snplinkage (version 1.2.0)

gtable_ld_associations_gdata: Gtable of linkage disequilibrium and associations using a GenotypeData object

Description

Compute linkage disequilibrium using snprelate_ld on the set of SNPs in the associations data frame and call gtable_ld_associations. Creates a gtable of a linkage disequilibrium, chromosomic positions, and association scores ggplots.

Usage

gtable_ld_associations_gdata(
  df_assocs,
  gdata,
  pvalue_colname = "pvalues",
  labels_colname = "probe_id",
  diamonds = nrow(df_assocs) 

Value

gtable

Arguments

df_assocs

SNP annotation data frame with columns chromosome, position, and as specified by parameters pvalue_colname and optionally labels_colname.

gdata

GenotypeData object, as returned by load_gds_as_genotype_data

pvalue_colname

Column name of df_snp with association values

labels_colname

Optional column name of df_snp with labels. Set NULL to remove labels.

diamonds

Should the values be displayed as diamonds or points ? Default is TRUE for up to 40 SNPs.

window

Window size for snprelate_ld. Forced to the total number of SNPs if diamonds is FALSE

...

Passed to gtable_ld_associations

Examples

library(snplinkage)
gds_path <- save_hgdp_as_gds()
gdata <- load_gds_as_genotype_data(gds_path)
qc <- snprelate_qc(gdata, tagsnp = .99)

snp_idxs_mhc <- select_region_idxs(qc$gdata,
  chromosome = 6, position_min = 29e6, position_max = 33e6)
df_assocs <- chisq_pvalues_gdata(qc$gdata, snp_idxs_mhc)

df_top_aim <- subset(df_assocs, rank(-pvalues, ties.method = 'first') <= 20)

#qc$gdata <- gdata_add_gene_annots(qc$gdata, rownames(df_top_aim))
qc$gdata <- gdata_add_gene_annots_aim_example(qc$gdata, rownames(df_top_aim))

plt <- gtable_ld_associations_gdata(df_top_aim, qc$gdata,
  labels_colname = 'gene')