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Create a Manhattan Plot

Source: R/gg_manhattan_df.R
gg_manhattan_df.Rd

This function is a wrapper around ggfastman::fast_manhattan which allows for the creation of a Manhattan plot from a dataframe containing GWAS summary statistics. It handles p-value underflow by calculating -log10 p-values directly from beta and standard error when available.

Usage

gg_manhattan_df(
  sumstats_df,
  annotation_df = NULL,
  chr_col = chromosome,
  pos_col = position,
  pval_col = p_value,
  beta_col = NULL,
  se_col = NULL,
  pval_threshold = 0.001,
  log10p_threshold = 3,
  label_col = gene,
  build = "hg19",
  color1 = "#045ea7",
  color2 = "#82afd3",
  speed = "slow",
  ...
)

Arguments

sumstats_df

Dataframe containing GWAS summary statistics

annotation_df

Optional dataframe containing chromosome, position, and annotation labels

chr_col

Name of chromosome column

pos_col

Name of position column

pval_col

Name of p-value column (used when beta_col and se_col are not provided)

beta_col

Name of beta (effect size) column (optional, used with se_col to avoid p-value underflow)

se_col

Name of standard error column (optional, used with beta_col to avoid p-value underflow)

pval_threshold

Threshold for plotting p-values (p-values greater than this value are excluded from the plot; default = 0.001)

log10p_threshold

Threshold for plotting -log10 p-values when using beta/se (default = 3, equivalent to p < 0.001)

label_col

Name of column in annotation_df containing annotations to include on the plot

build

(string) One of "hg18", "hg19", or "hg38" (passed to ggfastman)

color1

(string) Color for odd-numbered chromosomes (passed to ggfastman)

color2

(string) Color for even-numbered chromosomes (passed to ggfastman)

speed

(string) One of "slow", "fast", or "ultrafast"; passed to ggfastman to control plotting speed

...

Arguments passed to ggfastman::fast_manhattan

Value

A ggplot2 object

See also

Other plotting: gg_qq_df()

Examples

if (FALSE) { # \dontrun{
# Using p-values directly
gg_manhattan_df(sumstats_df)

# Using beta and se to avoid p-value underflow
gg_manhattan_df(sumstats_df, beta_col = beta, se_col = se)
} # }