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 18-Jun-2021 11:37:51 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/2_msa/O43826_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF [00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/2_msa/O43826_trimmed_msa.fasta [00:00:00] Loaded alignment with 168 taxa and 426 sites WARNING: Sequences tr_A0A2I3T9T2_A0A2I3T9T2_PANTR_9598 and tr_A0A2R9BE17_A0A2R9BE17_PANPA_9597 are exactly identical! WARNING: Sequences tr_A0A0V0RXX9_A0A0V0RXX9_9BILA_6336 and tr_A0A0V0U4N9_A0A0V0U4N9_9BILA_144512 are exactly identical! WARNING: Sequences tr_A0A1S3K8Q1_A0A1S3K8Q1_LINUN_7574 and tr_A0A1S3K927_A0A1S3K927_LINUN_7574 are exactly identical! WARNING: Sequences tr_A0A226MUM6_A0A226MUM6_CALSU_9009 and tr_A0A226P7Q7_A0A226P7Q7_COLVI_9014 are exactly identical! WARNING: Duplicate sequences found: 4 NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.reduced.phy Alignment comprises 1 partitions and 425 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 426 / 425 Gaps: 7.37 % Invariant sites: 1.17 % NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.rba Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] Generating 20 random starting tree(s) with 168 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 213 / 17040 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -94119.023476] Initial branch length optimization [00:00:00 -69576.869618] Model parameter optimization (eps = 10.000000) [00:00:16 -69016.272420] AUTODETECT spr round 1 (radius: 5) [00:00:23 -57667.776951] AUTODETECT spr round 2 (radius: 10) 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 6258R CPU @ 2.70GHz, 56 cores, 187 GB RAM RAxML-NG was called at 18-Jun-2021 11:39:36 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/2_msa/O43826_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF WARNING: The model you specified on the command line (LG4X) will be ignored since the binary MSA file already contains a model definition. If you want to change the model, please re-run RAxML-NG with the original PHYLIP/FASTA alignment and --redo option. [00:00:00] Loading binary alignment from file: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.rba [00:00:00] Alignment comprises 168 taxa, 1 partitions and 425 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 426 / 425 Gaps: 7.37 % Invariant sites: 1.17 % Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] NOTE: Resuming execution from checkpoint (logLH: -57667.78, ML trees: 0, bootstraps: 0) [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 213 / 17040 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -57667.776951] AUTODETECT spr round 2 (radius: 10) [00:00:10 -49203.178959] AUTODETECT spr round 3 (radius: 15) [00:00:27 -41112.772973] AUTODETECT spr round 4 (radius: 20) [00:00:43 -40772.588921] AUTODETECT spr round 5 (radius: 25) [00:00:58 -40758.585446] SPR radius for FAST iterations: 25 (autodetect) [00:00:58 -40758.585446] Model parameter optimization (eps = 3.000000) [00:01:06 -40598.602746] FAST spr round 1 (radius: 25) [00:01:18 -39018.839525] FAST spr round 2 (radius: 25) [00:01:30 -38905.679332] FAST spr round 3 (radius: 25) [00:01:39 -38894.057443] FAST spr round 4 (radius: 25) [00:01:46 -38885.823584] FAST spr round 5 (radius: 25) [00:01:54 -38882.496282] FAST spr round 6 (radius: 25) [00:02:00 -38882.495787] Model parameter optimization (eps = 1.000000) [00:02:03 -38881.958990] SLOW spr round 1 (radius: 5) [00:02:19 -38872.821600] SLOW spr round 2 (radius: 5) [00:02:34 -38871.170058] SLOW spr round 3 (radius: 5) [00:02:49 -38871.139179] SLOW spr round 4 (radius: 10) 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 18-Jun-2021 12:51:23 as follows: raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/2_msa/O43826_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF WARNING: The model you specified on the command line (LG4X) will be ignored since the binary MSA file already contains a model definition. If you want to change the model, please re-run RAxML-NG with the original PHYLIP/FASTA alignment and --redo option. [00:00:00] Loading binary alignment from file: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.rba [00:00:00] Alignment comprises 168 taxa, 1 partitions and 425 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 426 / 425 Gaps: 7.37 % Invariant sites: 1.17 % Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s) Parallel reduction/worker buffer size: 1 KB / 0 KB [00:00:00] NOTE: Resuming execution from checkpoint (logLH: -38871.14, ML trees: 0, bootstraps: 0) [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 213 / 17040 [00:00:00] Data distribution: max. searches per worker: 7 Starting ML tree search with 20 distinct starting trees [00:00:00 -38871.139179] SPR radius for FAST iterations: 25 (autodetect) [00:00:00 -38871.139179] SLOW spr round 4 (radius: 10) [00:00:13 -38868.685647] SLOW spr round 5 (radius: 5) [00:00:31 -38867.406969] SLOW spr round 6 (radius: 5) [00:00:46 -38867.406884] SLOW spr round 7 (radius: 10) [00:01:00 -38867.406880] SLOW spr round 8 (radius: 15) [00:01:03] [worker #2] ML tree search #3, logLikelihood: -38879.203674 [00:01:20 -38867.406880] SLOW spr round 9 (radius: 20) [00:01:27] [worker #1] ML tree search #2, logLikelihood: -38873.482211 [00:01:44 -38867.406880] SLOW spr round 10 (radius: 25) [00:02:01 -38867.406880] Model parameter optimization (eps = 0.100000) [00:02:04] [worker #0] ML tree search #1, logLikelihood: -38867.130864 [00:02:04 -93677.363057] Initial branch length optimization [00:02:05 -68528.132000] Model parameter optimization (eps = 10.000000) [00:02:22 -67927.793508] AUTODETECT spr round 1 (radius: 5) [00:02:28 -58178.532004] AUTODETECT spr round 2 (radius: 10) [00:02:38 -46532.999534] AUTODETECT spr round 3 (radius: 15) [00:02:52 -41689.465846] AUTODETECT spr round 4 (radius: 20) [00:03:07 -41567.299508] AUTODETECT spr round 5 (radius: 25) [00:03:20 -41510.387298] SPR radius for FAST iterations: 25 (autodetect) [00:03:20 -41510.387298] Model parameter optimization (eps = 3.000000) [00:03:28 -41276.665179] FAST spr round 1 (radius: 25) [00:03:39 -39085.003381] FAST spr round 2 (radius: 25) [00:03:48 -38907.954001] FAST spr round 3 (radius: 25) [00:03:55 -38902.738874] FAST spr round 4 (radius: 25) [00:04:02 -38897.928143] FAST spr round 5 (radius: 25) [00:04:08 -38897.927562] Model parameter optimization (eps = 1.000000) [00:04:12 -38896.382088] SLOW spr round 1 (radius: 5) [00:04:26 -38880.768355] SLOW spr round 2 (radius: 5) [00:04:39 -38876.944118] SLOW spr round 3 (radius: 5) [00:04:51 -38876.500091] SLOW spr round 4 (radius: 5) [00:05:04 -38876.500076] SLOW spr round 5 (radius: 10) [00:05:16] [worker #1] ML tree search #5, logLikelihood: -38871.153252 [00:05:17 -38876.119463] SLOW spr round 6 (radius: 5) [00:05:35 -38876.116864] SLOW spr round 7 (radius: 10) [00:05:52 -38876.116615] SLOW spr round 8 (radius: 15) [00:06:03] [worker #2] ML tree search #6, logLikelihood: -38877.726453 [00:06:11 -38876.116592] SLOW spr round 9 (radius: 20) [00:06:36 -38876.116590] SLOW spr round 10 (radius: 25) [00:06:53 -38876.116590] Model parameter optimization (eps = 0.100000) [00:06:55] [worker #0] ML tree search #4, logLikelihood: -38876.004257 [00:06:55 -94723.337922] Initial branch length optimization [00:06:56 -69488.211319] Model parameter optimization (eps = 10.000000) [00:07:10 -68860.802240] AUTODETECT spr round 1 (radius: 5) [00:07:17 -54215.466633] AUTODETECT spr round 2 (radius: 10) [00:07:27 -47036.498409] AUTODETECT spr round 3 (radius: 15) [00:07:37 -42825.736464] AUTODETECT spr round 4 (radius: 20) [00:07:52 -42428.943109] AUTODETECT spr round 5 (radius: 25) [00:08:03 -42428.937141] SPR radius for FAST iterations: 20 (autodetect) [00:08:03 -42428.937141] Model parameter optimization (eps = 3.000000) [00:08:13 -42246.037556] FAST spr round 1 (radius: 20) [00:08:24 -38992.574086] FAST spr round 2 (radius: 20) [00:08:34 -38899.731884] FAST spr round 3 (radius: 20) [00:08:41 -38890.439260] FAST spr round 4 (radius: 20) [00:08:47 -38888.235781] FAST spr round 5 (radius: 20) [00:08:53 -38888.231456] Model parameter optimization (eps = 1.000000) [00:08:56 -38887.422800] SLOW spr round 1 (radius: 5) [00:09:09 -38881.056824] SLOW spr round 2 (radius: 5) [00:09:11] [worker #1] ML tree search #8, logLikelihood: -38876.620458 [00:09:22 -38881.054937] SLOW spr round 3 (radius: 10) [00:09:35 -38879.348996] SLOW spr round 4 (radius: 5) [00:09:52 -38879.122972] SLOW spr round 5 (radius: 5) [00:10:07 -38879.122864] SLOW spr round 6 (radius: 10) [00:10:21 -38876.859432] SLOW spr round 7 (radius: 5) [00:10:39 -38874.767590] SLOW spr round 8 (radius: 5) [00:10:53 -38874.767500] SLOW spr round 9 (radius: 10) [00:11:07 -38874.767494] SLOW spr round 10 (radius: 15) [00:11:27 -38874.767494] SLOW spr round 11 (radius: 20) [00:11:51 -38874.767494] SLOW spr round 12 (radius: 25) [00:12:09 -38874.767494] Model parameter optimization (eps = 0.100000) [00:12:11] [worker #0] ML tree search #7, logLikelihood: -38874.708047 [00:12:11 -93078.274382] Initial branch length optimization [00:12:12 -69165.554958] Model parameter optimization (eps = 10.000000) [00:12:25 -68585.925205] AUTODETECT spr round 1 (radius: 5) [00:12:32 -54991.934790] AUTODETECT spr round 2 (radius: 10) [00:12:42 -45598.348924] AUTODETECT spr round 3 (radius: 15) [00:12:53 -43385.779389] AUTODETECT spr round 4 (radius: 20) [00:13:04 -42195.671895] AUTODETECT spr round 5 (radius: 25) [00:13:13 -42195.634470] SPR radius for FAST iterations: 20 (autodetect) [00:13:13 -42195.634470] Model parameter optimization (eps = 3.000000) [00:13:21 -42021.461352] FAST spr round 1 (radius: 20) [00:13:33 -38960.164097] FAST spr round 2 (radius: 20) [00:13:34] [worker #1] ML tree search #11, logLikelihood: -38872.651603 [00:13:42 -38893.912180] FAST spr round 3 (radius: 20) [00:13:50 -38885.480296] FAST spr round 4 (radius: 20) [00:13:56 -38885.189673] FAST spr round 5 (radius: 20) [00:14:02 -38881.309924] FAST spr round 6 (radius: 20) [00:14:08 -38881.309858] Model parameter optimization (eps = 1.000000) [00:14:11 -38878.259188] SLOW spr round 1 (radius: 5) [00:14:19] [worker #2] ML tree search #9, logLikelihood: -38869.204653 [00:14:25 -38870.068188] SLOW spr round 2 (radius: 5) [00:14:39 -38868.653001] SLOW spr round 3 (radius: 5) [00:14:51 -38868.645403] SLOW spr round 4 (radius: 10) [00:15:04 -38868.644116] SLOW spr round 5 (radius: 15) [00:15:25 -38868.643882] SLOW spr round 6 (radius: 20) [00:15:48 -38868.643839] SLOW spr round 7 (radius: 25) [00:16:07 -38868.643831] Model parameter optimization (eps = 0.100000) [00:16:10] [worker #0] ML tree search #10, logLikelihood: -38868.399496 [00:16:10 -94297.162221] Initial branch length optimization [00:16:10 -69907.846581] Model parameter optimization (eps = 10.000000) [00:16:27 -69256.540896] AUTODETECT spr round 1 (radius: 5) [00:16:34 -54439.326981] AUTODETECT spr round 2 (radius: 10) [00:16:43 -48160.090266] AUTODETECT spr round 3 (radius: 15) [00:16:55 -41355.879542] AUTODETECT spr round 4 (radius: 20) [00:17:07 -41139.093956] AUTODETECT spr round 5 (radius: 25) [00:17:18 -41131.226472] SPR radius for FAST iterations: 25 (autodetect) [00:17:18 -41131.226472] Model parameter optimization (eps = 3.000000) [00:17:27 -40833.970885] FAST spr round 1 (radius: 25) [00:17:36] [worker #1] ML tree search #14, logLikelihood: -38877.266803 [00:17:38 -38986.834479] FAST spr round 2 (radius: 25) [00:17:47 -38915.189999] FAST spr round 3 (radius: 25) [00:17:54 -38903.069868] FAST spr round 4 (radius: 25) [00:18:00 -38901.038919] FAST spr round 5 (radius: 25) [00:18:06 -38901.034857] Model parameter optimization (eps = 1.000000) [00:18:08 -38900.322379] SLOW spr round 1 (radius: 5) [00:18:23 -38879.083569] SLOW spr round 2 (radius: 5) [00:18:37 -38875.185949] SLOW spr round 3 (radius: 5) [00:18:50 -38870.440323] SLOW spr round 4 (radius: 5) [00:19:03 -38870.439806] SLOW spr round 5 (radius: 10) [00:19:16 -38870.439801] SLOW spr round 6 (radius: 15) [00:19:36 -38870.439801] SLOW spr round 7 (radius: 20) [00:20:01 -38870.439801] SLOW spr round 8 (radius: 25) [00:20:17 -38870.439801] Model parameter optimization (eps = 0.100000) [00:20:20] [worker #0] ML tree search #13, logLikelihood: -38870.102173 [00:20:20 -93573.248781] Initial branch length optimization [00:20:20 -69273.240053] Model parameter optimization (eps = 10.000000) [00:20:34 -68659.201028] AUTODETECT spr round 1 (radius: 5) [00:20:41 -58378.987354] AUTODETECT spr round 2 (radius: 10) [00:20:52 -46541.002707] AUTODETECT spr round 3 (radius: 15) [00:21:05 -44411.477394] AUTODETECT spr round 4 (radius: 20) [00:21:19 -44411.474797] SPR radius for FAST iterations: 15 (autodetect) [00:21:19 -44411.474797] Model parameter optimization (eps = 3.000000) [00:21:28 -44250.711959] FAST spr round 1 (radius: 15) [00:21:38] [worker #1] ML tree search #17, logLikelihood: -38868.047506 [00:21:40 -39037.675971] FAST spr round 2 (radius: 15) [00:21:50 -38914.763726] FAST spr round 3 (radius: 15) [00:21:56 -38909.908199] FAST spr round 4 (radius: 15) [00:22:02 -38909.559008] FAST spr round 5 (radius: 15) [00:22:06] [worker #2] ML tree search #12, logLikelihood: -38868.046790 [00:22:08 -38909.558886] Model parameter optimization (eps = 1.000000) [00:22:12 -38895.756197] SLOW spr round 1 (radius: 5) [00:22:27 -38878.609096] SLOW spr round 2 (radius: 5) [00:22:40 -38877.025217] SLOW spr round 3 (radius: 5) [00:22:53 -38876.690389] SLOW spr round 4 (radius: 5) [00:23:06 -38876.690263] SLOW spr round 5 (radius: 10) [00:23:19 -38874.508019] SLOW spr round 6 (radius: 5) [00:23:37 -38873.141172] SLOW spr round 7 (radius: 5) [00:23:52 -38873.140724] SLOW spr round 8 (radius: 10) [00:24:06 -38873.140723] SLOW spr round 9 (radius: 15) [00:24:25 -38873.140723] SLOW spr round 10 (radius: 20) [00:24:48 -38873.140723] SLOW spr round 11 (radius: 25) [00:25:08 -38873.140723] Model parameter optimization (eps = 0.100000) [00:25:10] [worker #0] ML tree search #16, logLikelihood: -38873.045917 [00:25:10 -95545.053942] Initial branch length optimization [00:25:11 -69426.609232] Model parameter optimization (eps = 10.000000) [00:25:26 -68851.482097] AUTODETECT spr round 1 (radius: 5) [00:25:32 -55990.098016] AUTODETECT spr round 2 (radius: 10) [00:25:42 -46029.640814] AUTODETECT spr round 3 (radius: 15) [00:25:44] [worker #1] ML tree search #20, logLikelihood: -38873.212911 [00:25:56 -43039.387189] AUTODETECT spr round 4 (radius: 20) [00:26:08 -42971.890389] AUTODETECT spr round 5 (radius: 25) [00:26:18 -42942.806319] SPR radius for FAST iterations: 25 (autodetect) [00:26:18 -42942.806319] Model parameter optimization (eps = 3.000000) [00:26:25 -42713.285676] FAST spr round 1 (radius: 25) [00:26:37 -38949.187492] FAST spr round 2 (radius: 25) [00:26:46 -38891.452399] FAST spr round 3 (radius: 25) [00:26:52 -38884.233790] FAST spr round 4 (radius: 25) [00:26:58 -38883.982812] FAST spr round 5 (radius: 25) [00:27:04 -38883.971196] Model parameter optimization (eps = 1.000000) [00:27:07 -38882.177420] SLOW spr round 1 (radius: 5) [00:27:21 -38874.305639] SLOW spr round 2 (radius: 5) [00:27:34 -38867.186052] SLOW spr round 3 (radius: 5) [00:27:47 -38867.185277] SLOW spr round 4 (radius: 10) [00:27:59 -38867.185227] SLOW spr round 5 (radius: 15) [00:28:20 -38867.185223] SLOW spr round 6 (radius: 20) [00:28:44 -38867.185223] SLOW spr round 7 (radius: 25) [00:29:01 -38867.185223] Model parameter optimization (eps = 0.100000) [00:29:04] [worker #0] ML tree search #19, logLikelihood: -38866.752376 [00:29:41] [worker #2] ML tree search #15, logLikelihood: -38875.417736 [00:35:15] [worker #2] ML tree search #18, logLikelihood: -38882.880639 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.259499,0.603797) (0.375951,0.621962) (0.287050,1.326683) (0.077500,2.950492) 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: -38866.752376 AIC score: 78411.504751 / AICc score: 81091.969868 / BIC score: 79785.959690 Free parameters (model + branch lengths): 339 Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.bestTree All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.mlTrees Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.bestModel Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/030621_run/phylogeny-snakemake/results/O43826/3_mltree/O43826.raxml.log Analysis started: 18-Jun-2021 12:51:23 / finished: 18-Jun-2021 13:26:39 Elapsed time: 2115.292 seconds (this run) / 2308.293 seconds (total with restarts) Consumed energy: 200.161 Wh (= 1 km in an electric car, or 5 km with an e-scooter!)