SNP track merged — snp_track

Manhattan plot of GWAS/QTL data with various fine-mapping related annotations. Support function for plot_locus.

Usage

snp_track_merged(
  dat,
  yvar = "-log10(P)",
  labels_subset = c("Lead", "CS", "UCS", "Consensus"),
  absolute_labels = FALSE,
  label_type = "rsid_only",
  label_leadsnp = TRUE,
  sig_cutoff = 5e-08,
  point_alpha = 0.5,
  show.legend = TRUE,
  xtext = TRUE,
  facet_formula = "Method~.",
  dataset_type = NULL,
  genomic_units = "POS",
  remove_duplicates = FALSE,
  strip.text.y.angle = 0,
  show_plot = FALSE,
  verbose = TRUE
)

Arguments

dat: Data to query transcripts with.
labels_subset: Include colored shapes and RSID labels to help highlight SNPs belonging to one or more of the following groups: Lead, Credible Set, Consensus.
sig_cutoff: Filters out SNPs to plot based on an (uncorrected) p-value significance cutoff.
point_alpha: Opacity of each data point.
xtext: Include x-axis title and text for each track (not just the lower-most one).
facet_formula: Formula to facet plots by. See facet_grid for details.
dataset_type: Dataset type (e.g. "GWAS" or "eQTL").
genomic_units: Which genomic units to return window limits in.
remove_duplicates: Remove duplicate labels when SNPs are part of >1 group in labels_subset.
strip.text.y.angle: Angle of the y-axis facet labels.
show_plot: Print plot to screen.
verbose: Print messages.

Examples

dat <- echodata::BST1[seq_len(100),]
plt <- snp_track_merged(dat = dat, yvar="PP", show_plot=TRUE)
#> Melting PP and CS from 5 fine-mapping methods.
#> + echoplot:: Constructing SNP labels.
#> Data is already melted. Skipping.
#> Adding SNP group labels to locus plot.