linkdis.plots: Linkage Disequilibrium heatmap plot
In lmem.gwaser: Linear Mixed Effects Models for Genome-Wide Association Studies

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/exploratory_gwas_functions.R

Performs a Linkage Disequilibrium heatmap plot for the GWAS analysis. Non-random association of markers (linkage disequilibrium) are estimated as Lewont in '/cs D'/c (Lewontin'/cs, 1964) with the LD function of the genetics package (Warnes and Leisch, 2005) and isualized with the LD.heatmap package (Shin et al., 2015). D'/c is estimated as: D'/c = D/DMax where D= pAB - pApB, DMax=Min (pApb, papB), and pA is the probability of the A allele for marker 1, pa=1-pA, pB is the probability of the B allele for marker 2, pb=1-pB, and pAB is the probability of AB alleles.

1	linkdis.plots (crossobj, heterozygotes, chr)

`crossobj`	An object of class = cross obtained from the gwas.cross function from this package, or the read.cross function from r/qtl package (Broman and Sen, 2009). This file contains phenotypic means, genotypic marker score, and genetic map.
`heterozygotes`	Logical value indicating whether heterozygotes are present.
`chr`	A vector containing chromosome number to use.

The function returns the LD.heatmap for the chromosomes selected.

Return a Linkage Disequilibrium heatmap plot.

When large data sets are being used, linkdis.plots is encourage to be performed for each chromosome separately.

Lucia Gutierrez

Comadran J, Thomas W, van Eeuwijk F, Ceccarelli S, Grando S, Stanca A, Pecchioni N, Akar T, Al-Yassin A, Benbelkacem A, Ouabbou H, Bort J, Romagosa I, Hackett C, Russell J (2009) Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin. Theor Appl Genet 119:175-187

Warnes, G; Leisch, F. 2005. Genetics: Population genetics R package 1.2.0. Lewontin, R. 1964. The interaction of selection and linkage. I. General Considerations: Heterotic models. Genetics 49: 49-67.

gwas.analysis

## Not run: 
data (QA_geno)
data (QA_map)
data (QA_pheno)

P.data <- QA_pheno
G.data <- QA_geno
map.data <- QA_map

cross.data <- gwas.cross (P.data, G.data, map.data,
cross='gwas', heterozygotes=FALSE)
summary (cross.data)

LD.plots

linkdis.plots(crossobj = cross.data, heterozygotes = FALSE, chr = c('1', '7'))

## End(Not run)