snp_manhattan: Manhattan plot

In bigsnpr: Analysis of Massive SNP Arrays

Manhattan plot

Description

Creates a manhattan plot.

Usage

snp_manhattan(
  gwas,
  infos.chr,
  infos.pos,
  colors = c("black", "grey60"),
  dist.sep.chrs = 1e+07,
  ind.highlight = integer(0),
  col.highlight = "red",
  labels = NULL,
  npoints = NULL,
  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.
infos.chr	Vector of integers specifying each SNP's chromosome. Typically ⁠<bigSNP>$map$chromosome⁠.
infos.pos	Vector of integers specifying the physical position on a chromosome (in base pairs) of each SNP. Typically ⁠<bigSNP>$map$physical.pos⁠.
colors	Colors used for each chromosome (they are recycled). Default is an alternation of black and gray.
dist.sep.chrs	"Physical" distance that separates two chromosomes. Default is 10 Mbp.
ind.highlight	Indices of SNPs you want to highlight (of interest). Default doesn't highlight any SNPs.
col.highlight	Color used for highlighting SNPs. Default uses red.
labels	Labels of the x axis. Default uses the number of the chromosome there are in infos.chr(sort(unique(infos.chr))). This may be useful to restrict the number of labels so that they are not overlapping.
npoints	Number of points to keep (ranked by p-value) in order to get a lighter object (and plot). Default doesn't cut anything. If used, the resulting object will have an attribute called subset giving the indices of the kept points.
coeff	Relative size of text. Default is 1.

Details

If you don't have information of chromosome and position, you should simply use plot instead.

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.