Sample Size and Power for Association Studies Involving Mitochondrial DNA Haplogroups

Calculate Sample Size and Power for Association Studies Involving Mitochondrial DNA Haplogroups. Based on formulae by Samuels et al. AJHG, 2006. 78(4):713-720. .

mthapower

Calculate sample size and power for association studies involving mitochondrial DNA haplogroups - Based on Samuels et al. AJHG, 2006. 78(4):713-720. DOI:10.1086/502682

Installation

• From CRAN:

install.packages("mthapower")

• From GitHub:

# install.packages("devtools")
devtools::install_github("aurora-mareviv/mthapower")

Shiny app

• Run in Shinyapps.io: mtDNA_power_calc
• Run locally from Gist:

# install.packages("shiny")
shiny::runGist('5895082')

Examples

Sample size estimation

• Determine the minimum number of cases (Ncmin), required to detect: either a change from p0 (haplogroup frequency in controls) to p1 (haplogroup frequency in cases), or a given OR, with a predefined confidence interval, in a study with Nh haplogroups.

library(mthapower)
library(dplyr)
mydata <- mthacases(p0=0.445, Nh=11,
                    OR.cas.ctrl=c(2), power=80,
                    sig.level=0.05) # Baudouin study
mydata <- mthacases(p0=0.445, Nh=11,
                    OR.cas.ctrl=c(1.25,1.5,1.75,2,2.25,2.5,2.75,3),
                    power=80, sig.level=0.05)
mydata <- mydata[c(2,6)]
mydata %>%
  knitr::kable()

plot(mydata)

Power estimation

• 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.

# Example 2a:
# library(mthapower)
pow <- mthapower(n.cases=203, p0=0.443, Nh=13, OR.cas.ctrl=2.33, sig.level=0.05)
pow %>%
  knitr::kable()

# Example 2b:
# 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)