Contents

visualize$associations$variants.qq

Single-variant association QQ plot

Quantile-quantile plot of a GWAS scan from associate$singleVariant: observed against expected -\log_{10}(p) under the null, with the 1:1 reference line and the genomic-inflation factor \lambda_{GC} annotated.

Usage

visualize.associations.variants.qq(
  results,
  outcome = NULL,
  stratum = NULL,
  genotype = NULL,
  thin = TRUE,
  palette = NULL,
  point.size = 0.7,
  point.alpha = 0.7,
  theme = c("polygenius", "none")
)

Arguments

Argument	Description
`results`	A PolyGeniusAssociation with schema "single.variant", or "meta" over one, or a plain data frame of single-variant rows. Any other schema aborts.
`outcome`	Character scalar, or NULL (default). Phenotype to plot, matched against the outcome column; required only when the result holds more than one phenotype.
`stratum`	Character scalar, or NULL (default). Stratum to plot, matched against the stratum column; required only when the result holds more than one stratum.
`genotype`	Character scalar, or NULL (default). Genotype dataset to plot, matched against the genotype column; required only when the result spans more than one genotype dataset.
`thin`	Logical scalar, default TRUE. Grid-deduplicates the dense bulk below -\log_{10}(p) = 2 to two decimal places once the scan exceeds 1e5 rows, keeping every tail point. Display only, so it never moves \lambda_{GC}.
`palette`	Point color: a role or hue name, a single color, a vector of two or more colors, a ramp function, or NULL (default) for the package categorical line color.
`point.size`	Numeric scalar, default 0.7. Point size.
`point.alpha`	Numeric scalar in [0, 1], default 0.7. Point opacity.
`theme`	One of "polygenius" (default), "none". Plot theme. "none" gives a bare theme_minimal() to style yourself; palette colors are applied either way.

Value

A ggplot object.

Details

P-values are read from the first of pval, p, p.value or pvalue present in the result table, matched case-insensitively and ignoring a leading #. Non-finite values and values outside (0, 1] are dropped, and the plot aborts when none remain.

\lambda_{GC} is not computed here for a PolyGeniusAssociation: it is read from the per-row lambda.gc column of the selected scan, otherwise from the single-row $diagnostics$genomic.inflation, and the plot aborts when neither is present. A plain data frame, for which no engine ever ran, is the only input for which the qchisq() formula is evaluated, over the full unthinned p-value vector.

Examples

gwas <- associate$singleVariant(data, phenotypes = dementia)
visualize$associations$variants.qq(gwas, outcome = "dementia")