plot_features: Plot sequence features such as domains alongside...

In adamwaring/ClusterBurden: Rare variant association utilising burden and positional information.

Description

Plot sequence features such as domains alongside distributions of case and control variant residues

Usage

plot_features(
  genename,
  pvals,
  cases,
  controls,
  case_coverage,
  control_coverage,
  cov_threshold = 0.5,
  features = c("Compositional-bias", "Coiled-coil", "Repeat", "Zinc-Finger", "Region",
    "Motif", "Domain", "Topological domain", "Intramembrane", "Transmembrane",
    "Cross-link", "Disulphide", "Glycosylation", "Lipidation", "Peptide", "Propeptide",
    "Signal peptide", "Transit peptide", "Structure"),
  SCALE = 1
)

Arguments

genename	gene to plot
pvals	pvals data.table from ClusterBurden WES analysis
cases	case data in format: data.table(aff, symbol, protein_position, ac)
controls	control data in format: data.table(aff, symbol, protein_position, ac)
case_coverage	optional coverage data for cases in format: data.table(symbol, protein_position, over_10)
control_coverage	optional coverage data for controls in format: data.table(symbol, protein_position, over_10)
cov_threshold	threshold at which to exclude a residue position from the analysis (choose 0 to keep all residues)
features	which sequence features to plot e.g. c("Domain", "Region", "Structure")
SCALE	scale of the plot

Value

Returns a ggplot object

Author(s)

Adam Waring - [e-mail]

adamwaring/ClusterBurden documentation built on July 29, 2020, 9:50 p.m.