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a
b
Fig. 26: (a) Duplicating datasets and (b) the parameter panel indicates the modified settings as chosen in the ‘[A]
Analysis Settings’ window (here, we have changed the substitution model to K2P with rate heterogeneity (and
estimated starting parameters) for the ‘Primate_1’ duplicate whereas the initial settings for the ‘Primate’ dataset is
JC).
Notes: when running a batch file:
✓ The run window is simplified (in comparison to what is described above in Section 5.5). Beside basic statistics on
the current run, the batch run window displays (in two separate panels) the log file information on the current run
and on the overall batch. Two buttons allow for stopping either the current run or the entire batch of runs.
✓ The result trees of all replicates of all runs are automatically added to the ‘TreeViewer’.
5.8. Building batch files manually
Instead of using the GUI, you can manually build Nexus batch files. As an example, the file below
will run the single dataset of 15 taxa and 100 characters first with the JC model then with the GTR
model + gamma-distributed rate heterogeneity.
The full list of MetaPIGA commands for manually building batch files are available in the Appendix 1.
Check the end of section 5.2 for instructions on how running MetaPIGA in command line (this
is particularly useful if you want to send jobs to a distant server).
#NEXUS
[Metapiga - LANE (Laboratory of Artificial and Natural Evolution, University of Geneva)]
BEGIN BATCH;
RUN LABEL=15-100 DATA=data_1 PARAM=param_1;
RUN LABEL=15-100_1 DATA=data_1 PARAM=param_2;
END;
BEGIN METAPIGA;
[BATCHLABEL=param_1]
HEURISTIC CP CONSENSUS=STOCHASTIC OPERATOR=SUPERVISED NPOP=4 NIND=4 TOLERANCE=0.05
HYBRIDIZATION=0.1 SELECTION=IMPROVE RECOMBINATION=0.1 OPERATORAPPLIEDTO=IND NCORE=1;
EVALUATION MODEL=JC DISTRIBUTION=NONE PINV=0.0;
OPTIMIZATION ENDONLY ALGO=GA TARGET{ BL };
STARTINGTREE GENERATION=LNJ(0.1)
MODEL=JC DISTRIBUTION=NONE PINV=0.0;
MetaPIGA 3.0 manual
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