jModelTest2 on XSEDE2.1.6Statistical selection of best-fit models of nucleotide substitution, run on XSEDEDiego Darriba and David PosadaDarriba D, Taboada GL, Doallo R, and Posada D. (2012) jModelTest 2: more models, new heuristics and parallel computing. Nature Methods 9(8), 772. Phylogeny / Alignmentjmodeltest2_expanse_xsedejmodeltest2_invokeperl($set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar) <= 24perl""0jmodeltest2_invoke2perl($set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar) > 24 && $set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar < 56 perl""0jmodeltest2_invoke3perl($set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar) > 55 perl""0number_nodes2perl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar <= 24scheduler.confperl
"nodes=1\\n" .
"node_exclusive=0\\n" .
"mem=30G\\n" .
"cpus-per-task=16\\n" .
"threads_per_process=16\\n"
number_nodes22perl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar > 24 && $set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar < 56scheduler.confperl
"nodes=1\\n" .
"node_exclusive=0\\n" .
"mem=46G\\n" .
"cpus-per-task=24\\n" .
"threads_per_process=24\\n"
number_nodes32perl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar > 55scheduler.confperl
"nodes=1\\n" .
"node_exclusive=0\\n" .
"mem=61G\\n" .
"cpus-per-task=32\\n" .
"threads_per_process=32\\n"
infileInput Alignmentinfile.phyperl"-d infile.phy"1runtime1scheduler.confMaximum Hours to Run (up to 168 hours)0.5The maximum hours to run must be less than 168perl$runtime > 168.0The maximum hours to run must be greater than 0.05perl$runtime < 0.05perl"runhours=$value\\n"The job will run on 16 processors as configured. If it runs for the entire configured time, it will consume 16 x $runtime cpu hoursperl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar <= 24The job will run on 24 processors as configured. If it runs for the entire configured time, it will consume 24 x $runtime cpu hoursperl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar > 24 && $set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar < 56 The job will run on 32 processors as configured. If it runs for the entire configured time, it will consume 32 x $runtime cpu hoursperl$set_subschemes*$uneq_basefmodels*$invar_models*$include_ratevar > 55Estimate the maximum time your job will need to run. We recommend testing initially with a < 0.5hr test run because Jobs set for 0.5 h or less depedendably run immediately in the "debug" queue.
Once you are sure the configuration is correct, you then increase the time. The reason is that jobs > 0.5 h are submitted to the "normal" queue, where jobs configured for 1 or a few hours times may
run sooner than jobs configured for the full 168 hours.
name_outputSpecify the name of your output file (-o)perl!$convert_phylipperl(defined $value) ? "-o $value":""output.txt3name_suffixSpecify a suffix for your log file (-n)perl!$convert_phylipperl(defined $value) ? "-n $value":"" 4convert_phylipConvert input to Phylip format (only)perl($value) ? "-getPhylip":"" 02choose_modelsConfigure Model Searchperl!$convert_phylipinformation_criterionClustering search (-H)perl$set_subschemes eq "203"AICAICcBICperl"-H $value"BIC25This is used only with 203 searches. AIC=Akaike Information Criterion; AICc = corrected Akaike Information Criterion; BIC = Bayesian Information Criterionthreshold_heuristicPerform threshold heuristic search. (-G; default = 0.1)perl!$convert_phylipperl(defined $value) ? "-G $value":""13set_subschemesSet the number of substitution schemes (-s)perl!$convert_phylip35711203perl" -s $value"115perl!defined $set_subschemesThis flag sets the number of substitution schemes. 3 = JC/F81 K80/HKY SYM/GTR; 5 = JC/F81, K80/HKY, TrNef/TrN, TPM1/TPM1uf, SYM/GTR 7 = JC/F81, K80/HKY, TrNef/TrN, TPM1/TPM1uf, TIM1ef/TIM1, TVMef/TVM, SYM/GTR; 11 = all named models; 203 = All possible GTR submatricesuneq_basefmodelsInclude models with unequal base frequencies. (-f)perl!$convert_phylip121""2"-f"27Please specify whether or not to use the -f optionperl!defined $uneq_basefmodelsinvar_modelsInclude models with a proportion invariable sites. (-i)perl!$convert_phylip121""2"-i"2Please specify whether or not to include models with invariable sites (-i)perl!defined $invar_models8include_ratevarInclude models with rate variation among sites?122Please specify whether or not to include models with rate variationperl!defined $include_ratevarnumratecat_modelsInclude models with rate variation among sites, set number of categories (-g; default = 4)perl!$convert_phylipperl(defined $value) ? "-g $value":""49confidenceint_modelsConfidence interval for the model selection process (-c; default = 100)perl!$convert_phylipperl(defined $value) ? "-c $value":""18configure_treesearchDefine Tree Searchset_basetreeBase tree topology for likelihood calculations. (-t)perl!$convert_phylipfixedBIONJMLperl" -t $value"ML This option lets you choose the base tree topology for liklihood calculations. The choices are:
Fixed BIONJ: Fixed BIONJ topology from Jukes-Cantor model; Neighor Joining: Use Neighbor-Joining topology for each model; and
Maximum Likelihood: use the maximum liklihood topology for each model10def_topsearchSet tree topology search operation option for Maximum-Likelihood search (-S)perl!$convert_phylip && $set_basetree eq "ML" && !defined $user_fixedtreeNNISPRBESTBESTperl" -S $value"10by default, jModelTest uses Maximum-Likelihood topologies as the base trees for the
model optimization, and checks both Nearest Neighbour Interchange (fast)and Subtree Pruning and Regrafting (slower) algorithms for the topology search. This obtains
the most accurate results, but it is also the most time consuming operation. According to the size of
the input alignment, one can directly select one of the algorithms saving time in the computations.
As a general rule, for a small number of taxa NNI algorithm would work better, as well as SPR is
more suitable for a large number of taxa. The tree search operation can be set with “-S” argument
(e.g., -t ML -S NNI).user_fixedtreeSelect a User-defined fixed tree for likelihood calculations (-u)perl!$convert_phylipuserfixedtree.treperl"-u userfixedtree.tre"8selection_criteriaInformation Criteriacriteria_1Select Information Criterion (choose all needed)perl!$convert_phylip-AIC-AICc-BIC-DTperl(defined $value) ? "$value":""-AIC-AICc-BIC-DT10Please select at least one Information Criterion (all four is typical)perl!defined $criteria_1' 'confidence_selectionConfidence level for the hLRTs (-h; default is 0.01)perl!$convert_phylipperl(defined $value) ? "-h $value":""13parameter_importancesCalculate the parameter importances (-p)perl!$convert_phylipperl($value) ? "-p":""116modeland_importancesDo model averaging and parameter importances (-v)perl!$convert_phylipperl($value) ? "-v":""017print_paupPrint out the PAUP block (-w)perl!$convert_phylipperl($value) ? "-w":""1 You can append the PAUP block produced here if you want to load the selected model and associated estimates in PAUP>20estimate_modelavgEstimate model-averaged phylogeny for each active criterion (-a)perl!$convert_phylipperl($value) ? "-a":""119strict_consensusUse strict consensus type for model-averaged phylogeny (-z)perl!$convert_phylipperl($value) ? "-z":""014Default for this parameter is Majority Rulecalculate_deltaCalculate delta AIC,AICc,BIC against unconstrained likelihood. (-uLnL)perl!$convert_phylipperl($value) ? "-uLnL":""019hRLT_paramshRLT parametershierarchical_likelihoodPerform hierarchical likelihood ratio tests (-hLRT)perl!$convert_phylip && $set_subschemes ne "203" &&($set_basetree eq "fixed" || defined $user_fixedtree)perl($value) ? "-hLRT":""013The -hrlt option not available for the 203 subsitution scheme. It requires an uploaded user-defined topology, or a fixed BIONJ-JC tree.specify_hyporderSpecify the hypothesis order (-O; default ftvwxgp)perl$hierarchical_likelihoodperl(defined $value) ? "-O $value":""ftvwxgp14This option allows you to set the hypothesis order as a string of small case letters. The options are as follows:
f:frequencies; t:transition/transversion ratio; v: 2ti4tv for subst=3 or 2ti for subst¿3; w: 2tv; x: 4tv; g: gamma;
p: proportion of invariable sites.
backward_selectionBackward selection for the hLRT (-r)perl$hierarchical_likelihood perl($value) ? "-r":""013dynamical_likelhoodPerform dynamical likelihood ratio tests. (-dLRT)perl$hierarchical_likelihood perl($value) ? "-dLRT":""012all_results*