Command line

Minimum command line

Specify at least the directory containing the MSAs (-a), the output directory (-o), the number of cores (-c) and the type of the sequences (-d aa or nt).

In addition, you need to specify a model: either with modeltesting (-m), to automatically determine the best-fit model, or using raxml global parameter option (-r or -R).

example: python pargenes/pargenes.py -a msa_dir -o output_dir -c 32 -d nt -R "--model GTR"

Global raxml (or modeltest) options

To specify some parameters to all raxml runs (for instance if you want to set the same model for all the MSAs), you can use --raxml-global-parameters <file>. The file should contain one unique line with all the raxml arguments you want to add.

Example of the content of this file: --model GTR --brlen unscaled

The same applies to modeltest options (--modeltest-global-parameters)

Per-msa raxml (or modeltest) options

To apply different options to each MSA, please use the option--per-msa-raxml-parameters <file>. The file should contain one line per MSA for which you want to add options. Each line starts with the MSA file name (without its path!) followed with the arguments.

For instance:

msa1.fasta --model partition1.part 
msa2.fasta --model partition2.part 
msa3.fasta --model partition3.part 

The same applies to modeltest options (--per-msa-modeltest-parameters)

ParGenes arguments

Unless stated otherwise, we strongly recommend you to use absolute paths when giving a file or directory location.

Common arguments

Command	Meaning
-a, --alignments-dir	Directory containing the input MSA files (fasta or phylip). ParGenes will try to parse all the files in this directory.
-o, --output-dir	Output directory. If the directory does not exist, it ParGenes creates it. Else, ParGenes will abort unless you are running from a checkpoint (see --continue option)
-c, --cores	Number of cores allocated for this job. Do not exceed the number of physical cores available. Should be at least 2.
-d, --data-type	Alignments type: nucleotides or amino acids. Possible values: {nt,aa}.
--dry-run	Special mode to parse the MSA, and compute some statistics without running the analysis. In particular, outputs an estimation of the maximum number of cores that a user could assign to this job without losing parallel efficiency. See also this section
--continue	Restart the analysis from the last checkpoint. Apart from this argument and the number of cores (̀--cores), please avoid changing any of the program inputs. For instance, use this option when your previous run stopped because of a hardware breakdown or a reached wall-time limit.
--scheduler	Defines the scheduling strategy. Possible values are: {split,onecore,openmp}. Please read this section

Arguments to customize RAxML-NG runs

Command	Meaning
-r, --raxml-global-parameters	Path to a file containing one single line with the arguments to pass to all the raxml runs. For instance, the file can contain: --model GTR --brlen unscaled
-R, --raxml-global-parameters-string	Alternative to --raxml-global-parameters: a quoted string with the arguments to pass to all the raxml runs. For instance: -R "--model GTR --brlen unscaled".
--per-msa-raxml-parameters	Path to a file containing per-msa raxml parameters
-s, --random-starting-trees	Number of random starting trees
-p, --parsimony-starting-trees	Number of parsimony starting trees
-b, --bs-trees	Number of bootstrap trees to compute

Arguments to customize ModelTest-NG runs

| -m, --use-modeltest | Autodetect the model with ModelTest-NG before running raxml | | --modeltest-global-parameters | A file containing the parameters to pass to ModelTest-NG | | --per-msa-modeltest-parameters | A file containing per-msa modeltest parameters | | --modeltest-criteria {AICc,AIC,BIC} | The criterion to use for best-fit model selection | | --modeltest-perjob-cores | Number of cores to assign to each modeltest core (at least 4) |

Arguments to customize Astral run

Command	Meaning
--use-astral	Run astral at the end, to generate a species tree from all the gene trees inferred with ParGenes
--astral-global-parameters	Path to a file containing arguments to pass to Astral

Advanced arguments

Other arguments (todo: move the to the upper array)

usage: pargenes.py 
  
  --msa-filter MSA_FILTER
                        A file containing the names of the msa files to
                        process
  --core-assignment {high,medium,low}
                        Policy to decide the per-job number of cores (low
                        favors a low per-job number of cores)


  --percentage-jobs-double-cores PERCENTAGE_JOBS_DOUBLE_CORES
                        Percentage (between 0 and 1) of jobs that will receive
                        twice more cores
  -m, --use-modeltest   Autodetect the model with modeltest
  --modeltest-global-parameters MODELTEST_GLOBAL_PARAMETERS
                        A file containing the parameters to pass to modeltest
  --per-msa-modeltest-parameters PER_MSA_MODELTEST_PARAMETERS
                        A file containing per-msa modeltest parameters
  --modeltest-criteria {AICc,AIC,BIC}
                        Alignments datatype
  --modeltest-perjob-cores MODELTEST_CORES
                        Number of cores to assign to each modeltest core (at
                        least 4)