read.plink: Read a PLINK binary fileset into a 'genotypes' object

In andrewparkermorgan/argyle: Basic interface and QC for genotypes from Illumina Infinium arrays

Description

Read a PLINK binary fileset into a genotypes object

Usage

read.plink(prefix, intensity = FALSE, chr = NULL, from = NULL,
  to = NULL, markers = NULL, keep = NULL, keep.chrnames = FALSE, ...)

Arguments

prefix	path to a PLINK fileset, excluding *.bed suffix
intensity	attempt to read intensity matrices (*.bii), if present
chr	chromosome(s) to keep
from	keep markers at physical position greater than or equal to this
to	keep markers at physical position less than or equal to this
markers	keep *markers* with these names
keep	keep *samples* with these names
keep.chrnames	whether to keep chromosome names as-is, or allow them to be converted to PLINK's style
...	ignored

Details

Reads a PLINK binary fileset using pure R. The fileset should be generated in the "variant-major" format (the default in all recent versions of PLINK.) Missing genotypes are represented as NAs.

If any of chr,from,to,markers,keep are specified, the file will be read in random-access mode. Positional filters are applied only if one or more chromosomes are specified. Marker-name filters are applied after chromosome/position filters; it rarely makes sense to specify both a set of names and a set of positions. Chromosome names must match exactly those used in the marker map (*.bim file), and sample names must match exactly those used in the sample metadata file (*.fam file).

Random-access mode is not guaranteed to be more efficient than reading the whole dataset into the R session and then subsetting it. Efficiency gains will depend on how much of the data happends to be found in contiguous blocks, and also on hardware (eg. SSD versus standard hard disk).

If intensities are present, they are expected to be encoded as described in the help page for write.plink().

Value

a genotypes object, with alleles in the "01" encoding (see recode.genotypes)

References

PLINK v1.9: https://www.cog-genomics.org/plink2

Purcell S et al. (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 81(3): 559-575. doi:10.1086/519795.

See Also

write.plink

andrewparkermorgan/argyle documentation built on May 10, 2019, 11:08 a.m.