gl.ld.haplotype {dartR.popgen}

Visualize patterns of linkage disequilibrium and identification of haplotypes

Description

This function plots a Linkage disequilibrium (LD) heatmap, where the colour shading indicates the strength of LD. Chromosome positions (Mbp) are shown on the horizontal axis, and haplotypes appear as triangles and delimited by dark yellow vertical lines. Numbers identifying each haplotype are shown in the upper part of the plot.

The heatmap also shows heterozygosity for each SNP.

The function identifies haplotypes based on contiguous SNPs that are in linkage disequilibrium using as threshold ld_threshold_haplo and containing more than min_snps SNPs.

Usage

gl.ld.haplotype(
  x,
  pop_name = NULL,
  chrom_name = NULL,
  ld_max_pairwise = 1e+07,
  maf = 0.05,
  ld_stat = "R.squared",
  ind.limit = 10,
  haplo_id = FALSE,
  min_snps = 10,
  ld_threshold_haplo = 0.5,
  target_snp = NULL,
  coordinates = NULL,
  color_haplo = "viridis",
  color_het = "deeppink",
  plot.out = TRUE,
  plot.save = FALSE,
  plot.dir = NULL,
  verbose = NULL
)

Arguments

x

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

pop_name

Name of the population to analyse. If NULL all the populations are analised [default NULL].

chrom_name

Nme of the chromosome to analyse. If NULL all the chromosomes are analised [default NULL].

ld_max_pairwise

Maximum distance in number of base pairs at which LD should be calculated [default 10000000].

maf

Minor allele frequency (by population) threshold to filter out loci. If a value > 1 is provided it will be interpreted as MAC (i.e. the minimum number of times an allele needs to be observed) [default 0.05].

ld_stat

The LD measure to be calculated: "LLR", "OR", "Q", "Covar", "D.prime", "R.squared", and "R". See ld (package snpStats) for details [default "R.squared"].

ind.limit

Minimum number of individuals that a population should contain to take it in account to report loci in LD [default 10].

haplo_id

Whether to identify haplotypes [default FALSE].

min_snps

Minimum number of SNPs that should have a haplotype to call it [default 10].

ld_threshold_haplo

Minimum LD between adjacent SNPs to call a haplotype [default 0.5].

target_snp

Position of target SNP [default NULL].

coordinates

A vector of two elements with the start and end coordinates in base pairs to which restrict the analysis e.g. c(1,1000000) [default NULL].

color_haplo

Color palette for haplotype plot. See details [default "viridis"].

color_het

Color for heterozygosity [default "deeppink"].

plot.out

Specify if heatmap plot is to be produced [default TRUE].

plot.save

Whethwr to save the plot in pdf format [default FALSE].

plot.dir

Directory in which to save files [default = working directory]

verbose

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

Details

The information for SNP's position should be stored in the genlight accessor "@position" and the SNP's chromosome name in the accessor "@chromosome" (see examples). The function will then calculate LD within each chromosome.

The output of the function includes a table with the haplotypes that were identified and their location.

Colors of the heatmap (color_haplo) are based on the function scale_fill_viridis from package viridis. Other color palettes options are "magma", "inferno", "plasma", "viridis", "cividis", "rocket", "mako" and "turbo".

Value

A table with the haplotypes that were identified.

Author(s)

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

See Also

Other ld functions: gl.ld.distance()

Examples

require("dartR.data")
x <- platypus.gl
x <- gl.filter.callrate(x, threshold = 1)
# only the first 15 individuals because of speed during tests
x <- gl.keep.pop(x, pop.list = "TENTERFIELD")[1:15, ]
x$chromosome <- as.factor(x$other$loc.metrics$Chrom_Platypus_Chrom_NCBIv1)
x$position <- x$other$loc.metrics$ChromPos_Platypus_Chrom_NCBIv1
ld_res <- gl.ld.haplotype(x,
  chrom_name = "NC_041728.1_chromosome_1",
  ld_max_pairwise = 10000000
)