spr round 3 (radius: 25) [06:23:07 -227652.849846] FAST spr round 4 (radius: 25) [06:25:13 -227645.802302] FAST spr round 5 (radius: 25) [06:27:19 -227628.118690] FAST spr round 6 (radius: 25) [06:29:18 -227628.118524] Model parameter optimization (eps = 1.000000) [06:29:34 -227621.763129] SLOW spr round 1 (radius: 5) [06:32:22 -227567.559654] SLOW spr round 2 (radius: 5) [06:35:05 -227553.486147] SLOW spr round 3 (radius: 5) [06:37:44 -227548.168508] SLOW spr round 4 (radius: 5) [06:40:20 -227547.400636] SLOW spr round 5 (radius: 5) [06:42:54 -227547.400522] SLOW spr round 6 (radius: 10) [06:45:42 -227541.478990] SLOW spr round 7 (radius: 5) [06:48:55 -227530.191160] SLOW spr round 8 (radius: 5) [06:51:44 -227529.656504] SLOW spr round 9 (radius: 5) [06:54:23 -227529.656440] SLOW spr round 10 (radius: 10) [06:57:10 -227529.656384] SLOW spr round 11 (radius: 15) [07:03:23 -227529.656327] SLOW spr round 12 (radius: 20) [07:12:25 -227529.656270] SLOW spr round 13 (radius: 25) [07:20:03] [worker #1] ML tree search #12, logLikelihood: -227571.002964 [07:21:51 -227529.656238] Model parameter optimization (eps = 0.100000) [07:21:59] [worker #0] ML tree search #9, logLikelihood: -227529.544453 [07:21:59 -783832.949003] Initial branch length optimization [07:22:03 -692723.546945] Model parameter optimization (eps = 10.000000) [07:22:43 -689914.170449] AUTODETECT spr round 1 (radius: 5) [07:25:43 -565865.735836] AUTODETECT spr round 2 (radius: 10) [07:28:56 -365094.126061] AUTODETECT spr round 3 (radius: 15) [07:32:29 -282462.596478] AUTODETECT spr round 4 (radius: 20) [07:37:09 -261456.107801] AUTODETECT spr round 5 (radius: 25) [07:42:01 -257676.942903] SPR radius for FAST iterations: 25 (autodetect) [07:42:01 -257676.942903] Model parameter optimization (eps = 3.000000) [07:42:24 -257434.449495] FAST spr round 1 (radius: 25) [07:45:33 -228593.159584] FAST spr round 2 (radius: 25) [07:48:07 -227703.637302] FAST spr round 3 (radius: 25) [07:50:27 -227619.359913] FAST spr round 4 (radius: 25) [07:52:36 -227606.199342] FAST spr round 5 (radius: 25) [07:54:39 -227582.541652] FAST spr round 6 (radius: 25) [07:56:38 -227579.894677] FAST spr round 7 (radius: 25) [07:58:34 -227579.894559] Model parameter optimization (eps = 1.000000) [07:58:52 -227577.019276] SLOW spr round 1 (radius: 5) [08:01:40 -227518.058241] SLOW spr round 2 (radius: 5) [08:04:22 -227514.908302] SLOW spr round 3 (radius: 5) [08:07:00 -227513.927805] SLOW spr round 4 (radius: 5) [08:09:36 -227507.511800] SLOW spr round 5 (radius: 5) [08:12:09 -227507.511604] SLOW spr round 6 (radius: 10) [08:14:55 -227507.511496] SLOW spr round 7 (radius: 15) [08:21:15 -227507.511387] SLOW spr round 8 (radius: 20) [08:30:20 -227507.511278] SLOW spr round 9 (radius: 25) [08:39:42 -227507.511169] Model parameter optimization (eps = 0.100000) [08:39:48] [worker #0] ML tree search #11, logLikelihood: -227507.417748 [08:39:48 -780156.320634] Initial branch length optimization [08:39:53 -691568.988084] Model parameter optimization (eps = 10.000000) [08:40:30 -688861.496933] AUTODETECT spr round 1 (radius: 5) [08:41:14] [worker #1] ML tree search #14, logLikelihood: -227541.376270 [08:43:28 -559728.184955] AUTODETECT spr round 2 (radius: 10) [08:46:46 -352266.431722] AUTODETECT spr round 3 (radius: 15) [08:50:18 -279514.866433] AUTODETECT spr round 4 (radius: 20) [08:54:53 -266006.225562] AUTODETECT spr round 5 (radius: 25) [09:01:41 -260969.180341] SPR radius for FAST iterations: 25 (autodetect) [09:01:41 -260969.180341] Model parameter optimization (eps = 3.000000) [09:02:16 -260737.328638] FAST spr round 1 (radius: 25) [09:05:40 -229029.035717] FAST spr round 2 (radius: 25) [09:08:21 -227719.636969] FAST spr round 3 (radius: 25) [09:10:39 -227617.659041] FAST spr round 4 (radius: 25) [09:12:44 -227596.581579] FAST spr round 5 (radius: 25) [09:14:44 -227591.062267] FAST spr round 6 (radius: 25) [09:16:42 -227589.054873] FAST spr round 7 (radius: 25) [09:18:38 -227589.054621] Model parameter optimization (eps = 1.000000) [09:18:56 -227584.046509] SLOW spr round 1 (radius: 5) [09:21:41 -227551.292067] SLOW spr round 2 (radius: 5) [09:24:23 -227531.770532] SLOW spr round 3 (radius: 5) [09:26:56 -227531.174431] SLOW spr round 4 (radius: 5) [09:29:26 -227531.174345] SLOW spr round 5 (radius: 10) [09:32:10 -227530.306981] SLOW spr round 6 (radius: 5) [09:35:11 -227530.306825] SLOW spr round 7 (radius: 10) [09:38:08 -227529.421344] SLOW spr round 8 (radius: 5) [09:40:59 -227528.646335] SLOW spr round 9 (radius: 5) [09:43:31 -227528.645835] SLOW spr round 10 (radius: 10) [09:46:07 -227528.645748] SLOW spr round 11 (radius: 15) [09:51:48 -227528.645663] SLOW spr round 12 (radius: 20) [10:00:14 -227528.645578] SLOW spr round 13 (radius: 25) [10:00:16] [worker #1] ML tree search #16, logLikelihood: -227537.426118 [10:09:00 -227528.645492] Model parameter optimization (eps = 0.100000) [10:09:10] [worker #0] ML tree search #13, logLikelihood: -227528.054888 [10:09:10 -786704.367064] Initial branch length optimization [10:09:14 -694784.159703] Model parameter optimization (eps = 10.000000) [10:09:51 -691912.054582] AUTODETECT spr round 1 (radius: 5) [10:12:39 -571254.287684] AUTODETECT spr round 2 (radius: 10) [10:15:46 -363263.353800] AUTODETECT spr round 3 (radius: 15) [10:18:54 -276122.140995] AUTODETECT spr round 4 (radius: 20) [10:23:14 -263384.282250] AUTODETECT spr round 5 (radius: 25) [10:27:53 -259693.363203] SPR radius for FAST iterations: 25 (autodetect) [10:27:53 -259693.363203] Model parameter optimization (eps = 3.000000) [10:28:14 -259468.214252] FAST spr round 1 (radius: 25) [10:31:10 -228960.738078] FAST spr round 2 (radius: 25) [10:33:31 -227686.215911] FAST spr round 3 (radius: 25) [10:35:43 -227620.669118] FAST spr round 4 (radius: 25) [10:37:41 -227611.893372] FAST spr round 5 (radius: 25) [10:39:39 -227599.924895] FAST spr round 6 (radius: 25) [10:41:30 -227593.299253] FAST spr round 7 (radius: 25) [10:43:19 -227593.299210] Model parameter optimization (eps = 1.000000) [10:43:27 -227592.305440] SLOW spr round 1 (radius: 5) [10:46:01 -227550.183967] SLOW spr round 2 (radius: 5) [10:48:31 -227542.490059] SLOW spr round 3 (radius: 5) [10:50:59 -227533.353444] SLOW spr round 4 (radius: 5) [10:53:20 -227533.353013] SLOW spr round 5 (radius: 10) [10:55:52 -227526.619606] SLOW spr round 6 (radius: 5) [10:58:52 -227521.061945] SLOW spr round 7 (radius: 5) [11:01:25 -227521.061821] SLOW spr round 8 (radius: 10) [11:04:01 -227521.061786] SLOW spr round 9 (radius: 15) [11:09:22 -227521.061751] SLOW spr round 10 (radius: 20) [11:13:20] [worker #1] ML tree search #18, logLikelihood: -227504.904871 [11:17:17 -227521.061716] SLOW spr round 11 (radius: 25) [11:25:32 -227521.061681] Model parameter optimization (eps = 0.100000) [11:25:42] [worker #0] ML tree search #15, logLikelihood: -227520.476430 [11:25:43 -786995.340522] Initial branch length optimization [11:25:46 -695689.855280] Model parameter optimization (eps = 10.000000) [11:26:24 -692924.468830] AUTODETECT spr round 1 (radius: 5) [11:29:11 -560705.635811] AUTODETECT spr round 2 (radius: 10) [11:32:13 -355292.249248] AUTODETECT spr round 3 (radius: 15) [11:35:38 -271903.317998] AUTODETECT spr round 4 (radius: 20) [11:39:37 -260272.726778] AUTODETECT spr round 5 (radius: 25) [11:44:13 -259908.350544] SPR radius for FAST iterations: 25 (autodetect) [11:44:13 -259908.350544] Model parameter optimization (eps = 3.000000) [11:44:30 -259725.058012] FAST spr round 1 (radius: 25) [11:47:29 -228435.373047] FAST spr round 2 (radius: 25) [11:49:48 -227708.804299] FAST spr round 3 (radius: 25) [11:51:58 -227609.107137] FAST spr round 4 (radius: 25) [11:53:52 -227600.186283] FAST spr round 5 (radius: 25) [11:55:41 -227599.671967] FAST spr round 6 (radius: 25) [11:57:28 -227599.671886] Model parameter optimization (eps = 1.000000) [11:57:43 -227588.009889] SLOW spr round 1 (radius: 5) [12:00:16 -227538.472342] SLOW spr round 2 (radius: 5) [12:02:46 -227519.365559] SLOW spr round 3 (radius: 5) [12:05:09 -227515.929602] SLOW spr round 4 (radius: 5) [12:07:30 -227512.741596] SLOW spr round 5 (radius: 5) [12:09:47 -227512.741517] SLOW spr round 6 (radius: 10) [12:12:15 -227512.741439] SLOW spr round 7 (radius: 15) [12:17:58 -227512.741361] SLOW spr round 8 (radius: 20) [12:26:15 -227512.741283] SLOW spr round 9 (radius: 25) [12:28:05] [worker #1] ML tree search #20, logLikelihood: -227540.028363 [12:34:58 -227512.741205] Model parameter optimization (eps = 0.100000) [12:35:05] [worker #0] ML tree search #17, logLikelihood: -227512.417243 [12:35:05 -784469.827822] Initial branch length optimization [12:35:10 -693807.596662] Model parameter optimization (eps = 10.000000) [12:35:48 -691093.276863] AUTODETECT spr round 1 (radius: 5) [12:38:30 -556424.482842] AUTODETECT spr round 2 (radius: 10) [12:41:28 -356450.470108] AUTODETECT spr round 3 (radius: 15) [12:44:35 -282060.037337] AUTODETECT spr round 4 (radius: 20) [12:49:02 -265781.459100] AUTODETECT spr round 5 (radius: 25) [12:53:30 -264229.039588] SPR radius for FAST iterations: 25 (autodetect) [12:53:30 -264229.039588] Model parameter optimization (eps = 3.000000) [12:53:52 -264041.001435] FAST spr round 1 (radius: 25) [12:56:43 -229739.321292] FAST spr round 2 (radius: 25) [12:59:05 -227785.390668] FAST spr round 3 (radius: 25) [13:01:07 -227626.650720] FAST spr round 4 (radius: 25) [13:02:58 -227619.027556] FAST spr round 5 (radius: 25) [13:04:42 -227619.027084] Model parameter optimization (eps = 1.000000) [13:04:56 -227610.398620] SLOW spr round 1 (radius: 5) [13:07:32 -227568.500509] SLOW spr round 2 (radius: 5) [13:10:03 -227549.408915] SLOW spr round 3 (radius: 5) [13:12:20 -227549.408422] SLOW spr round 4 (radius: 10) [13:14:47 -227549.408413] SLOW spr round 5 (radius: 15) [13:20:25 -227549.408404] SLOW spr round 6 (radius: 20) [13:28:27 -227549.408396] SLOW spr round 7 (radius: 25) [13:36:51 -227549.408388] Model parameter optimization (eps = 0.100000) [13:37:00] [worker #0] ML tree search #19, logLikelihood: -227549.162091 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.173942,0.483171) (0.165122,0.760008) (0.362644,0.922292) (0.298293,1.528695) 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: -227504.904871 AIC score: 459019.809743 / AICc score: 8503079.809743 / BIC score: 468011.503390 Free parameters (model + branch lengths): 2005 WARNING: Number of free parameters (K=2005) is larger than alignment size (n=655). 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/Q68DY1/3_mltree/Q68DY1.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/3_mltree/Q68DY1.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/3_mltree/Q68DY1.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q68DY1/3_mltree/Q68DY1.raxml.log Analysis started: 01-Jul-2021 17:09:21 / finished: 02-Jul-2021 06:46:21 Elapsed time: 49020.219 seconds Consumed energy: 4376.850 Wh (= 22 km in an electric car, or 109 km with an e-scooter!)