MendelianRandomization (version 0.10.0)

mr_forest: Draw a forest plot of causal estimates

Description

The mr_forest function draws a forest plot of causal estimates. The default option plots the variant-specific causal estimates (by/bx) and the estimate from the mr_ivw function using default settings (assuming variants are uncorrelated, random-effects for 4+ variants). Options allow users to plot estimates from a variety of different methods.

Usage

mr_forest(
  object,
  alpha = 0.05,
  snp_estimates = TRUE,
  methods = "ivw",
  ordered = FALSE
)
# S4 method for MRInput
mr_forest(
  object,
  alpha = 0.05,
  snp_estimates = TRUE,
  methods = "ivw",
  ordered = FALSE
)

Arguments

object

An MRInput object.

alpha

The significance level used to calculate the confidence intervals. The default value is 0.05, corresponding to 95% confidence intervals.

snp_estimates

Whether to plot the variant-specific estimates. Defaults to TRUE.

methods

Takes a string of computation methods used to calculate estimates. Defaults to "ivw". Options are: "median" (simple median estimate), "wmedian" (weighted median estimate), "egger" (MR-Egger estimate), "mbe" (mode-based estimate), "conmix" (contamination mixture estimate), and "maxlik" (maximum likelihood estimate).

ordered

Determines by whether to arrange the variant-specific estimates in ascending order. Defaults to FALSE.

Details

As the function produces a ggplot object, graphical parameters can be changed by adding commands from the ggplot2 package.

Examples

mr_forest(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse),
  alpha = 0.01, ordered = TRUE)
mr_forest(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse),
  methods = c("ivw", "wmedian", "egger"), snp_estimates = FALSE)
forest = mr_forest(mr_input(bx = ldlc, bxse = ldlcse, by = chdlodds, byse = chdloddsse))
# how to change x-axis limits
# library(ggplot2)
# forest2 = forest + coord_cartesian(xlim=c(-5,5))
# forest2