mthapower: Power calculations - mtDNA haplogroups

In aurora-mareviv/mthapower: Sample Size and Power for Association Studies Involving Mitochondrial DNA Haplogroups

Description

For a given study size, determine the minimum effect size that can be detected with the desired power and significance level, in a study with Nh haplogroups. Note: I assume that case-control equations are valid for cohorts with a balanced number of cases and controls. This function may not be generalizable for all studies involving mtDNA haplogroups.

Usage

mthapower(n.cases = ncases, p0 = p0, Nh = Nh,
  OR.cas.ctrl = OR.cas.ctrl, sig.level = sig.level)

Arguments

n.cases	number of cases or controls from the study. It can be either a single value, or a sequence: n.cases <- 300; n.cases <- seq(50,500 by=10).
p0	the frequency of the haplogroup in the control population. It depends on haplogroup baseline frequency.
Nh	number of categories for haplogroups. Usually 10 haplogroups plus one category for rare haplogroups: Nh <- 11.
OR.cas.ctrl	(p1 / (1-p1)) / (p0 / (1-p0)) the OR you want to detect with your data.
sig.level	the alpha error accepted. Can take 3 possible values: 0.05, 0.01 and 0.001 (see [Table 2] of Samuels et al).

Value

Calculates power given the number of cases and other parameters. The output is an object of class data.frame, ready to plot.

Author(s)

Author and maintainer: Aurora Baluja. Email: [e-mail]

References

1. DC Samuels, AD Carothers, R Horton, PF Chinnery. The Power to Detect Disease Associations with Mitochondrial DNA Haplogroups. AJHG, 2006. 78(4):713-720. DOI:10.1086/502682.

2. Source code: github.com/aurora-mareviv/mthapower.

3. Shiny app: aurora.shinyapps.io/mtDNA_power_calc.

Examples

# Example 1:
pow <- mthapower(n.cases=203, p0=0.443, Nh=13, OR.cas.ctrl=2.33, sig.level=0.05)

# Example 2:
# Create data frames
pow.H150 <- mthapower(n.cases=seq(50,1000,by=50), p0=0.433, Nh=11,
                      OR.cas.ctrl=1.5, sig.level=0.05)
pow.H175 <- mthapower(n.cases=seq(50,1000,by=50), p0=0.433, Nh=11,
                      OR.cas.ctrl=1.75, sig.level=0.05)
pow.H200 <- mthapower(n.cases=seq(50,1000,by=50), p0=0.433, Nh=11,
                      OR.cas.ctrl=2, sig.level=0.05)
pow.H250 <- mthapower(n.cases=seq(50,1000,by=50), p0=0.433, Nh=11,
                      OR.cas.ctrl=2.5, sig.level=0.05)

# Bind the three data frames:
bindata <- rbind(pow.H150,pow.H175,pow.H200,pow.H250)
# Adds column OR to binded data frame:
bindata$OR <- rep(factor(c(1.50,1.75,2,2.5)),
              times = c(nrow(pow.H150),
                        nrow(pow.H175),
                        nrow(pow.H200),
                        nrow(pow.H250)))
# Create plot:
# install.packages("car")
library(car)
scatterplot(power~ncases | OR, regLine=FALSE,
            smooth=FALSE,
            boxplots=FALSE,  by.groups=TRUE,
            data=bindata)

aurora-mareviv/mthapower documentation built on June 24, 2019, 4:19 p.m.