gl2bpp {dartR.base}

Converts a genlight object into a format suitable for input to the BPP program

Description

This function generates the sequence alignment file and the Imap file. The control file should produced by the user. If method = 1, heterozygous positions are replaced by standard ambiguity codes. If method = 2, the heterozygous state is resolved by randomly assigning one or the other SNP variant to the individual. Trimmed sequences for which the SNP has been trimmed out, rarely, by adapter mis-identity are deleted. This function requires 'TrimmedSequence' to be among the locus metrics (@other$loc.metrics) and information of the type of alleles (slot loc.all e.g. 'G/A') and the position of the SNP in slot position of the “'genlight“' object (see testset.gl@position and [e-mail] for how to format these slots.)

Usage

gl2bpp(
  x,
  method = 1,
  outfile = "output_bpp.txt",
  imap = "Imap.txt",
  outpath = NULL,
  verbose = NULL
)

Arguments

x

Name of the genlight object containing the SNP data [required].

method

One of 1 | 2, see details [default = 1].

outfile

Name of the saved sequence alignment file ["output_bpp.txt"].

imap

Name of the saved Imap file ["Imap.txt"].

outpath

Path where to save the output file [default global working directory or if not specified, tempdir()].

verbose

Verbosity: 0, silent or fatal errors; 1, begin and end; 2, progress log; 3, progress and results summary; 5, full report [default 2 or as specified using gl.set.verbosity].

Details

It's important to keep in mind that analyses based on coalescent theory, like those done by the programme BPP, are meant to be used with sequence data. In this type of data, large chunks of DNA are sequenced, so when we find polymorphic sites along the sequence, we know they are all on the same chromosome. This kind of data, in which we know which chromosome each allele comes from, is called "phased data." Most data from reduced representation genome-sequencing methods, like DArTseq, is unphased, which means that we don't know which chromosome each allele comes from. So, if we apply coalescence theory to data that is not phased, we will get biased results. As in Ellegren et al., one way to deal with this is to "haplodize" each genotype by randomly choosing one allele from heterozygous genotypes (2012) by using method = 2.

Be mindful that there is little information in the literature on the validity of this method.

Value

returns no value (i.e. NULL)

Author(s)

Custodian: Luis Mijangos (Post to https://groups.google.com/d/forum/dartr)

References

• Ellegren, Hans, et al. "The genomic landscape of species divergence in Ficedula flycatchers." Nature 491.7426 (2012): 756-760.

• Flouri T., Jiao X., Rannala B., Yang Z. (2018) Species Tree Inference with BPP using Genomic Sequences and the Multispecies Coalescent. Molecular Biology and Evolution, 35(10):2585-2593. doi:10.1093/molbev/msy147

See Also

Other linker: gl2bayesAss(), gl2bayescan(), gl2demerelate(), gl2eigenstrat(), gl2faststructure(), gl2gds(), gl2genalex(), gl2genepop(), gl2geno(), gl2gi(), gl2hiphop(), gl2phylip(), gl2plink(), gl2related(), gl2sa(), gl2structure(), gl2treemix(), gl2vcf()

Examples

require(dartR.data)
test <- gl.filter.callrate(platypus.gl,threshold = 1)
test <- gl.filter.monomorphs(test)
test <- gl.subsample.loc(test,n=25)
gl2bpp(x = test, outpath=tempdir())