gtable_ld_associations_gdata: Gtable of linkage disequilibrium and associations using a...

In snplinkage: Single Nucleotide Polymorphisms Linkage Disequilibrium Visualizations

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) <= 40,
  window = 15,
  ...
)

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

Value

gtable

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')

snplinkage documentation built on Sept. 11, 2024, 6:02 p.m.