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The output of this function are three files:

  • genotype file: contains genotype data for each individual at each SNP with an extension 'eigenstratgeno.'

  • snp file: contains information about each SNP with an extension 'snp.'

  • indiv file: contains information about each individual with an extension 'ind.'

Usage

gl2eigenstrat(
  x,
  outfile = "gl_eigenstrat",
  outpath = tempdir(),
  snp_pos = 1,
  snp_chr = 1,
  pos_cM = 0,
  sex_code = "unknown",
  phen_value = "Case",
  verbose = NULL
)

Arguments

x

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

outfile

File name of the output file [default 'gl_eigenstrat'].

outpath

Path where to save the output file [default tempdir(), mandated by CRAN]. Use outpath=getwd() or outpath='.' when calling this function to direct output files to your working directory.

snp_pos

Field name from the slot loc.metrics where the SNP position is stored [default 1].

snp_chr

Field name from the slot loc.metrics where the chromosome of each is stored [default 1].

pos_cM

A vector, with as many elements as there are loci, containing the SNP position in morgans or centimorgans [default 1].

sex_code

A vector, with as many elements as there are individuals, containing the sex code ('male', 'female', 'unknown') [default 'unknown'].

phen_value

A vector, with as many elements as there are individuals, containing the phenotype value ('Case', 'Control') [default 'Case'].

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

Eigenstrat only accepts chromosomes coded as numeric values, as follows: X chromosome is encoded as 23, Y is encoded as 24, mtDNA is encoded as 90, and XY is encoded as 91. SNPs with illegal chromosome values, such as 0, will be removed.

References

  • Patterson, N., Price, A. L., & Reich, D. (2006). Population structure and eigenanalysis. PLoS genetics, 2(12), e190.

  • Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nature genetics, 38(8), 904-909.

Author

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

Examples

# \donttest{
require("dartR.data")
gl2eigenstrat(platypus.gl,snp_pos='ChromPos_Platypus_Chrom_NCBIv1',
snp_chr = 'Chrom_Platypus_Chrom_NCBIv1')
#> Starting gl2eigenstrat 
#>   Processing genlight object with SNP data
#>   Warning: data include loci that are scored NA across all individuals.
#>   Consider filtering using gl <- gl.filter.allna(gl)
#> Completed: gl2eigenstrat 
#> 
# }