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# WARNING!!! You need to run bppml on the ML.bpp example file first to be able to run this example!
# Global variables:
DATA = LSU
# Sequences:
# The alphabet to use:
# DNA, RNA or Protein
alphabet=DNA
# The sequence file to use (sequences must be aligned!)
input.sequence.file=../../../Data/$(DATA).phy
# The alignment format:
input.sequence.format=Phylip(order=sequential, type=extended)
#Sites to use:
# all, nogap or complete (=only resolved chars)
input.sequence.sites_to_use = complete
# Specify a maximum amount of gaps: may be an absolute number or a percentage.
input.sequence.max_gap_allowed = 100%
input.tree.file = $(DATA).ML.dnd
input.tree.format = Newick
# ----------------------------------------------------------------------------------------
# Model specification
# ----------------------------------------------------------------------------------------
# the same syntax as in bppML!
# Here we directly use the output file from example ML.bpp to load the model:
param = LSU.params.txt
# ----------------------------------------------------------------------------------------
# Ancestral Sequence Reconstruction
# ----------------------------------------------------------------------------------------
asr.method = marginal //only option for now
# Shall we output the site specific probabilities in each case:
asr.probabilities = yes
# Should we sample from the posterior distribution instead of using the maximum probability?
asr.sample = yes
# How many samples should we use?
asr.sample.number = 10
# Alignment information log file (site specific rates, probabilities, etc):
output.sites.file = $(DATA).sites.csv
# Nodes information log file
output.nodes.file = $(DATA).nodes.csv
# Write sequences:
output.sequence.file = $(DATA).ancestors.fasta
output.sequence.format = Fasta
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