BEAST v2.7.8, 2002-2025 Bayesian Evolutionary Analysis Sampling Trees Designed and developed by Remco Bouckaert, Alexei J. Drummond, Andrew Rambaut & Marc A. Suchard Centre for Computational Evolution University of Auckland r.bouckaert@auckland.ac.nz alexei@cs.auckland.ac.nz Institute of Evolutionary Biology University of Edinburgh a.rambaut@ed.ac.uk David Geffen School of Medicine University of California, Los Angeles msuchard@ucla.edu Downloads, Help & Resources: http://beast2.org/ Source code distributed under the GNU Lesser General Public License: http://github.com/CompEvol/beast2 BEAST developers: Alex Alekseyenko, Trevor Bedford, Erik Bloomquist, Joseph Heled, Sebastian Hoehna, Denise Kuehnert, Philippe Lemey, Wai Lok Sibon Li, Gerton Lunter, Sidney Markowitz, Vladimir Minin, Michael Defoin Platel, Oliver Pybus, Tim Vaughan, Chieh-Hsi Wu, Walter Xie Thanks to: Roald Forsberg, Beth Shapiro and Korbinian Strimmer Running file /Users/yil218/WorkSpace/BEAST-Tutorial/RSV2.xml File: RSV2.xml seed: -7436193881878261442 threads: 1 Loading package SSM v1.2.1 feast v10.5.0 flc v1.2.0 LPhyBeastExt v1.0.0 starbeast3 v1.1.9 CCD v1.0.3 Mascot v3.0.7 phylonco v1.2.0 SA v2.1.1 BEAST.base v2.7.8 BEASTLabs v2.0.3 BEAST.app v2.7.8 phylonco.lphybeast v1.2.1 BEAST_CLASSIC v1.6.4 MM v1.2.1 bdtree v0.0.1 ORC v1.2.0 lphybeast v1.2.1 Alignment(RSV2) 129 taxa 629 sites 332 patterns Filter 3::3 129 taxa 209 sites 92 patterns BE8078s92=92 NYCH09s93=93 SE01s92=92 SE05s91=91 MON1s92=92 BE1587s89=89 BE614s93=93 BE12005s94=94 BE174s95=95 BE12350s96=96 BE12216s96=96 BE11600s94=94 SE10s92=92 MAD6s92=92 BE15471s97=97 SE03s91=91 MAD2s93=93 BE10490s93=93 SE11s95=95 NYCH17s93=93 MAD6s93=93 MAD8s92=92 MAD1s93=93 BE13280s99=99 BE13192s99=99 BE1061s100=100 BE16s100=100 BE2122s100=100 BE1556s101=101 BE800s100=100 BE1441s101=101 BE11976s100=100 BE64s101=101 BE822s100=100 BE13281s99=99 BE1936s100=100 BE1835s101=101 BE1937s100=100 BE1224s101=101 BE2149s100=100 BE1343s101=101 BE1836s101=101 BE1717s101=101 BE112s101=101 BE1150s100=100 BE797s100=100 BE944s100=100 BE14536s98=98 BIR6190s89=89 MON1s90=90 WV12342s84=84 BE2584s85=85 BE933s88=88 WV5222s81=81 BE156s84=84 S2s76=76 BE11030s100=100 BE11129s100=100 BE11091s100=100 BE519s101=101 BE13425s99=99 BE004s102=102 SE12s97=97 BE14808s98=98 SE02s98=98 BE11s101=101 BE13393s99=99 BE14898s98=98 BE332s102=102 BE12028s100=100 BE14461s98=98 MON2s88=88 NYCH57s94=94 BE11465s94=94 MON1s89=89 BE15752s97=97 SE05s96=96 BE13551s95=95 BE12895s95=95 SE10s91=91 SE11s92=92 SE12s94=94 BE1591s90=90 BE512s95=95 SE01s95=95 BE4147s87=87 BE071s88=88 BE538s88=88 BE204s84=84 BE183s85=85 BE076s86=86 BE2466s85=85 BE4763s88=88 BE76s86=86 BE339s86=86 BE3252s86=86 BE410s86=86 WV23836s88=88 BE13462s99=99 BE11584s101=101 BE13412s99=99 SE12s95=95 BE12243s96=96 SE08s96=96 SE09s92=92 SE12s92=92 BE6274s91=91 MADs91=91 BE1440s92=92 BE6460s91=91 BE305s89=89 BE3785s87=87 BE307s87=87 BE119s87=87 BE138s90=90 BE191s90=90 BE369s90=90 MON9s91=91 BIR642s89=89 WV19983s87=87 MON5s91=91 MON51s90=90 MON9s92=92 NYCH34s94=94 BIR1734s89=89 WV2780s79=79 WV6973s82=82 AUSA2s61=61 USALongs56=56 AUSA2s61 = 61 (41.0) BE004s102 = 102 (0.0) BE071s88 = 88 (14.0) BE076s86 = 86 (16.0) BE10490s93 = 93 (9.0) BE1061s100 = 100 (2.0) BE11030s100 = 100 (2.0) BE11091s100 = 100 (2.0) BE11129s100 = 100 (2.0) BE112s101 = 101 (1.0) 119 more... Starting frequencies: [0.25, 0.25, 0.25, 0.25] Using BEAGLE version: 4.0.0 (PRE-RELEASE) resource 0: CPU (x86_64) with instance flags: PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_SSE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU Ignoring ambiguities in tree likelihood. Ignoring character uncertainty in tree likelihood. With 92 unique site patterns. Using rescaling scheme : dynamic Filter 1::3 129 taxa 210 sites 114 patterns Starting frequencies: [0.25, 0.25, 0.25, 0.25] Using BEAGLE version: 4.0.0 (PRE-RELEASE) resource 0: CPU (x86_64) with instance flags: PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_SSE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU Ignoring ambiguities in tree likelihood. Ignoring character uncertainty in tree likelihood. With 114 unique site patterns. Using rescaling scheme : dynamic Filter 2::3 129 taxa 210 sites 148 patterns Starting frequencies: [0.25, 0.25, 0.25, 0.25] Using BEAGLE version: 4.0.0 (PRE-RELEASE) resource 0: CPU (x86_64) with instance flags: PRECISION_DOUBLE COMPUTATION_SYNCH EIGEN_REAL SCALING_MANUAL SCALERS_RAW VECTOR_SSE THREADING_NONE PROCESSOR_CPU FRAMEWORK_CPU Ignoring ambiguities in tree likelihood. Ignoring character uncertainty in tree likelihood. With 148 unique site patterns. Using rescaling scheme : dynamic =============================================================================== Citations for this model: Bouckaert, Remco, Timothy G. Vaughan, Joￃﾫlle Barido-Sottani, Sebastiￃﾡn Duchￃﾪne, Mathieu Fourment, Alexandra Gavryushkina, Joseph Heled, Graham Jones, Denise Kￃﾼhnert, Nicola De Maio, Michael Matschiner, Fￃﾡbio K. Mendes, Nicola F. Mￃﾼller, Huw A. Ogilvie, Louis du Plessis, Alex Popinga, Andrew Rambaut, David Rasmussen, Igor Siveroni, Marc A. Suchard, Chieh-Hsi Wu, Dong Xie, Chi Zhang, Tanja Stadler, Alexei J. Drummond BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS computational biology 15, no. 4 (2019): e1006650. Hasegawa M, Kishino H, Yano T (1985) Dating the human-ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution 22:160-174. Douglas J, Zhang R, Bouckaert R. Adaptive dating and fast proposals: Revisiting the phylogenetic relaxed clock model. PLoS computational biology. 2021 Feb 2;17(2):e1008322. Bouckaert RR. An efficient coalescent epoch model for Bayesian phylogenetic inference. Systematic Biology, syac015, 2022 =============================================================================== Start likelihood: -48037.89319259741 Writing file /Users/yil218/WorkSpace/BEAST-Tutorial/RSV2.log Writing file /Users/yil218/WorkSpace/BEAST-Tutorial/RSV2.trees Sample posterior likelihood prior 0 -48037.2679 -47799.7762 -237.4916 -- 10000 -9071.9808 -8466.1093 -605.8714 -- 20000 -6935.0650 -6299.5461 -635.5189 -- 30000 -6303.9395 -5698.6533 -605.2862 -- 40000 -6200.0386 -5608.6356 -591.4029 -- 50000 -6153.1634 -5559.3705 -593.7929 -- 60000 -6094.0710 -5509.4721 -584.5988 46s/Msamples 70000 -6086.7914 -5498.2663 -588.5251 47s/Msamples 80000 -6079.3602 -5490.4249 -588.9353 46s/Msamples 90000 -6056.1070 -5472.6147 -583.4922 45s/Msamples 100000 -6083.5939 -5492.9587 -590.6352 44s/Msamples 110000 -6089.3679 -5493.1794 -596.1885 44s/Msamples 120000 -6098.8119 -5494.5916 -604.2203 43s/Msamples 130000 -6059.6491 -5467.4396 -592.2095 43s/Msamples 140000 -6088.9607 -5487.8687 -601.0920 43s/Msamples 150000 -6102.9333 -5486.8346 -616.0987 43s/Msamples 160000 -6087.7688 -5480.6014 -607.1673 42s/Msamples 170000 -6059.3839 -5471.2649 -588.1189 42s/Msamples 180000 -6054.2633 -5462.5960 -591.6672 42s/Msamples 190000 -6081.1050 -5465.7042 -615.4008 42s/Msamples 200000 -6082.3960 -5473.1363 -609.2597 41s/Msamples 210000 -6066.4510 -5465.6925 -600.7585 41s/Msamples 220000 -6073.6121 -5489.0878 -584.5243 41s/Msamples 230000 -6083.9531 -5486.3906 -597.5625 41s/Msamples 240000 -6058.9166 -5458.3772 -600.5393 41s/Msamples 250000 -6072.2373 -5481.2714 -590.9658 41s/Msamples 260000 -6076.3072 -5495.6304 -580.6768 41s/Msamples 270000 -6058.2669 -5475.7298 -582.5371 41s/Msamples 280000 -6054.1225 -5483.9418 -570.1806 41s/Msamples 290000 -6071.8638 -5475.1851 -596.6787 41s/Msamples 300000 -6056.3719 -5481.2993 -575.0725 41s/Msamples 310000 -6061.1278 -5480.1072 -581.0205 41s/Msamples 320000 -6064.1373 -5467.8967 -596.2405 41s/Msamples 330000 -6067.7974 -5474.4951 -593.3023 41s/Msamples 340000 -6065.5227 -5476.1434 -589.3792 41s/Msamples 350000 -6076.4684 -5477.7474 -598.7210 41s/Msamples 360000 -6060.3044 -5475.4072 -584.8971 41s/Msamples 370000 -6065.7740 -5476.2312 -589.5428 41s/Msamples 380000 -6047.5320 -5470.5911 -576.9408 41s/Msamples 390000 -6065.8184 -5483.0938 -582.7246 40s/Msamples 400000 -6075.2611 -5482.5734 -592.6877 40s/Msamples 410000 -6072.1798 -5476.6680 -595.5118 40s/Msamples 420000 -6047.3473 -5470.5929 -576.7544 40s/Msamples 430000 -6058.8928 -5476.3794 -582.5133 40s/Msamples 440000 -6058.2126 -5470.8940 -587.3185 40s/Msamples 450000 -6068.6766 -5468.0448 -600.6317 40s/Msamples 460000 -6072.5759 -5465.8264 -606.7495 40s/Msamples 470000 -6097.6523 -5489.5163 -608.1359 40s/Msamples 480000 -6086.0428 -5490.5784 -595.4643 40s/Msamples 490000 -6098.4500 -5507.7537 -590.6963 40s/Msamples 500000 -6065.6245 -5496.5645 -569.0600 40s/Msamples 510000 -6047.8923 -5481.0631 -566.8291 40s/Msamples 520000 -6078.7145 -5485.5682 -593.1463 40s/Msamples 530000 -6072.1313 -5487.8800 -584.2512 40s/Msamples 540000 -6059.5445 -5482.6141 -576.9303 40s/Msamples 550000 -6066.5060 -5469.3309 -597.1751 40s/Msamples 560000 -6071.9593 -5470.3688 -601.5904 40s/Msamples 570000 -6058.1156 -5460.8944 -597.2211 40s/Msamples 580000 -6068.6110 -5470.5900 -598.0209 40s/Msamples 590000 -6073.5252 -5471.2548 -602.2703 40s/Msamples 600000 -6075.3219 -5476.7424 -598.5794 40s/Msamples 610000 -6054.6226 -5467.0904 -587.5321 40s/Msamples 620000 -6085.1024 -5476.0329 -609.0695 40s/Msamples 630000 -6077.3674 -5492.2771 -585.0902 40s/Msamples 640000 -6072.0459 -5477.4711 -594.5748 40s/Msamples 650000 -6059.0015 -5475.7309 -583.2706 40s/Msamples 660000 -6074.1838 -5474.0207 -600.1630 40s/Msamples 670000 -6083.7754 -5475.4181 -608.3572 40s/Msamples 680000 -6067.5053 -5478.8992 -588.6060 40s/Msamples 690000 -6068.0928 -5489.1066 -578.9862 40s/Msamples 700000 -6064.0367 -5478.7686 -585.2680 40s/Msamples 710000 -6098.2752 -5499.6019 -598.6732 40s/Msamples 720000 -6058.6090 -5489.2982 -569.3107 40s/Msamples 730000 -6067.9142 -5477.8797 -590.0344 40s/Msamples 740000 -6089.8624 -5476.4172 -613.4451 40s/Msamples 750000 -6085.7816 -5476.5924 -609.1892 40s/Msamples 760000 -6055.3801 -5469.0777 -586.3024 40s/Msamples 770000 -6056.6020 -5481.1585 -575.4435 40s/Msamples 780000 -6075.2389 -5491.7792 -583.4596 40s/Msamples 790000 -6096.7155 -5499.3392 -597.3762 40s/Msamples 800000 -6090.5410 -5482.8733 -607.6677 40s/Msamples 810000 -6093.8530 -5478.6005 -615.2525 40s/Msamples 820000 -6088.8971 -5478.5929 -610.3041 40s/Msamples 830000 -6053.6229 -5476.3853 -577.2376 40s/Msamples 840000 -6077.5847 -5483.1840 -594.4006 40s/Msamples 850000 -6085.6071 -5489.1163 -596.4908 40s/Msamples 860000 -6078.3892 -5487.8032 -590.5859 40s/Msamples 870000 -6075.2215 -5479.3265 -595.8949 40s/Msamples 880000 -6068.7570 -5483.6545 -585.1025 40s/Msamples 890000 -6050.7734 -5476.9677 -573.8057 40s/Msamples 900000 -6074.1812 -5480.3332 -593.8480 40s/Msamples 910000 -6076.4841 -5481.4471 -595.0370 40s/Msamples 920000 -6071.6034 -5474.5693 -597.0340 40s/Msamples 930000 -6063.9045 -5483.5795 -580.3250 40s/Msamples 940000 -6090.0997 -5487.3912 -602.7085 40s/Msamples 950000 -6061.6251 -5476.9702 -584.6549 40s/Msamples 960000 -6084.1861 -5478.5617 -605.6243 40s/Msamples 970000 -6086.6654 -5493.9985 -592.6668 40s/Msamples 980000 -6053.6312 -5475.4396 -578.1916 40s/Msamples 990000 -6074.2887 -5479.0850 -595.2037 40s/Msamples 1000000 -6061.4821 -5480.6611 -580.8210 40s/Msamples Operator Tuning #accept #reject Pr(m) Pr(acc|m) AdaptableOperatorSampler(StrictClockRateScaler.c:clock) - 3409 14691 0.01797 0.18834 AdaptableOperatorSampler(strictClockUpDownOperator.c:clock) - 72 17875 0.01797 0.00401 AdaptableOperatorSampler(KappaScaler.s:RSV2_1) - 107 504 0.00060 0.17512 AdaptableOperatorSampler(FrequenciesExchanger.s:RSV2_1) - 247 983 0.00120 0.20081 beast.base.inference.operator.kernel.BactrianDeltaExchangeOperator(FixMeanMutationRatesOperator) 0.20734 6555 17595 0.02397 0.27143 AdaptableOperatorSampler(FrequenciesExchanger.s:RSV2_2) - 257 928 0.00120 0.21688 AdaptableOperatorSampler(KappaScaler.s:RSV2_2) - 158 434 0.00060 0.26689 AdaptableOperatorSampler(FrequenciesExchanger.s:RSV2_3) - 323 858 0.00120 0.27350 AdaptableOperatorSampler(KappaScaler.s:RSV2_3) - 101 485 0.00060 0.17235 EpochFlexOperator(CoalescentConstantBICEPSEpochTop.t:tree) 0.03374 4705 19543 0.02397 0.19404 EpochFlexOperator(CoalescentConstantBICEPSEpochAll.t:tree) 0.03538 4451 19420 0.02397 0.18646 TreeStretchOperator(CoalescentConstantBICEPSTreeFlex.t:tree) 0.02322 6056 18136 0.02397 0.25033 kernel.BactrianScaleOperator(CoalescentConstantTreeRootScaler.t:tree) 0.07369 6918 28840 0.03595 0.19347 kernel.BactrianNodeOperator(CoalescentConstantUniformOperator.t:tree) 2.28981 122186 237157 0.35950 0.34003 kernel.BactrianSubtreeSlide(CoalescentConstantSubtreeSlide.t:tree) 1.75417 27766 151901 0.17975 0.15454 Exchange(CoalescentConstantNarrow.t:tree) - 44685 134901 0.17975 0.24882 Exchange(CoalescentConstantWide.t:tree) - 81 35977 0.03595 0.00225 WilsonBalding(CoalescentConstantWilsonBalding.t:tree) - 240 35551 0.03595 0.00671 kernel.BactrianScaleOperator(PopSizeScaler.t:tree) 0.21351 9519 26386 0.03595 0.26512 Tuning: The value of the operator's tuning parameter, or '-' if the operator can't be optimized. #accept: The total number of times a proposal by this operator has been accepted. #reject: The total number of times a proposal by this operator has been rejected. Pr(m): The probability this operator is chosen in a step of the MCMC (i.e. the normalized weight). Pr(acc|m): The acceptance probability (#accept as a fraction of the total proposals for this operator). Total calculation time: 41.908 seconds End likelihood: -6061.482176048203