View source: R/gl.ld.distance.r
gl.ld.distance | R Documentation |
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).
gl.ld.distance(
ld_report,
ld_resolution = 1e+05,
pop_colors = NULL,
plot_theme = NULL,
plot.out = TRUE,
save2tmp = FALSE,
verbose = NULL
)
ld_report |
Output from function |
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]. |
A dataframe with information of LD against distance by population.
Custodian: Luis Mijangos – Post to https://groups.google.com/d/forum/dartr
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.
Other ld functions:
gl.ld.haplotype()
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)
}
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