Plots linkage disequilibrium against distance by population disequilibrium patterns

The function creates a plot showing the pairwise LD measure against distance in number of base pairs pooled over all the chromosomes and a red line representing the threshold (R.squared = 0.2) that is commonly used to imply that two loci are unlinked (Delourme et al., 2013; Li et al., 2014).

Usage

gl.ld.distance(
  ld_report,
  ld_resolution = 1e+05,
  pop_colors = NULL,
  plot_theme = NULL,
  plot.out = TRUE,
  save2tmp = FALSE,
  verbose = NULL
)

Arguments

ld_report: Output from function gl.report.ld.map [required].
ld_resolution: Resolution at which LD should be reported in number of base pairs [default NULL].
pop_colors: A color palette for box plots by population or a list with as many colors as there are populations in the dataset [default NULL].
plot_theme: User specified theme [default NULL].
plot.out: Specify if plot is to be produced [default TRUE].
save2tmp: If TRUE, saves any ggplots and listings to the session temporary directory (tempdir) [default FALSE].
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].

Value

A dataframe with information of LD against distance by population.

References

Delourme, R., Falentin, C., Fomeju, B. F., Boillot, M., Lassalle, G., André, I., . . . Marty, A. (2013). High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napusL. BMC genomics, 14(1), 120.
Li, X., Han, Y., Wei, Y., Acharya, A., Farmer, A. D., Ho, J., . . . Brummer, E. C. (2014). Development of an alfalfa SNP array and its use to evaluate patterns of population structure and linkage disequilibrium. PLoS One, 9(1), e84329.

Author

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

Examples

if ((requireNamespace("snpStats", quietly = TRUE)) & (requireNamespace("fields", quietly = TRUE))) {
require("dartR.data")
x <- platypus.gl
x <- gl.filter.callrate(x,threshold = 1)
x <- gl.filter.monomorphs(x)
x$position <- x$other$loc.metrics$ChromPos_Platypus_Chrom_NCBIv1
x$chromosome <- as.factor(x$other$loc.metrics$Chrom_Platypus_Chrom_NCBIv1)
ld_res <- gl.report.ld.map(x,ld_max_pairwise = 10000000)
ld_res_2 <- gl.ld.distance(ld_res,ld_resolution= 1000000)
}
#> Starting gl.filter.callrate 
#>   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)
#>   Warning: Data may include monomorphic loci in call rate 
#>                     calculations for filtering
#>   Recalculating Call Rate
#>   Removing loci based on Call Rate, threshold = 1 
#> 

#> Completed: gl.filter.callrate 
#> Starting gl.filter.monomorphs 
#>   Processing genlight object with SNP data
#>   Identifying monomorphic loci
#>   Removing monomorphic loci and loci with all missing 
#>                        data
#> Completed: gl.filter.monomorphs 
#> Starting gl.report.ld.map 
#>   Processing genlight object with SNP data
#>   Calculating pairwise LD in population SEVERN_ABOVE 
#>   Calculating pairwise LD in population SEVERN_BELOW 
#>   Calculating pairwise LD in population TENTERFIELD 
#> 

#> Completed: gl.report.ld.map 
#> Starting gl.ld.distance 
#> 

#>           pop distance    ld_stat
#>        <fctr>    <num>      <num>
#>  SEVERN_ABOVE  1000001 0.10239933
#>  SEVERN_ABOVE  2000001 0.11837328
#>  SEVERN_ABOVE  3000001 0.06542061
#>  SEVERN_ABOVE  4000001 0.08078629
#>  SEVERN_ABOVE  5000001 0.04427707
#>  SEVERN_ABOVE  6000001 0.04725646
#>  SEVERN_ABOVE  7000001 0.09087990
#>  SEVERN_ABOVE  8000001 0.07732017
#>  SEVERN_ABOVE  9000001 0.03934305
#>  SEVERN_ABOVE  9992140 0.07103110
#>  SEVERN_BELOW  1000001 0.14760863
#>  SEVERN_BELOW  2000001 0.14563835
#>  SEVERN_BELOW  3000001 0.05268563
#>  SEVERN_BELOW  4000001 0.08586598
#>  SEVERN_BELOW  5000001 0.10992954
#>  SEVERN_BELOW  6000001 0.04812035
#>  SEVERN_BELOW  7000001 0.07374916
#>  SEVERN_BELOW  8000001 0.10933380
#>  SEVERN_BELOW  9000001 0.12975825
#>  SEVERN_BELOW  9992140 0.03812468
#>   TENTERFIELD  1000001 0.03968855
#>   TENTERFIELD  2000001 0.08432615
#>   TENTERFIELD  3000001 0.06752635
#>   TENTERFIELD  4000001 0.03745991
#>   TENTERFIELD  5000001 0.03536964
#>   TENTERFIELD  6000001 0.10039732
#>   TENTERFIELD  7000001 0.02024599
#>   TENTERFIELD  8000001 0.01268421
#>   TENTERFIELD  9000001 0.04717859
#>   TENTERFIELD  9992140 0.08552747
#>           pop distance    ld_stat
#> Completed: gl.ld.distance 
#>