snp_qq: Q-Q plot

In bigsnpr: Analysis of Massive SNP Arrays

Q-Q plot

Description

Creates a quantile-quantile plot from p-values from a GWAS study.

Usage

snp_qq(gwas, lambdaGC = TRUE, coeff = 1)

Arguments

gwas	A mhtest object with the p-values associated with each SNP. Typically, the output of bigstatsr::big_univLinReg, bigstatsr::big_univLogReg or snp_pcadapt.
lambdaGC	Add the Genomic Control coefficient as subtitle to the plot?
coeff	Relative size of text. Default is 1.

Value

A ggplot2 object. You can plot it using the print method. You can modify it as you wish by adding layers. You might want to read this chapter to get more familiar with the package ggplot2.

Examples

set.seed(9)

test <- snp_attachExtdata()
G <- test$genotypes
y <- rnorm(nrow(G))

gwas <- big_univLinReg(G, y)

snp_qq(gwas)
gwas_gc <- snp_gc(gwas) # this modifies `attr(gwas_gc, "transfo")`
snp_qq(gwas_gc)

# The next plot should be prettier with a real dataset
snp_manhattan(gwas_gc,
              infos.chr = test$map$chromosome,
              infos.pos = test$map$physical.pos) +
  ggplot2::geom_hline(yintercept = -log10(5e-8), linetype = 2, color = "red")

p <- snp_qq(gwas_gc) +
  ggplot2::aes(text = asPlotlyText(test$map)) +
  ggplot2::labs(subtitle = NULL, x = "Expected -log10(p)", y = "Observed -log10(p)")
## Not run: plotly::ggplotly(p, tooltip = "text")

bigsnpr documentation built on Sept. 30, 2024, 9:18 a.m.