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Easy genome-wide Manhattan plot visualization

Source: R/ez_manhattan.R
ez_manhattan.Rd

This function creates a Manhattan plot from GWAS (Genome-Wide Association Study) data, visualizing p-values across the entire genome with chromosomes displayed along the x-axis using cumulative positions and alternating colors.

For regional association plots (LocusZoom-style) focused on a single locus, use ez_locusZoom() instead.

Usage

ez_manhattan(
  input,
  chr = NULL,
  bp = NULL,
  p = NULL,
  snp = NULL,
  track_labels = NULL,
  group_var = NULL,
  logp = TRUE,
  size = 0.5,
  colors = c("grey", "skyblue"),
  highlight_snps = NULL,
  highlight_color = "purple",
  threshold_p = NULL,
  threshold_color = "red",
  threshold_linetype = 2,
  facet_label_position = c("top", "left"),
  border = FALSE,
  region = NULL,
  gene = NULL,
  ...
)

Arguments

input

A data frame or named list of data frames containing GWAS results with columns for chromosome, position, p-values, and optionally SNP names. Must contain data from multiple chromosomes. Supports both GWAS-style (CHR, BP, P) and GRanges-style (seqnames, start, pvalue) column naming.

chr

Character string specifying the column name for chromosome numbers. Default: auto-detect from "CHR", "seqnames", "chrom", etc.

bp

Character string specifying the column name for base pair positions. Default: auto-detect from "BP", "start", "pos", etc.

p

Character string specifying the column name for p-values. Default: auto-detect from "P", "pvalue", "p.value", etc.

snp

Character string specifying the column name for SNP identifiers. Default: auto-detect from "SNP", "rsid", "variant_id", etc.

track_labels

Optional vector of track labels (used for unnamed list input). Default: NULL.

group_var

Column name for grouping data within a single data frame. Default: NULL.

logp

Logical indicating whether to plot -log10(p-values). Default: TRUE.

size

Numeric value for point size in the plot. Default: 0.5.

colors

Vector of colors for alternating chromosomes. Default: c("grey", "skyblue").

highlight_snps

Character vector of SNP IDs to highlight. Default: NULL.

highlight_color

Color for highlighting significant SNPs. Default: "purple".

threshold_p

Numeric p-value threshold for drawing a significance line (e.g., 5e-8 for genome-wide significance). If NULL, no line is drawn. Default: NULL.

threshold_color

Color for the significance threshold line. Default: "red".

threshold_linetype

Linetype for the significance threshold line. Default: 2 (dashed).

facet_label_position

Position of facet labels for multi-track plots: "top" or "left". Default: "top".

border

Logical. If TRUE, adds a black border around the plot panel. Default: FALSE

region

Deprecated. Use ez_locusZoom() for regional plots.

gene

Deprecated. Use ez_locusZoom() for regional plots.

...

Additional arguments passed to geom_manhattan().

Value

A ggplot2 object containing the Manhattan plot.

Details

This function creates a genome-wide Manhattan plot for GWAS results across multiple chromosomes. It is a wrapper around geom_manhattan that provides a flexible interface with support for grouping and multiple tracks.

The function creates a genome-wide Manhattan plot with:

  • Chromosomes displayed along the x-axis with cumulative positions

  • Alternating colors for adjacent chromosomes (customizable via colors)

  • -log10(p-values) on the y-axis

  • Optional significance threshold line

  • Optional SNP highlighting

For multiple tracks (via named list), plots are stacked vertically using facets. For grouped data (via group_var), colors distinguish different groups.

Regional plots

For LocusZoom-style regional association plots with LD coloring, gene lookup, and stackability with other tracks, use ez_locusZoom() instead.

See also

ez_locusZoom for regional association plots, geom_manhattan for the underlying geom

Examples

# Basic genome-wide Manhattan plot
df <- data.frame(
  CHR = rep(1:3, each = 20),
  BP = rep(1:20, 3) * 1000,
  P = runif(60, 0.0001, 1),
  SNP = paste0("rs", 1:60)
)
ez_manhattan(df)


# With alternating chromosome colors
ez_manhattan(df, colors = c("navy", "orange"))


# With significance threshold
ez_manhattan(df, threshold_p = 5e-8)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_hline()`).