Separate markers column into chrom, locus and pos

Radiator uses unique marker names by combining CHROM, LOCUS, POS columns, with double underscore separators, into MARKERS = CHROM__LOCUS__POS.

Used internally in radiator and might be of interest for users who need to get back to the original metadata the function provides an easy way to do it.

separate_markers(
  data,
  sep = "__",
  markers.meta.lists.only = FALSE,
  markers.meta.all.only = FALSE,
  generate.markers.metadata = TRUE,
  generate.ref.alt = FALSE,
  biallelic = NULL,
  parallel.core = parallel::detectCores() - 1,
  verbose = TRUE
)

Arguments

data

An object with a column named MARKERS. If CHROM, LOCUS, POS are already present, the function returns the dataset untouched. The data can be whitelists and blacklists of markers or tidy datasets or radiator GDS object.

sep

(optional, character) Separator used to identify the different field in the MARKERS column.

When the MARKERS column doesn't have separator and the function is used to generate markers metadata column: "CHROM", "LOCUS", "POS", "REF", "ALT", use sep = NULL. Default: sep = "__".

markers.meta.lists.only

(logical, optional) Allows to keep only the markers metadata: "VARIANT_ID", "MARKERS", "CHROM", "LOCUS", "POS", useful for whitelist or blacklist. Default: markers.meta.lists.only = FALSE

markers.meta.all.only

(logica, optionall) Allows to keep all available markers metadata: "VARIANT_ID", "MARKERS", "CHROM", "LOCUS", "POS", "COL", "REF", "ALT", useful inside radiator. Default: markers.meta.all.only = FALSE

generate.markers.metadata

(logical, optional) Generate missing markers metadata when missing. "CHROM", "LOCUS", "POS". Default: generate.markers.metadata = TRUE

generate.ref.alt

(logical, optional) Generate missing REF/ALT alleles with: REF = A and ALT = C (for biallelic datasets, only). It is turned off automatically when argument markers.meta.lists.only = TRUE and on automatically when argument markers.meta.all.only = TRUE Default: generate.ref.alt = FALSE

biallelic

(logical) Speed up the function execution by entering if the dataset is biallelic or not. Used internally for verification, before generating REF/ALT info. By default, the function calls detect_biallelic_markers. The argument is required if data is a tidy dataset and not just a whitelist/blacklist. Default: biallelic = NULL

parallel.core

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

verbose

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

Value

The same data in the global environment, with 3 new columns: CHROM, LOCUS, POS. Additionnal columns may be genrated, see arguments documentation.

See also

detect_biallelic_markers and generate_markers_metadata

Author

Thierry Gosselin thierrygosselin@icloud.com

Examples

if (FALSE) { # \dontrun{
whitelist <- radiator::separate_markers(data = whitelist.markers)
tidy.data <- radiator::separate_markers(data = bluefintuna.data)
} # }