MrBayes on XSEDE3.2.7aTree Inference Using Bayesian Analysis - run on XSEDEJohn P. Huelsenbeck and Fred Ronquist
Huelsenbeck, J. P. and F. Ronquist. 2001. MRBAYES: Bayesian inference of phylogeny. Bioinformatics 17:754-755.
Ronquist, F. and J. P. Huelsenbeck. 2003. MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19:1572-1574. .
Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D.L., Darling, A., Höhna, S., Larget, B., Liu, L., Suchard, M.A., and Huelsenbeck, J.P. 2012 MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space
Syst Biol 61 (3): 539-542 doi:10.1093/sysbio/sys029
Phylogeny / Alignmentmrbayes_xsede_expansembmpi_326perl$run_version eq "6"perl""0mbmpi_327perl$run_version eq "7"perl""0mpi_processes_conf13scheduler.confperl$mrbayesblockquery && $run_version eq "6" && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"threads_per_process=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf1b3scheduler.confperl$mrbayesblockquery && $run_version eq "6" && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"threads_per_process=4\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf23scheduler.confperl$mrbayesblockquery && $run_version eq "7" && $set_beagle_params && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=2\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=2\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified * 0.5 . "\\n"
mpi_processes_conf2b3scheduler.confperl$mrbayesblockquery && $run_version eq "7" && $set_beagle_params && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=4\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=4\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf2c3scheduler.confperl$mrbayesblockquery && $run_version eq "7" && !$set_beagle_params && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=1\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf2d3scheduler.confperl$mrbayesblockquery && $run_version eq "7" && !$set_beagle_params && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=4\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf33scheduler.confperl!$mrbayesblockquery && $run_version eq "6" && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=1\\n" .
"mpi_processes=" . $nchainsval * $nrunsval . "\\n"
mpi_processes_conf3b3scheduler.confperl!$mrbayesblockquery && $run_version eq "6" && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"threads_per_process=4\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchainsval * $nrunsval . "\\n"
mpi_processes_conf43scheduler.confperl!$mrbayesblockquery && $run_version eq "7" && $set_beagle_params && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=2\\n" .
"threads_per_process=2\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchainsval * $nrunsval . "\\n"
mpi_processes_conf4b3scheduler.confperl!$mrbayesblockquery && $run_version eq "7" && $set_beagle_params && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=4\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"threads_per_process=4\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchainsval * $nrunsval . "\\n"
mpi_processes_conf4c3scheduler.confperl!$mrbayesblockquery && $run_version eq "7" && !$set_beagle_params && !$more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/128))) . "G\\n" .
"node_exclusive=0\\n" .
"threads_per_process=1\\n" .
"mpi_processes=" . $nchains_specified * $nruns_specified . "\\n"
mpi_processes_conf4d3scheduler.confperl!$mrbayesblockquery && $run_version eq "7" && !$set_beagle_params && $more_memoryperl "jobtype=mpi\\n" .
"cpus-per-task=1\\n" .
"mem=" . (int($nchains_specified * $nruns_specified*(248/32))) . "G\\n" .
"threads_per_process=4\\n" .
"node_exclusive=0\\n" .
"mpi_processes=" . $nchainsval * $nrunsval . "\\n"
infileInput File (must be in Nexus format) (-execute)paramfile.txtperl"execute infile.nex\\n"2infile.nexsetoptsparamfile.txtperl"set autoclose=yes\\n"1setwarnoptsparamfile.txtperl"set nowarnings=yes\\n"1mrbayes_closeoutperl"quit\\n"paramfile.txt99ALL_FILES*run_versionChoose the MB version you wish to run677mrbayesblockquery1My Data Contains a MrBayes Data Block (CHECK THIS OR MrBayes BLOCK ENTRIES WILL BE OVERWRITTEN!!!)perl($value)? "":""0Jobs that do not have a MrBayes block cannot be restarted. We encourage you to use a MrBayes block if possible.perl!$mrbayesblockqueryThis interface allows you to configure MrBayes from the command line, or from a MrBayes block in your data file.
However, you must choose one or the other. So, if you have a MrBayes Block in your data, you should configure the entire
run in that block (see the MrBayes manual for help on how to do this). It is our belief that MrBayes is sufficiently complex
in its command structure and use that if you want to analyse multiple partitions and multiple datatypes you should do it in
the Nexus file structure. The current interface supports multiple data partitions ONLY in the Nexus file. If you need more
options than we provide, please let us know: http://www.ngbw.org/ngbugz. Other options are not included in this interface
because they (and any complex MrBayes runs) are much better handled in the MrBayes block of your data file, are more useful
for interactive running, or are not appropriate for batch runs. These include: Ctype, Link, Unlink, Delete, Include,
Restore, Props, Plot, and Comparetree, the prset option Aarevmatpropts is not supported; the lset Ploidy option does not
seem to be working in MrBayes 3.1.2. Any parameters requiring printing to the screen are not supported for obvious reasons.
Importantly, unlike the command line version, it is not possible to upload a MrBayes block file that calls a separate data
file with your matrix.
nruns_specified1My MrBayes Block specifies nruns=scheduler.confperl$mrbayesblockquery2The values entered for nruns and nchains influence the number of cpu's that can be used in parallel. Please enter the value you specified for
nruns in the MrBayes block of the Nexus file. If you didn't specify a value for nruns, please leave this field at its default value of 2.
Please enter a value for nrunsperl!$nruns_specifiedThe value of nruns must be greater than 0perl$nruns_specified < 1nchains_specified1My MrBayes Block specifies nchains=scheduler.confperl$mrbayesblockquery4The value entered for nruns and nchains influences the number of cpu's that can be used in parallel. Enter the value you specified
for nchains in the MrBayes block of the nexus file. If you didn't specify a value for nchains, please leave this field at its default value of 4.
Please enter value for nchainsperl!$nchains_specifiedThe value of nchains must be greater than 0perl$nchains_specified < 1The value for nchains must be 1 or greater. The recommended value is at least 4.perl$nchains_specified < 1nruns x nchains must be less than or equal to 16.perl($nruns_specified * $nchains_specified > 16) nruns x nchains must be a multiple of 2perl((($nruns_specified * $nchains_specified) % 2) != 0)Version 3.2.7 is the development version, with an important bug fixed.perl$run_version eq "71"The job will run on 2 processors as configured. If it runs for the entire configured time, it will consume 2 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 2 && !$more_memoryThe job will run on 4 processors as configured. If it runs for the entire configured time, it will consume 4 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 4 && !$more_memoryThe job will run on 6 processors as configured. If it runs for the entire configured time, it will consume 6 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 6 && !$more_memoryThe job will run on 8 processors as configured. If it runs for the entire configured time, it will consume 8 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 8 && !$more_memoryThe job will run on 10 processors as configured. If it runs for the entire configured time, it will consume 10 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 10 && !$more_memoryThe job will run on 12 processors as configured. If it runs for the entire configured time, it will consume 12 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 12 && !$more_memoryThe job will run on 14 processors as configured. If it runs for the entire configured time, it will consume 14 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 14 && !$more_memoryThe job will run on 16 processors as configured. If it runs for the entire configured time, it will consume 16 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 16 && !$more_memoryThe job will run on 8 processors as configured. If it runs for the entire configured time, it will consume 8 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 2 && $more_memoryThe job will run on 16 processors as configured. If it runs for the entire configured time, it will consume 16 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 4 && $more_memoryThe job will run on 24 processors as configured. If it runs for the entire configured time, it will consume 24 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 6 && $more_memoryThe job will run on 32 processors as configured. If it runs for the entire configured time, it will consume 32 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 8 && $more_memoryThe job will run on 40 processors as configured. If it runs for the entire configured time, it will consume 40 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 10 && !$more_memoryThe job will run on 48 processors as configured. If it runs for the entire configured time, it will consume 48 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 12 && $more_memoryThe job will run on 52 processors as configured. If it runs for the entire configured time, it will consume 52 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 14 && $more_memoryThe job will run on 64 processors as configured. If it runs for the entire configured time, it will consume 64 x $runtime cpu hoursperl$mrbayesblockquery && $nchains_specified * $nruns_specified == 16 && $more_memoryThe job will run on 2 processors as configured. If it runs for the entire configured time, it will consume 2 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 2 && !$more_memoryThe job will run on 4 processors as configured. If it runs for the entire configured time, it will consume 4 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 4 && !$more_memoryThe job will run on 6 processors as configured. If it runs for the entire configured time, it will consume 6 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 6 && !$more_memoryThe job will run on 8 processors as configured. If it runs for the entire configured time, it will consume 8 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 8 && !$more_memoryThe job will run on 10 processors as configured. If it runs for the entire configured time, it will consume 10 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 10 && !$more_memoryThe job will run on 12 processors as configured. If it runs for the entire configured time, it will consume 12 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 12 && !$more_memoryThe job will run on 14 processors as configured. If it runs for the entire configured time, it will consume 14 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 14 && !$more_memoryThe job will run on 16 processors as configured. If it runs for the entire configured time, it will consume 16 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 16 && !$more_memoryThe job will run on 8 processors as configured. If it runs for the entire configured time, it will consume 8 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 2 && $more_memoryThe job will run on 16 processors as configured. If it runs for the entire configured time, it will consume 16 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 4 && $more_memoryThe job will run on 24 processors as configured. If it runs for the entire configured time, it will consume 24 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 6 && $more_memoryThe job will run on 32 processors as configured. If it runs for the entire configured time, it will consume 32 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 8 && $more_memoryThe job will run on 40 processors as configured. If it runs for the entire configured time, it will consume 40 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 10 && !$more_memoryThe job will run on 48 processors as configured. If it runs for the entire configured time, it will consume 48 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 12 && $more_memoryThe job will run on 52 processors as configured. If it runs for the entire configured time, it will consume 52 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 14 && $more_memoryThe job will run on 64 processors as configured. If it runs for the entire configured time, it will consume 64 x $runtime cpu hoursperl!$mrbayesblockquery && $nrunsval * $nchainsval == 16 && $more_memoryruntime1scheduler.confMaximum Hours to Run (click here for help setting this correctly)168The maximum hours to run must be less than 168perl$runtime > 168.0Please enter a positive number for the maximum runtimeperl$runtime < 0Please specify a maximum runtimeperl!defined $runtime perl"runhours=$value\\n"Estimate the maximum time your job will need to run. We recommend testing initially with a < 0.5hr test run because Jobs set for 0.5 h or less depedendably run immediately in the "debug" queue.
Once you are sure the configuration is correct, you then increase the time. The reason is that jobs > 0.5 h are submitted to the "normal" queue, where jobs configured for 1 or a few hours times may
run sooner than jobs configured for the full 168 hours.
zipfilename1scheduler.confperl"zipfilename=$value\\n"flagdatatypeMy Data Type Is (only one data type can be used through the web form, see help below)perl!$mrbayesblockquerydnadnaproteinstandardotherSetting this flag helps us eliminate uneeded optionsseedSet the Seed Number (set seed=)paramfile.txtperl!$mrbayesblockqueryperl(defined $value) ? "set seed=$value\\n":""1Sets the seed number for the random number generator. The random number seed is initialized haphazardly at the beginning of each MrBayes session. This option allows you to set the seed to some specific value, thereby allowing you to exactly repeat an analysis. If the analysis uses swapping between cold and heated chains, you must also set the swap seed (see below) to exactly repeat the analysis.
swapseedSet the Swapseed (set swapseed=)paramfile.txtperl!$mrbayesblockqueryperl(defined $value) ? "set swapseed=$value\\n":""1Sets the seed used for generating the swapping sequence when Metropolis-coupled heated chains are used. By default, this seed is generated at the beginning of each MrBayes session. This option allows you to set the seed to some specific value, thereby allowing you to exactly repeat a swap sequence.
more_memoryI need more memoryparamfile.txt01Write output in scientific notation (higher precision). Otherwise, use fixed format (easier for humans to read).
scientificUse scientific notationparamfile.txtperl!$mrbayesblockquery0perl(defined $value) ? "set scientific=Yes\\n":"set scientific=No\\n"1Write output in scientific notation (higher precision). Otherwise, use fixed format (easier for humans to read).
precisionHow many decimals should we print?paramfile.txtperl!$mrbayesblockquery15perl(defined $value) ? "set precision = $value\\n":""1Please set the precsion to a number between 3 and 15. 15 is the default.perl$value < 3Please set the precsion to a number between 3 and 15. 15 is the default.perl$value > 15Set the number of decimals to print your results in. Values of 3-15 are permitted.
set_beagle_paramsRun BEAGLEparamfile.txt1Disabling BEAGLE will slow your run by as much as 20%. You should only do this if a run with BEAGLE fails, or if you believe using BEAGLE gave you unexpected results.perl!$set_beagle_paramsWe have seen examples where MrBayes runs on BEAGLE can produce anomalous topologies. If you see an odd topology, please try the run without BEAGLEperl$set_beagle_paramsBeagle should speed up runs by about 10-20%. You should only disable this parameter if you have a problem using Beagle.set_beagle_params6paramfile.txtperl$set_beagle_params && $run_version == "6"perl"set usebeagle=yes beagleprecision=double beaglesse=yes beaglescaling=dynamic beaglethreads=no\\n"set_beagle_params7aparamfile.txtperl$set_beagle_params && $run_version == "7" && !$more_memoryperl"set usebeagle=yes beagleprecision=double beaglesse=yes beaglescaling=dynamic beaglethreads=2\\n"set_beagle_params7bparamfile.txtperl$set_beagle_params && $run_version == "7" && $more_memoryperl"set usebeagle=yes beagleprecision=double beaglesse=yes beaglescaling=dynamic beaglethreads=4\\n"set_nobeagle7paramfile.txtperl!$set_beagle_params && $run_version eq "7"perl"set usebeagle=no\\n"set_outgroupSpecify (only) one outgroupparamfile.txtperl!$mrbayesblockqueryperl(defined $value) ? "outgroup $value\\n":""3With this command, "outgroup 3" assigns the third taxon in the matrix to be the outgroup. Similarly, "outgroup Homo_sapiens" assings the taxon "Homo_sapiens" to be the outgroup (assuming that there is a taxon named "Homo_sapiens" in the matrix). Only a single taxon can be assigned to be the outgroup.
lsetoptsLikelihood Model ParametersnstoptsSet the number of substitution types (Nst=)perl!$mrbayesblockqueryparamfile.txtperl"lset Nst= $value\\n"1126mixed5Sets the number of substitution types: "1" constrains all of the rates to be the same (e.g., a JC69 or F81 model); "2" allows transitions and transversions to have potentially different rates (e.g., a K80 or HKY85 model); "6" allows all rates to be different, subject to the constraint of time-reversibility (e.g., a GTR model).
nucmodeloptsSet the nucleotide substitution model (Nucmodel=)paramfile.txtperl!$mrbayesblockqueryperl"lset Nucmodel= $value\\n"4by44by4doubletcodonprotein5This parameter specifies the general form of the nucleotide substitution model. The options are "4by4" [the standard model of DNA substitution in which there are only four states (A,C,G,T/U)], "doublet" (a model appropriate for modelling the stem regions of ribosomal genes where the state space is the 16 doublets of nucleotides), and "codon" (the substitution model is expanded around triplets of nucleotides--a codon).codonoptsSet the Codon translation table (Codon=)paramfile.txtperl"lset Code= $value\\n"perl$nucmodelopts eq "codon" && !$mrbayesblockqueryuniversaluniversalvertmtmycoplasmaciliatesmetmtyeast5omegavaroptsAllow the nonsynonymous/synonymous rate ratio (omega) (Omegavar=)paramfile.txtperl!$mrbayesblockquery && $nucmodelopts eq "codon"perl"lset omegavar= $value\\n"equalequalNy98M35Allows the nonsynonymous/synonymous rate ratio (omega) to vary across codons. Ny98 assumes that there are three classes, with potentially different omega values (omega1, omega2, omega3): omega2 = 1; omega1 is less than 1 but greater than 0; and omega3 is greater than 1. Like the Ny98 model, the M3 model has three omega classes. However, their values are less constrained, with omega1 less than omega2, which is less than omega3. The default (omegavar = equal) has no variation on omega across sites.ploidyoptsSet the ploidy (Ploidy=)perl"Ploidy= $value\\n"perl$brlenspropts eq "clock:coalescence"DiploidDiploidHaploidzlinked5This option is used when a coalescence prior is used on trees.
rateoptsSet the model for among-site rate variation (Rates=)paramfile.txtperl!$mrbayesblockqueryperl"lset Rates= $value\\n"equalequalgammaadgammapropinvinvgamma5In general, the rate at a site is considered to be an unknown random variable. Valid options are: equal:No rate variation across sites; gamma: The rate at a site is drawn from a gamma distribution. The gamma distribution has a single parameter that describes how much rates vary; adgamma: Autocorrelated rates across sites. The marginal rate distribution is gamma, but adjacent sites have correlated rates; propinv -- A proportion of the sites are invariable; invgamma -- A proportion of the sites are invariable while the rate for the remaining sites are drawn from a gamma distribution.Note that MrBayes versions 2.0 and earlier supported options that allowed site specific rates (e.g., ssgamma). In versions 3.0 and later, site specific rates are allowed, but set using the 'prset ratepr' command for each partition.
NgammacatoptsSet number of rate categories for gamma distribution (Ngammacat=)paramfile.txtperl!$mrbayesblockquery && $rateopts eq "gamma"perl"lset Ngammacat= $value\\n"45The Ngammacat parameter sets the number of rate categories for the gamma distribution. The gamma distribution is continuous. However, it is virtually impossible to calculate likelihoods under the continuous gamma distribution. Hence, an approximation to the continuous gamma is used; the gamma distribution is broken into ncat categories of equal weight (1/ncat). The mean rate for each category represents the rate for the entire cateogry. This option allows you to specify how many rate categories to use when approximating the gamma. The approximation is better as ncat is increased. In practice, "ncat=4" does a reasonable job of approximating the continuous gamma.
NbetacatoptsSet number of rate categories for beta distribution (Nbetacat=)paramfile.txtperl!$mrbayesblockqueryperl"lset Nbetacat= $value\\n"55A symmetric beta distribution is used to model the stationary frequencies when morphological data are used. This option specifies how well the beta distribution will be approximated.CovarionoptsForce the use of covarion-like model (4X4 dna model, or protein) (Covarion=)paramfile.txtperl!$mrbayesblockqueryperl($value)? "lset Covarion = Yes\\n":""05This forces the use of a covarion-like model of substitution for nucleotide or amino acid data (it is not used for other data types).The valid options are "yes" and "no". The covarion model allows the rate at a site to change over its evolutionary history. Specifically, the site is either on or off. When it is off, no substitutions are possible. When the process is on, substitutions occur according to a specified substitution model (specified using the other lset options).
codingoptsSpecify how characters were sampled (Coding=)paramfile.txtperl!$mrbayesblockqueryperl"lset coding = $value\\n"allallvariablenoabsencenopresence5The Coding parameter specifies how characters were sampled. If all site patterns had the possibility of being sampled, then "all" should be specified (the default). Otherwise "variable" (only var iable characters had the possibility of being sampled), "noabsence" (characters for which all taxa were coded as absent were not sampled), and "nopresence" (characters for which all taxa were coded as present were not sampled. "All" works for all data types. However, the others only work for morphological (all/variable) or restriction site (all/variable/noabsence/nopresence) data. ParsmodeloptsForce calculation under a Parsimony model (Parmodel=)paramfile.txtperl!$mrbayesblockquery0perl($value)? "lset parsmodel = Yes\\n":""5This forces calculation under the so-called parsimony model described by Tuffley and Steel (1998). The options are "yes" or "no". Note that the biological assumptions of this model are anything but parsimonious. In fact, this model assumes many more parameters than the next most complicated model implemented in this program. If you really believe that the parsimony model makes the biological assumptions described by Tuffley and Steel, then the parsimony method is miss-named.prsetparamsConfigure PriorstratiooptsTransition/Transversion Rate Ratio; DNA only (Tratiopr=)paramfile.txtperl!$mrbayesblockquery && $flagdatatype eq "dna" betabetafixedbeta"prset Tratiopr = beta($betameanx, $betavary)\\n"fixed"preset Tratiopr = fixed($tratiofixed)\\n"10Tratiopr changes the prior probability of the transition/transversion ratio. It can be fixed (fixed), or set to a beta distribution with mean x and variance y (beta(x,y)).The program assumes that the transition and transversion rates are independent gamma-distributed random variables with the same scale parameter when beta is selected. If you want a diffuse prior that puts equal emphasis on transition/transversion rate ratios above 1.0 and below 1.0, then use a flat Beta, beta(1,1), which is the default. If you wish to concentrate this distribution more in the equal-rates region, then use a prior of the type beta(x,x), where the magnitude of x determines how much the prior is concentrated in the equal rates region. For instance, a beta(20,20) puts more probability on rate ratios close to 1.0 than a beta(1,1). If you think it is likely that the transition/transversion rate ratio is 2.0, you can use a prior of the type beta(2x,x), where x determines how strongly the prior is concentrated on tratio values near 2.0. For instance, a beta(2,1) is much more diffuse than a beta(80,40) but both have the expected tratio 2.0 in the absence of data. The parameters of the Beta can be interpreted as counts: if you have observed x transitions and y transversions, then a beta(x+1,y+1) is a good representation of this information. The fixed option allows you to fix the tratio to a particular value.betameanxBeta mean xperl!$mrbayesblockquery && $tratioopts eq "beta"perl""1.010betavaryBeta variance yperl""perl!$mrbayesblockquery && $tratioopts eq "beta"1.010tratiofixedFixed Transition/Transversion Ratioperl""perl!$mrbayesblockquery && $tratioopts eq "fixed"1.010revmatproptsSubstitution Rates of the GTR Model; Nucleic Data only (Revmatpr=)paramfile.txtperl!$mrbayesblockquery && $flagdatatype eq "dna" dirichletdirichletfixeddirichlet"prset revmatpr = dirichlet($atocrate,$atograte,$atotrate,$ctograte,$ctotrate,$gtotrate)\\n"fixed"prset revmatpr = fixed($fixedatocrate,$fixedatograte,$fixedatotrate,$fixedctograte,$fixedctotrate,$fixedgtotrat)\\n"10
Revmatpr sets the prior for the substitution rates of the GTR model for nucleotide data. For Revmatpr=dirichlet, MrBayes assumes that the six substitution rates are independent gamma-distributed random variables with the same scale parameter. The six numbers in brackets each corresponds to a particular substitution type. Together, they determine the shape of the prior. The six rates are in the order A / C, A / G, A / T, C / G, C / T, and G / T. By default, dirichlet(1,1,1,1,1,1) is used, also referred to as a 'flat' Dirichlet. For a prior where the C / T rate is 5 times and the A / G rate 2 times higher, on average, than the transversion rates, which are all the same, then you should use a prior of the form dirichlet(x,2x,x,x,5x,x), where x determines how much the prior is focused on these particular rates. For more information, see Tratiopr. The fixed option allows you to fix the substitution rates to particular values.
atocrateA/C rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010atograteA/G rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010atotrateA/T rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010ctograteC/G rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010ctotrateC/T rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010gtotrateG/T Rateperl""perl!$mrbayesblockquery && $revmatpropts eq "dirichlet"1.010fixedatocrateA/C rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010fixedatograteA/G rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010fixedatotrateA/T rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010fixedctograteC/G rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010fixedctotrateC/T rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010fixedgtotrateG/T Rateperl""perl!$mrbayesblockquery && $revmatpropts eq "fixed"1.010aamodelproptsSet the Rate Matrix for Amino Acids (Aamodelpr=)paramfile.txtperl!$mrbayesblockqueryperl("$value" ne "$vdef")? "prset aamodelpr=$value\\n" : ""fixed(poisson)fixed(blosum)fixed(cprev)fixed(dayhoff)fixed(equalin)fixed(gtr)fixed(jones)mixedfixed(mtmam)fixed(mtrev)fixed(poisson)fixed(rtrev)fixed(vt)fixed(wag)fixed(lg)10Aamodelpr sets the rate matrix for amino acid data.You choose a single fixed model, or choose mixed to average over the ten models by specifying "mixed".
In the latter case, the Markov chain will sample each model according to its probability. The sampled model is reported as an index: poisson(0), jones(1), dayhoff(2), mtrev(3), mtmam(4), wag(5), rtrev(6), cprev(7), vt(8), or blosum(9). The 'Sump' command summarizes the MCMC samples and calculates the posterior probability estimate for each of these models.
omegaproptsNonsynonymous/Synonymous Rate Ratio (Omegapr=)paramfile.txtperl!$mrbayesblockquery && $omegavaropts eq "equal" && $nucmodelopts eq "codon" uniformuniformexponentialfixeduniform"prset omegapr = uniform($omegaprdir1,$omegaprdir2)\\n"exponential"prset omegapr = exponential($omegaprexponential)\\n"fixed"prset omegapr = fixed($omegafixed)\\n"10This parameter specifies the prior on the nonsynonymous/synonymous rate ratio. The options are:uniform, exponential, and fixed.
This parameter is used only when the nucleotide substitution model is set to codon, and there is no variation in omega across sites (i.e. omegavar=equal").
omegaprdir1Uniform Omega Rate1perl""perl!$mrbayesblockquery && $omegapropts eq "uniform"1.010omegaprdir2Uniform Omega Rate2perl!$mrbayesblockquery && $omegapropts eq "uniform"perl""1.010omegaprexponentialExponential Omega Rateperl!$mrbayesblockquery && $omegapropts eq "exponential"perl""1.010omegafixedFixed Omega Rateperl""perl!$mrbayesblockquery && $omegapropts eq "fixed"1.010ny98omega1proptsNonsynonymous/Synonymous Rate Ratio for sites under purifying selection (Ny98omega1pr=)paramfile.txtperl!$mrbayesblockquery && $omegavaropts eq "Ny98"betabetafixedbeta"prset Ny98omega1pr = beta($ny98omega1prbeta1,$ny98omega1prbeta2)\\n"fixed"prset Ny98omega1pr = fixed($ny98omega1prfix1)\\n"10This parameter is only in effect if the nucleotide substitution model is set to "codon" and where omega varies across sites using the model of Nielsen and Yang (1998) (i.e., Ny98). If fixing the parameter, you must specify a number between 0 and 1.
ny98omega1prbeta1Ny98omega1 Beta Rate 1perl""perl!$mrbayesblockquery && $ny98omega1propts eq "beta"1.010ny98omega1prbeta2Ny98omega1 Beta Rate 2perl""perl!$mrbayesblockquery && $ny98omega1propts eq "beta"1.010ny98omega1prfix1Fixed Ny98Omega1 Rateperl!$mrbayesblockquery && $ny98omega1propts eq "fixed"perl""1.010ny98omega3proptsNonsynonymous/Synonymous Rate Ratio for sites under positive selection (Ny98omega3pr=)paramfile.txtperl!$mrbayesblockquery && $omegavaropts eq "Ny98"perl""exponentialuniformexponentialfixeduniform"prset Ny98omega3pr = uniform($ny98omega3pruni1,$ny98omega3pruni2)\\n"exponential"prset Ny98omega3pr = exponential($ny98omega3prexp1)\\n"fixed"prset ny98omega3pr = fixed($ny98omega3prfix1)\\n"10This parameter specifies the prior on the nonsynonymous/synonymous rate ratio for positively selected sites. The options are:uniform, exponential, and fixed. This parameter is only in effect if the nucleotide substitution model is set to codon and where omega varies across sites according to the NY98 model.
ny98omega3pruni1Ny98 Uniform Omega Rate 1 for Positive Selectionperl""The value entered must be greater than or equal to 1perl$ny98omega3pruni1 < 1perl!$mrbayesblockquery && $ny98omega3propts eq "uniform"1.010ny98omega3pruni2Ny98 Uniform Omega Rate 2 for Positive Selectionperl""The value entered must be greater than or equal to 1perl$ny98omega3pruni2 < 1perl!$mrbayesblockquery && $ny98omega3propts eq "uniform"1.010ny98omega3prexp1Ny98 Exponential Omega Rate for Positive Selection10perl!$mrbayesblockquery && $ny98omega3propts eq "exponential"1.0perl""The value entered must be greater than or equal to 1perl$ny98omega3prexp1 < 1ny98omega3prfix1Ny98 Fixed Omega Rate for Positive Selectionperl""perl!$mrbayesblockquery && $ny98omega3pr eq "fixed"1.010M3omega3proptsNonsynonymous/Synonymous Rate Ratio for sites under the M3 model (M3omega1pr=)paramfile.txtperl!$mrbayesblockquery && $omegavaropts eq "M3"perl""exponentialexponentialfixedexponential"prset M3omega3pr = exponential \\n"fixed"prset M3omega3pr = fixed($M3omega3prfix1,$M3omega3prfix2,$M3omega3prfix3)\\n"10This parameter specifies the prior on the nonsynonymous/synonymous rate ratio for positively selected sites. The options are:uniform, exponential, and fixed. This parameter is only in effect if the nucleotide substitution model is set to codon and where omega varies across sites according to the NY98 model.
M3omega3prfix1M3 Fixed Omega Rate 1 for M3 Modelperl""perl!$mrbayesblockquery && $M3omega3pr eq "fixed"1.010M3omega3prfix2M3 Fixed Omega Rate 2 for M3 Modelperl""perl!$mrbayesblockquery && $M3omega3pr eq "fixed"1.010M3omega3prfix3M3 Fixed Omega Rate 3 for M3 Modelperl""perl!$mrbayesblockquery && $M3omega3pr eq "fixed"1.010codoncatfreqsoptsFrequencies of sites under Purifying, Neutral, and Positive Selection (Codoncatfreqs=)paramfile.txtperl$omegavaropts eq "Ny98" || $omegavaropts eq "M3"perl""dirichletdirichletfixeddirichlet"prset Codoncatfreqs = dirichlet($codoncatfreqsdir1,$codoncatfreqsdir2,$codoncatfreqsdir3)\\n"fixed"prset Codoncatfreqs = fixed($codoncatfreqsfix1,$codoncatfreqsfix2,$codoncatfreqsfix3)\\n"10Codoncatfreqs specifies the prior on frequencies of sites under purifying, neutral, and positive selection. The options are dirichlet and fixed. This parameter is relevant if the nucleotide substitution model is set to "codon" and where omega varies across sites using the models of Nielsen and Yang (1998), or Yang et al. (2000) i.e. Omegavar=Ny98 or M3. Note that the sum of the three frequencies must be 1.
codoncatfreqsdir1Codoncatfreqs Dirichlet Parameter 1perl!$mrbayesblockquery && $codoncatfreqsopts eq "dirichlet"perl""1.010codoncatfreqsdir2Codoncatfreqs Dirichlet Parameter 2perl!$mrbayesblockquery && $codoncatfreqsopts eq "dirichlet"perl""1.010codoncatfreqsdir3Codoncatfreqs Dirichlet Parameter 3perl""perl!$mrbayesblockquery && $codoncatfreqsopts eq "dirichlet"1.010codoncatfreqsfix1Codoncatfreqs Fixed Parameter 1perl!$mrbayesblockquery && $codoncatfreqsopts eq "fixed"10perl""codoncatfreqsfix2Codoncatfreqs Fixed Parameter 2perl!$mrbayesblockquery && $codoncatfreqsopts eq "fixed"perl""10codoncatfreqsfix3Codoncatfreqs Fixed Parameter 3perl!$mrbayesblockquery && $codoncatfreqsopts eq "fixed"10perl""statewfreqproptsState Frequencies (Statefreqpr=); Assigning frequencies to each state is not supportedperl!$mrbayesblockqueryparamfile.txtdirichletdirichletfixed(equal)fixed(empirical)dirichlet"prset statefreqpr = dirichlet($statewfreqprdir1)\\n"fixed (equal)"prset statefreqpr = fixed(equal)\\n"fixed (empirical)"prset statefreqpr = fixed(empirical)\\n"10This parameter specifies the prior on the state frequencies. The options are dirichlet, fixed, with equal frequencies, and fixed with empirically determined frequencies.
If you specify a single number, then the prior has all states equally probable with a variance related to the single parameter passed.
statewfreqprdir1Statefreqs Dirichlet Parameter (A single number)perl!$mrbayesblockquery && $statewfreqpropts eq "dirichlet"1.010shapeproptsGamma Shape Parameter (Shapepr=)perl!$mrbayesblockqueryparamfile.txtuniformuniformexponentialfixeddirichlet"prset shapepr = uniform($shapepruni1,$shapepruni2)\\n"exponential"prset shapepr = exponential($shapeprexp1)\\n"fixed"prset shapepr = fixed($shapeprfix1)\\n"10This parameter specifies the prior on the state frequencies. The options are dirichlet, fixed, with equal frequencies, and fixed with emirically determined frequencies.
The dirichlet prior has all states equally probable with a variance related to the single parameter passed in.
shapepruni1Gamma Shape Uniform Parameter 1perl""perl!$mrbayesblockquery && $shapepropts eq "uniform"0.010shapeprdir2Gamma Shape Dirichlet Parameter 2perl""perl!$mrbayesblockquery && $shapepropts eq "uniform"50.010shapeprexp1Gamma Shape Exponential Parameterperl""perl!$mrbayesblockquery && $shapepropts eq "exponential"1.010shapeprfix1Gamma Shape Fixed Parameterperl""perl!$mrbayesblockquery && $shapepropts eq "fixed"1.010pinvarproptsProportion of Invariable Sites (Pinvarpr=)perl!$mrbayesblockqueryparamfile.txtuniformuniformfixeduniform"prset pinvarpr = uniform($pinvarpruni1,$pinvarpruni2)\\n"fixed"prset pinvarpr = fixed($pinvarprfix1)\\n"10This parameter specifies the prior for the proportion of invariable sites. The options are uniform and fixed. The valid range for the parameters is between 0 and 1.
pinvarpruni1Invariable Sites, Uniform Parameter 1perl!$mrbayesblockquery && $pinvarpropts eq "uniform"perl""0.010pinvarpruni2Invariable Sites, Uniform Parameter 2perl!$mrbayesblockquery && $pinvarpropts eq "uniform"perl""1.010pinvarprfix1Invariable Sites, Fixed Parameterperl!$mrbayesblockquery && $pinvarpropts eq "fixed"perl""1.010ratecorrproptsAutocorrelation Parameter for Gamma Distribution for Among SIte Variation (Ratecorrpr=)paramfile.txtperl!$mrbayesblockquery && $flagdatatype eq "dna" uniformuniformfixeduniform"prset ratecorrpr = uniform($ratecorrpruni1,$ratecorrpruni2)\\n"fixed"prset ratecorrpr = fixed($ratecorrprfix1)\\n"10This parameter specifies the prior for the autocorrelation parameter of the autocorrelated gamma distribution for among-site rate variation. The options are uniform and fixed
The parameter for uniform is between -1 and 1. The default setting is uniform, (-1, 1).
ratecorrpruni1Autocorrelation Uniform Parameter 1perl""perl!$mrbayesblockquery && $ratecorrpropts eq "uniform"-1.010ratecorrpruni2Autocorrelation Uniform Parameter 2perl""perl!$mrbayesblockquery && $ratecorrpropts eq "uniform"1.010ratecorrprfix1Autocorrelation Fixed Parameterperl!$mrbayesblockquery && $ratecorrpropts eq "fixed"perl""1.010covswitchproptsCovrion Switching Rates (Covswitchpr=)perl!$mrbayesblockqueryparamfile.txtuniformuniformexponentialfixeduniform"prset covswitchpr = uniform($covswitchuni1,$covswitchuni2)\\n"exponential"prset covswitchpr = exponential($covswitchexp1)\\n"fixed"prset covswitchpr = fixed($covswitchfix1,covswitchfix2)\\n"10This option sets the prior for the covarion switching rates. The options are uniform, exponential, and fixed, The covarion model has two rates: a rate from on to off
and a rate from off to on. The rates are assumed to have independent priors that individually are either uniformly or exponentially distributed. The other option is to fix the switching rates, in which case you must specify both rates. (The first number is off to on and the second is on to off; the first should always be less than the second).
covswitchuni1Covarion Model Off to On Rate (Uniform)perl!$mrbayesblockquery && $covswitchpropts eq "uniform"perl""0.010covswitchuni2Covarion Model On to Off Rate (Uniform)perl!$mrbayesblockquery && $covswitchpropts eq "uniform"perl""100.010covswitchexp1Covarion Model Exponential Parameterperl""perl!$mrbayesblockquery && $covswitchpropts eq "exponential"1.010covswitchfix1Covarion Model Off to On Rate (Fixed)perl""perl!$mrbayesblockquery && $covswitchpropts eq "fixed"1.010covswitchfix2Covarion Model On to Off Rate (Fixed)perl""perl!$mrbayesblockquery && $covswitchpropts eq "fixed"1.010symdirihyperproptsStationary frequencies for states in standard data sets (Symdirihyperpr=)perl!$mrbayesblockqueryparamfile.txtfixed(infinity)uniformexponentialfixedfixed(infinity)uniform"prset symdirihyperpr = uniform($symdiruni1,$symdiruni2)\\n"exponential"prset symdirihyperpr = exponential($symdirexp1)\\n"fixed"prset symdirihyperpr = fixed($symdirfix1)\\n"fixed (infinity)"prset symdirihyperpr = fixed(infinity)\\n"10Symdirihyperpr sets the prior for the stationary frequencies of the states for morphological (standard) data. There can be as many as 10 states for standard data. However, the labelling of the states is somewhat arbitrary. For example, the state "1" for different characters does not have the same meaning. This is not true for DNA characters, for example, where a "G" has the same meaning across characters. The fact that the labelling of morphological characters is arbitrary makes it difficult to allow unequal character state frequencies. MrBayes gets around this problem by assuming that the states have a dirichlet prior, with all states having equal frequency. The variation in the dirichlet can be controlled by this parameter--symdirihyperpr.Symdirihyperpr specifies the distribution on the variance parameter of the dirichlet. Valid options are uniform, exponential, fixed with an explicit rate value, and fixed(infinity). "Fixed(infinity)" fixes the dirichlet prior such that all character states have equal frequency.
symdiruni1Stationary Frequency Uniform Param 1perl""perl!$mrbayesblockquery && $symdirihyperpropts eq "uniform"1.010symdiruni2Stationary Frequency Uniform Param 2perl""perl!$mrbayesblockquery && $symdirihyperpropts eq "uniform"1.010symdirexp1Stationary Frequency Exponential Param 1perl""perl!$mrbayesblockquery && $symdirihyperpropts eq "exponential"1.010symdirfix1Stationary Frequency Fixed Param 1perl""perl!$mrbayesblockquery && $symdirihyperpropts eq "fixed"1.010topologyproptsSpecify Topological Constraint Types (Topologypr=)paramfile.txtperl!$mrbayesblockquery && $noconstraints >= 1uniformuniformspeciestreeconstraintsuniform"prset topologypr = uniform\\n"constraints"prset topologypr = constraints($constraintnames)\\n"10This parameter specifies the prior probabilities of phylogenies.
The options are uniform constraints If the prior is selected to be "uniform" all possible trees are considered
a priori equally probable. The constraints option allows you to specify complicated prior
probabilities on trees (constraints are discussed more fully in "help constraint").
Note that you must specify a list of constraints that you wish to be obeyed.
The list can be either the constraint's number or its name. Also, note that the
constraints simply tell you how much more (or less) probable individual trees are that possess
the constraint than trees not possessing the constraint.
constraintnames1Enter the names or numbers of the constraints to be used, separated by commasperl!$mrbayesblockquery && $topologypropts eq "constraints"perl""10brlensproptsProbability distribution on branch lengths (Brlenspr=)perl!$mrbayesblockqueryparamfile.txtunconstrained:exponentialunconstrained:uniformunconstrained:exponentialclock:uniformclock:birthdeathclock:coalescenceunconstrained:uniform"prset brlenspr = unconstrained:uniform(0,$brlenspruni2)\\n"unconstrained:exponential"prset brlenspr = unconstrained:exponential($brlensprexp1)\\n"clock:uniform"prset brlenspr = clock:uniform\\n"clock:birthdeath"prset brlenspr = clock:birthdeath\\n"clock:coalescence"prset brlenspr = clock:coalescence\\n"10Brlenspr specifies the prior probability distribution on branch lengths. The options are unconstrained:uniform, unconstrained:exponential, clock:uniform, clock:birthdeath, clock:coalescence. Trees with unconstrained branch lengths are unrooted whereas clock-constrained trees are rooted. The option after the colon specifies the details of the probability density of branch lengths. If you choose a birth-death or coalescence prior, you may want to modify the details of the parameters of those processes.
brlenspruni1Unconstrained Uniform Param 1 is set at 0perl!$mrbayesblockquery && $brlenspropts eq "uniform"brlenspruni2Unconstrained Uniform Param 2perl""perl!$mrbayesblockquery && $brlenspropts eq "uniform"1.010brlensprexp1Unconstrained Exponential Paramperl""perl!$mrbayesblockquery && $brlenspropts eq "unconstrained:exponential"10.010treeheightproptsDistribution on Tree Height (for Clock Models) (Treeagepr=)perl!$mrbayesblockquery && $brlenspropts eq "clock:uniform" paramfile.txtexponentialgammaexponentialfixedgamma"prset treeagepr = gamma($treeheightsprgamma1,$treeheightsprgamma2)\\n"exponential"prset treeagepr = exponential($treeheightsprexp1)\\n"fixed"prset treeagepr = fixed($treeheightsprfx1)\\n"10Treeagepr specifies the prior probability distribution on the tree height, when a clock model is specified. The options are gamma and exponential. (And, yes, we know the exponential is a special case of the gamma distribution.) The tree height is the expected number of substitutions on a single branch that extends from the root of the tree to the tips. This parameter does not come into play for the coalescence prior. It insures that the prior probability distribution for unconstrained and birth-death models is proper.
treeheightsprgamma1Gamma Param 1perl""perl!$mrbayesblockquery && $treeheightpropts eq "gamma"1.010treeheightsprgamma2Unconstrained Uniform Param 2perl!$mrbayesblockquery && $treeheightpropts eq "gamma"perl""1.010treeheightsprexp1Unconstrained Exponential Paramperl!$mrbayesblockquery && $treeheightpropts eq "exponential"perl""1.010treeheightsprfx1Treeagepr Fixed Paramperl!$mrbayesblockquery && $treeheightpropts eq "exponential"perl""1.010rateproptsSite Specific Rates Models (Ratepr=)paramfile.txtperl!$mrbayesblockqueryfixedfixedvariablefixed"prset ratepr = fixed\\n"variable"prset ratepr = variable\\n"10Ratepr specifies the site specific rates model. First, you must have defined a partition of the characters. For example, you may define a partition that divides the characters by codon position, if you have DNA data. Second, you must make that partition the active one using the set command. For example, if your partition is called "by_codon", then you make that the active partition using "set partition=by_codon". Now that you have defined and activated a partition, you can specify the rate multipliers for the various partitions. The options are fixed, variable, and dirichlet. For "fixed" the rate multiplier for that partition is set to 1 (i.e., the rate is fixed to the average rate across partitions). On the other hand, for "variable", the rate is allowed to vary across partitions subject to the constraint that the average rate of substitution across the partitions is 1. You must specify a variable rate prior for at least twopartitions, otherwise the option is not activated when calculating likelihoods. The variable option automatically associates the partition rates with a dirichlet(1,...,1) prior. The dirichlet option is an alternative way of setting a partition rate to be variable, and also gives accurate control of the shape of the prior. The parameters of the Dirichlet are listed in the order of the partitions that the ratepr is applied to. For instance, "prset applyto=(1,3,4)ratepr = dirichlet(10,40,15)" would set the Dirichlet parameter 10 to partition 1, 40 to partition 3, and 15 to partition 4.
speciationproptsSpeciation Rate (for Birth:Death Clock Models) (Speciationpr=)paramfile.txtperl!$mrbayesblockquery && $brlenspropts eq "clock:birthdeath"uniformuniformexponentialfixeduniform"prset speciationpr = uniform($speciationpruni1,$speciationpruni2)\\n"exponential"prset speciationpr = exponential($speciationprexp1)\\n"fixed"prset speciationpr = fixed($speciationprfix1)\\n"10Speciationpr sets the prior on the speciation rate. The options are uniform, exponential, and fixed. This parameter is only relevant if the birth-death process is selected as the prior on branch lengths.
speciationpruni1Speciationpr Uniform Param 1perl""perl!$mrbayesblockquery && $speciationpropts eq "uniform"0.010speciationpruni2Speciationpr Uniform Param 2perl!$mrbayesblockquery && $speciationpropts eq "uniform"perl""10.010speciationprexp1Speciationpr Exponential Paramperl""perl!$mrbayesblockquery && $speciationpropts eq "exponential"1.010speciationprfix1Speciationpr Fixed Paramperl""perl!$mrbayesblockquery && $speciationpropts eq "fixed"1.010extinctionproptsExtinction Rate (for Birth:Death Clock Models) (Extinctionpr=)paramfile.txtperl!$mrbayesblockquery && $brlenspropts eq "clock:birthdeath"betabetafixedbeta"prset extinctionpr = beta($extinctionpruni1,$extinctionpruni2)\\n"fixed"prset extinctionpr = fixed($extinctionprfix1)\\n"10Extinctionpr sets the prior on the extinction rate. Valid options are uniform, exponential, and fixed.This parameter is only relevant if the birth-death process is selected as the prior on branch lengths.
extinctionpruni1Extinctionpr Beta Param 1perl""perl !$mrbayesblockquery && $extinctionpropts eq "beta"1.010extinctionpruni2Extinctionpr Beta Param 2perl!$mrbayesblockquery && $extinctionpropts eq "beta"perl""1.010extinctionprfix1Extinctionpr Fixed Paramperl""perl!$mrbayesblockquery && $extinctionpropts eq "fixed"1.010sampleproboptsFraction of Species Samples in Birth Death Analysis (SampleprobExtinctionpr=)paramfile.txtperl!$mrbayesblockquery && $brlenspropts eq "clock:birthdeath"perl"prset sampleprob = $value\\n"1.010Sampleprob sets the fraction of species that are sampled in the analysis. This is used with the birth death prior on trees (see Yang and Rannala, 1997).
thetaproptsPrior on the coalescence parameter (nucleic acid data) (Thetapr=)paramfile.txtperl!$mrbayesblockquery && $brlenspropts eq "clock:coalescence"uniformuniformexponentialfixeduniform"prset thetapr = uniform($thetapruni1,$thetapruni2)\\n"exponential"prset thetapr = exponential($thetaprexp1)\\n"fixed"prset thetapr = fixed($thetaprfix1)\\n"10Thetapr sets the prior on the coalescence parameter. This parameter is only relevant if the coalescence process is selected as the prior on branch lengths.
thetapruni1Thetapr Uniform Param 1perl""perl!$mrbayesblockquery && $extinctionpropts eq "uniform"0.010thetapruni2Thetapr Uniform Param 2perl!$mrbayesblockquery && $extinctionpropts eq "uniform"perl""10.010thetaprexp1Thetapr Exponential Paramperl""perl!$mrbayesblockquery && $thetapropts eq "exponential"1.010thetaprfix1Thetapr Fixed Paramperl""perl!$mrbayesblockquery && $thetapropts eq "fixed"1.010datamodificationsData Specificationsdatabreaksoptsparamfile.txtSpecify Breaks in Sequence Data (Protein and Nucleic Acid Data only)perl!$mrbayesblockqueryperl"databreaks $value"20The Databreaks command is used to specify breaks in the input data matrix. Some of the models (e.g. autocorrelated gamma model) implemented by MrBayes account for nonindependence at adjacent characters. Databreaks option specifies that two sites that are adjacent in the matrix, are actually separated by many kilobases or megabases in the genome. For example, say you have a data matrix of 3204 characters that include nucleotide data from three genes that are physically unlinked. The first gene covers characters 1 to 970, the second gene covers characters 971 to 2567, and the third gene covers characters 2568 to 3204. Just enter the last number of the contiuous sequnce, in this case, 970 and 2567, separated by spaces.
pairsoptsSpecify nucleotide pairs involved in Watson-Crick pairing (pairs nucmodel=doublet only)paramfile.txtperl!$mrbayesblockquery && $nucmodelopts eq "doublet"perl"pairs $value\\n"20The Pairs command is used to specify pairs of nucleotides. For example, RNA sequences with a known secondary structure of stems and loops. Substitutions in nucleotides involved in a Watson-Crick pairing in stems are not strictly independent; a change in one changes the probability of a change in the partner. A solution to this problem is to expand the model around the pair of nucleotides in the stem. Pairs allows you to do this. The correct usage is to enter the numbers of a base-pairforming nucleotide pair, separated by a semicolon: for example:30:56. To include multiplepairs, separate the enteredvalues by commas: 31:55, 32:54, 33:53, 34:52, 35:51, 36:50. This specifies pairings between nucleotides 30 and 56, 31 and 55, etc. Onlynucleotide data (DNA or RNA) may be paired using this command. Note that in order for the program to actually implement a "doublet" model involving a 16 X 16 rate matrix, you must specify that the structure of
the model is 16 X 16 using "lset nucmodel=doublet".
CharsetCharacter Setsperl!$mrbayesblockquerynocharsetsHow many character sets would you like to define? See the note below.perl!$mrbayesblockqueryparamfile.txtperl""012345678030You can specify up to 8 character sets here. You can experiment here, but if you get serious, you should really do this in the MrBayes Command block of a Nexus file. For more information see the help section below.charset1Name for character set 1paramfile.txtperl!$mrbayesblockquery && $nocharsets >= 1perl""30Charset defines a character set. You must specify the name of the charset you wish to create, and the first and last positions of that set. Both parameters are entered into the forms
provided, for up to 8 charsets. The character set name is entered in the first box; it cannot have any spaces in it. The character range is entered second, you enter the first character position, and last characterer position, separated by a hyphen. You can use "." to indicate the last character. In addition, the forward slash (\) can be used to tell the program to assign every third (or second, or fifth, or whatever) character to the character set. For example, "charset first_pos = 1-720\3" defines a character set called "first_pos" that includes every third site from 1 to 720.
charset1rangeCharacter set 1 rangeperl!$mrbayesblockquery && $nocharsets >= 1paramfile.txtperl(defined $value )? " charset $charset1 = $value\\n": ""30charset2Name for character set 2paramfile.txtperl!$mrbayesblockquery && $nocharsets >= 2perl""30charset2rangeCharacter set 2 rangeperl!$mrbayesblockquery && $nocharsets >= 2paramfile.txtperl(defined $value )? " charset $charset2 = $value\\n" : ""30charset3Name for character set 3paramfile.txtperl!$mrbayesblockquery && $nocharsets >= 3perl""30charset3rangeCharacter set 3 rangeperl!$mrbayesblockquery && $nocharsets >= 3paramfile.txtperl(defined $value )? " charset $charset3 = $value\\n" : ""30charset4Name for character set 4paramfile.txtperl!$mrbayesblockquery && $nocharsets >= 4perl""30charset4rangeCharacter set 4 rangeperl!$mrbayesblockquery && $nocharsets >= 4paramfile.txtperl(defined $value )? " charset $charset4 = $value\\n" : ""30charset5Name for character set 5perl!$mrbayesblockquery && $nocharsets >= 5perl""30charset5rangeCharacter set 5 rangeperl!$mrbayesblockquery && $nocharsets >= 5paramfile.txtperl(defined $value )? " charset $charset5 = $value\\n" : ""30charset6Name for character set 6perl!$mrbayesblockquery && $nocharsets >= 6perl""30charset6rangeCharacter set 6 rangeperl!$mrbayesblockquery && $nocharsets >= 6paramfile.txtperl(defined $value )? " charset $charset6 = $value\\n" : ""30charset7Name for character set 7perl!$mrbayesblockquery && $nocharsets >= 7perl""30charset7rangeCharacter set 7 rangeperl!$mrbayesblockquery && $nocharsets >= 7paramfile.txtperl(defined $value )? " charset $charset7 = $value\\n" : ""30charset8Name for character set 8perl!$mrbayesblockquery && $nocharsets >= 8perl""30charset8rangeCharacter set 8 rangeperl!$mrbayesblockquery && $nocharsets >= 8paramfile.txtperl(defined $value )? " charset $charset8 = $value\\n" : ""30excludeoptsExclude these characters from the analysis perl!$mrbayesblockqueryparamfile.txtperl"exclude $value\\n"30Exclude removes specific character positions from the analysis. Enter one of the following into the form provided : a set of individual character position numbers separated by spaces (2, 3, 10, 11, 12, 13, 14, and 22); a range of numbers, by giving the starting and finishing position, separated by a hyphen ( 1-100 ). Note the backslash can be used to exclude every nth character (1-100\3), the name of a character set, or "all". A mixture is also allowed (2 3 10-14 22).
mcmcparamsParameters for MCMCngenvalNumber of Generations (Ngen=)perl!$mrbayesblockqueryparamfile.txtperl"mcmc ngen=$value filename=infile.nex nruns=$nrunsval nchains=$nchainsval temp=$tempval swapfreq=$swapfreqval nswaps=$nswapsval samplefreq=$samplefreqval $mcmcdiagnval minpartfreq=$minpartfreqval $allchainsval $relburninval burnin=$burninval burninfrac=$burninfracval $stopruleval $startingtreeval stopval=$stopval $sbrlensval nperts=$npertsval $ordertaxaval\\n"5000The number of samples you requested is greater than 50,000; this may cause your .t output file to exceed the allowed limit of 500 GB. Please consider editing your input file to request a lower sample frequency.perl$ngenval > 50000 * $samplefreqvalPlease enter a value for ngen of at least 5000 generationsperl$ngenval < 500050Ngen sets the number of cycles for the MCMC algorithm. This should be a big number as you want the chain to first reach stasis, and then remain there for enough time to take lots of samples.
nrunsvalNumber of Runs (nruns=)perl!$mrbayesblockqueryparamfile.txtperl" "250Nruns sets the number of independent analyses started simultaneously. Only values of 2 and 4 are permitted.
Please enter a value for nruns (default = 2)perl!$mrbayesblockquery && !defined $nrunsval Please enter a value greater than 0 for nruns (default = 2)perl!$mrbayesblockquery && $nrunsval < 1 nchainsvalNumber of Chains to Run (nchains=)perl!$mrbayesblockqueryparamfile.txtperl""450 Nchains specifies how many chains are run for each analysis for the MCMCMC variant. The default is 4: 1 cold chain and 3 heated chains. If Nchains is set to 1, MrBayes will use regular MCMC sampling, without heating.
The value of nchains must 1 or greater. The default (recommended) is 4.perl$nchainsval < 1nruns x nchains must be a multiple of 2perl((($nrunsval * $nchainsval) % 2) != 0)nruns x nchains must be less than or equal to 24.perl($nrunsval * $nchainsval > 24) Please enter a value for nchains= (default = 4)perl!defined $nchainsvaltempvalTemperature parameter (temp=)perl!$mrbayesblockqueryparamfile.txtperl" "0.20050Temp is the temperature parameter for heating the chains. The higher the temperature, the more likely the heated chains are tomove between isolated peaks in the posterior distribution. However, excessive heating may lead to very low acceptance rates for swaps between different chains. Before changing the default setting, however, note that the acceptance rates of swaps tend to fluctuate during the burn-in phase of the run.
swapfreqvalHow often should swap of states be attemptedperl!$mrbayesblockqueryperl""1Swapfreq specifies how often swaps of states between chains are attempted. You must be running at least two chains for this option to be relevant. The default is Swapfreq=1, resulting in Nswaps (see below) swaps being tried each generation of the run. If Swapfreq is set to 10, then Nswaps swaps will be tried every tenth generation of the run.
nswapsvalHow many swaps should be tried per generationperl!$mrbayesblockqueryperl""1Nswaps sets the number of swaps tried for each swapping generation of the chain (see also Swapfreq).
samplefreqvalHow often should the Markov chain be sampled?perl!$mrbayesblockqueryparamfile.txtperl""100050Samplefreq specifies how often the Markov chain is sampled. You can sample the chain every cycle, but this results in very large output files. Thinning the chain is a way of making these files smaller and making the samples more independent.
mcmcdiagnvalWrite acceptance ratios of moves and swaps to file?perl!$mrbayesblockquerymcmcdiagn=Yesmcmcdiagn=Yesmcmcdiagn=NoMcmcdiagn determines whether acceptance ratios of moves and swaps will be printed to file. The file will be named similarly to the .p' and '.t' files, but will have the ending '.mcmc'. If more than one independent analysis is run simultaneously (see Nruns below), convergence diagnostics for tree topology will also be printed to this file. The convergence diagnostic used is the average standard deviation in partition frequency values across independent analyses. The Burnin setting (see below) determines how many samples will be discarded as burnin before calculating the partition frequencies. The Minpartfreq setting (see below) determines the minimum partition frequency required for a partition to be included in the calculation. As the independent analyses approach stationarity (converge), the value of the diagnostic is expected to approach zero.
minpartfreqvalMinimum frequency for a partition to be included (minpartfreq)perl!$mrbayesblockqueryparamfile.txtperl""0.150Minpartfreq sets the minimum frequency required for a partition to be included in the calculation of the topology convergence diagnostic. The partition is included if the minimum frequency is reached in at least one of the independent tree samples that are compared.
allchainsvalparamfile.txtRecord acceptance ratios for all chains?perl!$mrbayesblockqueryallchains=Noallchains=Yesallchains=NoAllchains: when set to YES, acceptance ratios for moves are recorded for all chains, cold or heated. By default, only the acceptance ratios for the cold chain are recorded.
relburninvalDiscard a proportion of the sampled values as burnin when calculating the convergence diagnostic?perl!$mrbayesblockqueryperl""relburnin=Yesrelburnin=Yesrelburnin=No Relburnin: If set to YES, a proportion of the sampled values will be discarded as burnin when calculating the convergence diagnostic. The proportion to be discarded is set with Burninfrac. By default, the Relburnin option is set to NO, resulting in a specific number of samples being discarded instead. This number is set by Burnin (see below).
burninfracvalSpecify the fraction of the sampled values discarded as burninparamfile.txtperl!$mrbayesblockquery && $relburninval eq "relburnin=Yes"perl""0.25BurninFrac specifies fraction of samples that will be discarded when convergence diagnostics are calculated. The value of this option is only relevant when Relburnin is set to YES. Example: A value for this option of 0.25 means that 25 percent of the samples will be discarded.
burninvalSpecify the number of sampled values discarded as burninparamfile.txtperl!$mrbayesblockquery && $relburninval eq "relburnin=No"perl""050Burnin specifies the number of samples (not generations) that will be discarded when convergence diagnostics are calculated. The value of this option is only relevant when Relburnin is set to NO.
stoprulevalStop early if the convergence diagnostic falls below the stop value?perl!$mrbayesblockquery && $mcmcdiagnval eq "mcmcdiagn=Yes" && $nrunsval > 1stoprule=Yesstoprule=Yesstoprule=NoStoprule: if set to NO, then the chain is run the number of generations determined by Ngen. If it is set to YES, and topological convergence diagnostics are calculated (Mcmcdiagn is set to YES), then the chain will be stopped before the pre-determined number of generations if the convergence diagnostic falls below the stop value.
stopvalPlease enter the stop valueparamfile.txtperl!$mrbayesblockquery && $mcmcdiagnval eq "mcmcdiagn=Yes" && $nrunsval > 1 perl""0.01Please enter a value for the stopvalueperl$stopruleval eq "stoprule=Yes" && !defined $stopval50Stopval: the critical value for the topological convergence diagnostic. Only used when Stoprule and Mcmcdiagn are set to yes, and more than one analysis is run simultaneously (Nruns greater than 1).
startingtreevalperl!$mrbayesblockquery && $Usertreeselparamfile.txtperl""starttree=random50Startingtree specifies whether the starting tree for the chain is randomly selected or user-defined. It might be a good idea to start from randomly chosen trees; convergence seems likely if independently run chains, each of which started from different random trees, converge to the same answer.
npertsvalNumber of random perturbations to apply to user starting tree.perl!$mrbayesblockquery && $startingtreeval eq "startingtree=user"perl""0Nperts is the number of random perturbations to apply to the user starting tree. This allows you to have something between completely random and user-defined trees start the chain.
sbrlensvalSave branch length information?perl!$mrbayesblockqueryparamfile.txtSavebrlens=YesSavebrlens=YesSavebrlens=No50ordertaxavalShould taxa be ordered before trees are printed to file?perl!$mrbayesblockqueryparamfile.txtOrdertaxa=YesOrdertaxa=YesOrdertaxa=Noperl""50Ordertaxa determines whether taxa should be ordered before trees are printed to file. If set to 'Yes', terminals in the sampled trees will be reordered to match the order of the taxa in thedata matrix as closely as possible. By default, trees will be printed without reordering of taxa.
outputoptsOutput/Reporting OptionssumtintroReport parameters Report allows you to control how the posterior distribution is reported. For rate parameters, it allows you to choose among several popular parameterizations. The report command also allows you to request printing of some model aspects that are usually not reported. For instance, if a node is constrained in the analysis, MrBayes can print the probabilities of the ancestral states at that node. Similarly, if there is rate variation in the model, MrBayes can print the inferred site rates, and if there is omega variation, MrBayes can print the inferred omega (positive selection) values foreach codon. In a complex model with several partitions, each partition is controlled separately using the same 'Applyto' mechanism as in the 'Lset' and 'Prset' commands.
Options:
Applyto allows you to apply the report commands to specific partitions. This command should be the first in the list of commands specified in 'report'.
For example, report applyto=(1,2) tratio=ratio
report applyto=(3) tratio=dirichlet
would result in the transition and transversion rates of the first and second partitions in the model being reported as a ratio and the transition and transversion rates of the third partition being reported as proportions of the rate sum (the Dirichlet parameterization).
Tratio -- This specifies the report format for the transition and transversion rates of a nucleotide substitution model with nst=2. If 'ratio' is selected, the rates will be reported as a ratio (transition rate/transversion rate). If 'dirichlet' is selected, the transition and transversion rates will instead be reported as proportions of the rate sum. For example, if the transition rate is three times the transversion rate and 'ratio' is selected, this will reported as a single value, '3.0'. If 'dirichlet' is selected instead, the same rates will be reported using two values, '0.75 0.25'. The sum of the Dirichlet values is always 1. Although the Dirichlet format may be unfamiliar to some users, it is more convenient for specifying priors than the ratio format.
Revmat -- This specifies the report format for the substitution rates of a GTR substitution model for nucleotide or amino acid data. If 'ratio' is selected, the rates will be reported scaled to the G-T rate (for nucleotides) or the Y-V rate (for amino acids). If 'dirichlet' is specified instead, the rates are reported as proportions of the rate sum. For instance, assume that the C-T rate is twice the A-G rate and four times the transversion rates, which are equal. If the report format is set to 'ratio', this would be reported as '1.0 2.0 1.0 1.0 4.0 1.0' since the rates are reported in the order rAC, rAG, rAT, rCG, rCT, rGT and scaled relative to the last rate, the G-T rate. If 'dirichlet' is selected instead, the same rates would have been reported as '0.1 0.2 0.1 0.1 0.4 0.1' since the rates are now scaled so that they sumto 1.0. The Dirichlet format is the parameterization used for formulating priors on the rates.
Ratemult -- This specifies the report format used for the rate multiplier of different model partitions. Three formats are available. If 'scaled' is selected, then rates are scaled such that the mean rate per site across partitions is 1.0. If 'ratio' is chosen, the rates are scaled relative to the rate of the first partition. Finally, if 'dirichlet' is chosen, the rates are given as proportions of the rate sum. The latter is the format used when formulating priors on the rate multiplier.
Ancstates -- If this option is set to 'yes', MrBayes will print the probability of the ancestral states at all constrained nodes. Typically, you are interested in the ancestral states of only a few characters and only at one node in the tree. To perform such an analysis, first define and enforce a topology constraint using 'constraint' and 'prset topologypr = constraints (...)'.Then put the character(s) of interest in a separate partition and set MrBayes to report the ancestral states for that partition. For instance, if the characters of interest are in partition 2, use 'report applyto=(2) ancstates=yes' to force MrBayes to print the probability of the ancestral states of those characters at the constrained node to the '.p' file.
Siterates If this option is set to 'yes' and the relevant model has rate variation across sites, the mean site rate in the posterior will be reported for each site to the '.p' file.
Possel If this option is set to 'yes' and the relevant model has omega variation across sites, the mean omega value for each model site (codon in this case) will be written to the '.p' file.
tratiovalReport format for the transition and transversion rates of a nucleotide substitution model with nst=2paramfile.txtratioperl!$mrbayesblockquery && $nstopts == 2perl"report tratio=$value\\n"ratiodirichlet45revmatoptsReport format for substitution rates of a GTR substitution model for nucleotide or amino acid dataperl!$mrbayesblockqueryparamfile.txtdirichletperl"report revmat=$value\\n"ratiodirichlet45reportancstateoptsReport the probability of ancestral states at all constrained nodesparamfile.txt0perl!$mrbayesblockquery && $topologypropts eq "constraint"perl($value)? "report Ancstates=Yes\\n":"report Ancstates=No\\n"45reportsiterateoptsReport mean site rate in the posteriorperl!$mrbayesblockqueryparamfile.txt0perl($value)? "report Siterates=Yes\\n":"report Siterates=No\\n"45reportposseloptsWrite Mean Omega Valuesparamfile.txt0perl!$mrbayesblockquery && $nucmodelopts eq "codon"perl($value)? "report possel=Yes\\n":"report possel=No\\n"45sumtintroSet Sumt parameters Sumt command is used to produce summary statistics for trees sampled during a Bayesian MCMC analysis. You can either summarize trees from one individual analysis, or trees coming from several independent analyses. In either case, all the sampled trees are read in and the proportion of the time any single taxon bipartition is found is counted. The proportion of the time that the bipartition is found is an approximation of the posterior probability of the bipartition. (A taxon bipartition is defined by removing a branch on the tree, dividing the tree into those taxa to the left and right of the removed branch.) The branchlength of the bipartition is also recorded, if branch lengths have been saved to file. The result is a list of taxon bipartitions, the frequency with which they were found, the posterior probability of the bipartition and the mean and variance of the lengthof the branch (if bl's were recorded).
The partition information is output to a file with the suffix ".parts" and a consensus tree is also printed to a file with the suffix ".con". The consensus tree is either a 50 percent majority rule tree or a majority rule tree showing all compatible partitions. If branch lengths have been recorded during the run, the ".con" file will contain a consensus tree with branch lengths and interior nodes labelled with support values. This tree can be viewed in a program such as TreeView. Finally, MrBayes produces a file with the ending ".trprobs" that contains a list of all the trees that were found during the MCMC analysis, sorted by their probabilities. This list of trees can be used to construct a credible set of trees. For example, if you want to construct a 95 percent credible set of trees, you include all of those trees whose cumulated probability is less than or equal to 0.95. If you are analyzing a large set of taxa, you may actually want to skip the calculation of tree probabilities entirely by setting "Calctreeprobs" to NO.
When calculating summary statistics you probably want to skip those trees that were sampled in the initial part of the run, the so-called burn-in period. The number of skipped samples is controlled by the "burnin" setting. The default is 0 but you typically want to override this setting. If you are summarizing the trees sampled in several independent analyses, such as those resulting from setting the "Nruns" option of the "Mcmc" command to a value larger than 1, MrBayes will also calculate convergence diagnostics for the sampled topologies and branch lengths. These values can help you determine whether it is likely that your chains have converged.
The "Sumt" command expands the "Filename" according to the current values of the "Nruns" and "Ntrees" options. For instance, if both "Nruns" and "Ntrees" are set to 1, "Sumt" will try to open a file named "Filename.t". If "Nruns" is set to 2 and "Ntrees" to 1, then "Sumt" will open two files, Filename.run1.t and Filename.run2.t, etc. By default, the "Filename" option will be set such that "Sumt" automatically summarizes all the results from your immediately preceding "Mcmc" command. You can also use the "Sumt" command to summarize tree samples inolder analyses. If you want to do that, remember to first read in a matrix so that MrBayes knows what taxon names to expect in the trees. Then set the "Nruns", "Ntrees" and "Filename" options appropriately.
Options:
Burnin -- Determines the number of samples that will be discarded from the input file before calculating summary statistics. If there are several input files, the same number of sampleswill be discarded from each. Note that the burnin is set separately for the 'sumt', 'sump', and 'mcmc' commands.
Ntrees -- Determines how many trees there are in the sampled model. If 'Ntrees' is greater then 1 then the names of the files are derived from 'Filename' by adding '.tree1.t', '.tree2.t', etc. If Nruns=1 and Ntrees=1 (see below), then only '.t' is added to 'Filename'.
Displaygeq -- The minimum probability of partitions to display.
Contype -- Type of consensus tree. 'Halfcompat' results in a 50 majority rule tree, 'Allcompat' adds all compatible groups to such a tree.
Calctreeprobs -- Determines whether tree probabilities should be calculated.
sumtburninSumt Burnin Valueperl!$mrbayesblockqueryparamfile.txt10perl"sumt burnin=$value relburnin=$sumt_relburnin burninfrac=$sumt_burninfrac nruns=$sumtnruns ntrees=$sumtntrees minpartfreq=$sumtdisplaygeq $sumtcontype conformat=$sumt_conformat\\n"Please enter a sumt burnin value of 10 or moreperl$value < 1070sumt_relburninDiscard a specified proportion of samples instead of a specific number(Relburnin=Yes)perl!$mrbayesblockqueryparamfile.txtYesYesNoperl""60 Specify the fraction of samples to be discarded.
sumt_burninfracSpecify the fraction of samples to be discarded (Burninfrac=)perl!$mrbayesblockquery && $sumt_relburnin eq "Yes"paramfile.txt0.25perl""60 Specify the fraction of samples to be discarded.
sumtnrunsHow many .t files should be summarized (Sumt nruns=)perl!$mrbayesblockqueryparamfile.txt2perl""70Sumt Nruns Determines how many '.t' files from independent analyses will be summarized. If Nruns > 1 then the names of the files are derived from 'Filename' by adding '.run1.t', '.run2.t', etc. If Nruns=1 and Ntrees=1 (see below), then only '.t' is added to 'Filename'.
sumtntreesHow many trees should be in the Sumt modelperl!$mrbayesblockqueryparamfile.txt1perl""70Sumt Ntrees determines how many trees there are in the sampled model. If 'Ntrees' > 1 then the names of the files are derived from 'Filename' by adding '.tree1.t', '.tree2.t', etc. If there are both multiple trees and multiple runs, the filenames will be 'Filename.tree1.run1.t', 'Filename.tree1.run2.t', etc.sumtdisplaygeqMinimum probability of partitions to display in Sumt (0.05 = 95%)perl!$mrbayesblockqueryparamfile.txt0.05perl""70sumtcontypeType of consensus treeparamfile.txtcontype=Halfcompatperl""70perl!$mrbayesblockquerycontype=Halfcompatcontype=AllcompatContype sets the type of consensus tree. The choices are 50 per cent majority rule tree, and one where all compatible groups are added to the tree.sumt_conformatChoose the output format for your consensus tree (Conformat=)perl!$mrbayesblockqueryparamfile.txtFigtreeFigtreeSimpleperl""60 Figtree format is rich and can be read by the program Figtree. Simple format can be read by many programs
sumtshowtreeprobsShow Tree Probabilitiesperl!$mrbayesblockqueryparamfile.txtshowtreeprobs=Noshowtreeprobs=Yesshowtreeprobs=Noperl""70sumpintroSet Sump parametersSump specifies how information is summarized, and written to a parameter file. During MCMC analysis, MrBayes prints the sampled parameter values to a tab delimited text file. By default, the name of the parameter file is assumed to be the name of the last matrix-containing nexus file, but with a '.p' extension. You can set 'Sump' to summarize the information in any other parameter file by setting the 'filename' option to the appropriate file name. The 'Sump' command does not require a matrix to be read in first. When you invoke the 'Sump' command, three items are output (1) a generation plot of the likelihood values; (2) estimates of the marginal likelihood of the model; and (3) a table with the mean, variance, and 95 percent credible interval for the sampled parameters. Each of these items can be switched on or off using the options 'Plot', 'Marglike', and 'Table'. By default, all three items are output but only to the screen. If output to a file is also desired, set 'Printtofile' to 'Yes'. The name of the output file is specified by setting the 'Outputname' option. When a new matrix is read in or when the 'Mcmc' output filename or 'Sump' input filename is changed, the 'Sump' outputname is changed as well. If you want to output to another file than the default, make sure you specify the outputname every time you invoke 'Sump'. If the specified outputfile already exists, you will
be prompted about whether you like to overwrite it or append to it. When you run several independent analyses simultaneously in MrBayes, the 'Nruns' and 'Filename' options are automatically set such that 'Sump' will summarize all the resulting output files.
Default settings: Burnin:0; Nruns:1; Filename:temp.p.p; Printtofile:No; Outputname:temp.p.stat; Plot:Yes; Marglike:Yes; Table:Yes
sumpburninSump Burnin Valueperl!$mrbayesblockqueryparamfile.txt10perl"sump burnin=$value relburnin=$sump_relburnin burninfrac=$sump_burninfrac nruns=$sumpnruns outputname=sumpoutput.out $sumpplot $sumpmarglike $sumptable\\n"Please enter a sump burnin value of 10 or moreperl$value < 1060Burnin determines the number of samples that will be discarded from the input file before calculating summary statistics. If there are several input files, the same number of samples will be discarded from each.sump_relburninDiscard a specified proportion of samples instead of a specific number(Relburnin=Yes)perl!$mrbayesblockqueryparamfile.txtYesYesNoperl""60 Specify the fraction of samples to be discarded.
sump_burninfracSpecify the fraction of samples to be discarded (Burninfrac=)perl!$mrbayesblockquery && $sump_relburnin eq "Yes"paramfile.txt0.25perl""60 Specify the fraction of samples to be discarded.
sumpnrunsHow many '.p' files from independent analyses will be summarized (sump Nruns=)perl!$mrbayesblockqueryparamfile.txt2perl""60Sump nruns determines how many '.p' files from independent analyses that will be summarized. If Nruns > 1 then the names of the files are derived from 'Filename' by adding '.run1.p', '.run2.p', etc. If Nruns=1, then the single file name is obtained by adding '.p' to 'Filename'.