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TraitRELAX_template.bpp
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# Global variables:
verbose = 1
# ----------------------------------------------------------------------------------------
# Input character file
# ----------------------------------------------------------------------------------------
input.character.file = <path_to_character_data_file>
input.character.format = Fasta # here, state the format of the character trait data
# ----------------------------------------------------------------------------------------
# Input alignment file
# ----------------------------------------------------------------------------------------
alphabet=Codon(letter=DNA)
genetic_code=Standard
input.sequence.file = <path_to_codon_sequence_alignment>
input.sequence.format = Fasta # here, state the format of the codon sequence alignment
input.sequence.sites_to_use = all
input.sequence.max_gap_allowed = 100%
input.sequence.remove_stop_codons = yes
# ----------------------------------------------------------------------------------------
# Input tree file
# ----------------------------------------------------------------------------------------
init.tree = user
input.tree.file = <path_to_tree_in_nwk_format>
input.tree.format = Newick # here, state the format of the tree file
init.brlen.method = Input
# ----------------------------------------------------------------------------------------
# Character Model specification
# ----------------------------------------------------------------------------------------
character_model.set_initial_parameters = true # here, use 'true' to customize the initial parameters for the character model
character_model.mu = 8.0
character_model.pi0 = 0.5
character.use_analytic_mapping = 1 # 1 for usage of the analytic approximation of trait history (recommended)
# ----------------------------------------------------------------------------------------
# Sequence Model specification
# ----------------------------------------------------------------------------------------
sequence_model.set_initial_parameters = true # here, use 'true' to customize the initial parameters for the sequence model
model1 = RELAX(kappa=2,p=0.001,omega1=1,omega2=2,theta1=0.5,theta2=0.8,frequencies=F3X4,1_Full.theta=0.5,1_Full.theta1=0.5,1_Full.theta2=0.5,2_Full.theta=0.5,2_Full.theta1=0.5,2_Full.theta2=0.5,3_Full.theta=0.5,3_Full.theta1=0.5,3_Full.theta2=0.5,k=1)
model2 = RELAX(kappa=RELAX.kappa_1,p=RELAX.p_1,omega1=RELAX.omega1_1,omega2=RELAX.omega2_1,theta1=RELAX.theta1_1,theta2=RELAX.theta2_1,frequencies=F3X4,1_Full.theta=RELAX.1_Full.theta_1,1_Full.theta1=RELAX.1_Full.theta1_1,1_Full.theta2=RELAX.1_Full.theta2_1,2_Full.theta=RELAX.2_Full.theta_1,2_Full.theta1=RELAX.2_Full.theta1_1,2_Full.theta2=RELAX.2_Full.theta2_1,3_Full.theta=RELAX.3_Full.theta_1,3_Full.theta1=RELAX.3_Full.theta1_1,3_Full.theta2=RELAX.3_Full.theta2_1,k=1)
likelihood.computation.approach = 3 # the order of likelihood computation approaches corresponds to the discussion in the manuscript: 1 (Random effects, which is currently not impleemnted), 2 (PAML's approach), 3 (Fixed effect)
# ----------------------------------------------------------------------------------------
# Optimization parameters
# ----------------------------------------------------------------------------------------
optimization.tolerance = 0.000001
optimization.max_number_f_eval = 10000
optimization = FullD(derivatives=Newton,nstep=10)
optimization.final = powell
optimization.ignore_parameters = RELAX.k_1,BrLen # removing the BrLen argument will result in branches lengths optimization with respect to the sequence model
optimization.advanced = 1 # 1 for advanced optimization procedure with sequential iterations with decreasing starting points to increase changes of convergence into global maxima (recommended)
optimization.scale.tree = 0 # 1 to optimize the tree scale with respect to the sequence model, 0 to leave as is
# ----------------------------------------------------------------------------------------
# Output files
# ----------------------------------------------------------------------------------------
output.estimates = <path_to_parameter_estimatess_output_file> # set to 'none' if not required
optimization.profiler = <path_to_optimization_steps_output_file> # set to 'none' if not required
output.infos = <path_to_log_likelihood_scores_by_sequence_sites> # set to 'none' if not required
joint.likelihood.debug = <bool> # set to 'true' for getting the strcuture of the expected and stochasting trait mappings as output
output.debug.dir = <path_to_mappings> # the directory to which the respective mappings will be written
output.tree.format = Newick # the format in which the mappings will be written (the newick format corresponds to the input format
# of labeled trees given as partitions to RELAX)
# ----------------------------------------------------------------------------------------
# Statistical test
# ----------------------------------------------------------------------------------------
statisical.test = <test_type> # can be either "traditional LRT" or "parametric boostrap"
# in the case of parametric boostrap, only the null simulations will be generated
# the user will execute TraitRELAX on the simulations independently,
# and may parse their results to obtain a test result using the script ./utils/parametricBootstrapParser.py
# for additional documentation, use "python ./utils/parametricBootstrapParser.py -h"
output.simulations = <output_to_null_simulations> # the directory ot which the simulated datasets will be written in case of paramtertic bootstrap
simulations.number_of_replicates = <number_of_datasets> # the number of simulated datasets based on which the null likelihood ratio distribution will be set in the case of paramtertic bootstrap