plot_saturation_n: Draw a saturation plot of the oligotyping input file (n)...
In genomewalker/oligo4fun: Oligtyping diagnostics for functional genes

Description Usage Arguments Details Value Examples

Perform multiple random subsamplings of your alignemnt.

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plot_saturation_n(aln = aln, rep = 100, nseqs = 1000, model = "K80",
  parallel = FALSE, all = FALSE, reg_id = NULL, reg_dir = NULL,
  conf_file = NULL, job_res = list(), ...)

`aln`	a matrix containing the DNA sequences; this must be of class "DNAbin"
`rep`	number of random subsamplings
`nseqs`	a value for the number of sequences to pick
`model`	a character string specifying the evolutionary model to be used by `dist.dna`
`parallel`	a logical indicating whether to do the random subsampling on a sequential way or use the `BatchJobs` framework to distribute the random subsamplings on different cores or in computer cluster
`all`	a logical indicating whether to use all codon positions; defaults to FALSE so only the third codon position is used.
`reg_id`	Name of registry. Displayed e.g. in mails or in cluster queue
`reg_dir`	Path where files regarding the registry / jobs should be saved
`conf_file`	Location of the configuration file to load

You can calculate multiple saturation plots and its associated statistics. The different random subsamplings can be easily distributed over multiple cores or in a computer cluster.

An object of class “oligodiag” is a list containing at least the following components:

plot: a ggplot object containing the saturation plots of each random sampling
seed: the seeds used for picking the random sequences
aln: a matrix of the random selected sequences stored in binary format for each random subsampling
combined_stats: mean and standard deviation of transitions and transversions for each random subsampling
saturation: whether your alignment presents saturation for each random subsampling
raw: raw results for each random subsampling