Write a genlight object from: a tidy data frame, GDS file or object.

Source: R/genlight.R

Write a genlight object from a tidy data frame or GDS file or object. Used internally in radiator and might be of interest for users. genlight is a formal (S4) class for storing genotypes of binary SNPs in a compact way, using a bit-level coding scheme. This storage is most efficient with haploid data, where the memory taken to represent data can be reduced more than 50 times. However, genlight can be used for any level of ploidy, and still remain an efficient storage mode.

write_genlight(
  data,
  write = FALSE,
  dartr = FALSE,
  verbose = FALSE,
  parallel.core = parallel::detectCores() - 2,
  biallelic = TRUE
)

Arguments

data

(4 options) A file or object generated by radiator:

  • tidy data

  • Genomic Data Structure (GDS)

How to get GDS and tidy data ? Look into tidy_genomic_data, read_vcf or tidy_vcf.

write

(logical, optional) To write in the working directory the genlight object. The file is written with radiator_genlight_DATE@TIME.RData and can be open with load or readRDS. Default: write = FALSE.

dartr

(logical, optional) For non-dartR users who wants to have a genlight object ready for the dartR package. This option transfer or generates: CALL_RATE, AVG_COUNT_REF, AVG_COUNT_SNP, REP_AVG, ONE_RATIO_REF, ONE_RATIO_SNP. These markers metadata are stored into the genlight slot: genlight.obj@other$loc.metrics. Use the radiator generated GDS data for best result. Default: dartr = FALSE.

verbose

(optional, logical) When verbose = TRUE the function is a little more chatty during execution. Default: verbose = TRUE.

parallel.core

(optional) The number of core used for parallel execution during import. Default: parallel.core = parallel::detectCores() - 1.

biallelic

(logical, optional) If you already know that the data is biallelic use this argument to speed up the function. Default: biallelic = TRUE.

References

Jombart T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics, 24, 1403-1405.

Jombart T, Ahmed I (2011) adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics, 27, 3070-3071.

Author

Thierry Gosselin thierrygosselin@icloud.com

Examples

if (FALSE) { # \dontrun{
# With defaults:
turtle <- radiator::write_genlight(data = "my.radiator.gds.rad")

# Write gl object in directory:
turtle <- radiator::write_genlight(data = "my.radiator.gds.rad", write = TRUE)

# Generate a dartR ready genlight and verbose = TRUE:
turtle <- radiator::write_genlight(
    data = "my.radiator.gds.rad",
    write = TRUE,
    dartr = TRUE,
    verbose = TRUE
 )
} # }