Type: Package
Title: Sample Size and Power for Association Studies Involving Mitochondrial DNA Haplogroups
Version: 0.1.1
Maintainer: Aurora Baluja <mariauror@gmail.com>
Description: 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. <doi:10.1086/502682>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: ggplot2, car
URL: https://github.com/aurora-mareviv/mthapower
BugReports: https://github.com/aurora-mareviv/mthapower/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-14 09:00:12 UTC; aure
Author: Aurora Baluja ORCID iD [aut, cre]
Repository: CRAN
Date/Publication: 2019-05-14 09:40:03 UTC

Sample size calculations - mtDNA haplogroups

Description

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. 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

mthacases(p0 = p0, Nh = Nh, OR.cas.ctrl = OR.cas.ctrl,
  power = power, sig.level = sig.level)

Arguments

p0

the frequency of the haplogroup in the control population, (that is, the controls among exposed). It depends on haplogroup baseline frequency.

Nh

number of haplogroup categories. 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. It can be either a single value, or a sequence: OR.cas.ctrl <- 2; OR.cas.ctrl <- seq(1.25,3 by=0.5).

power

the power to detect a given OR in my study (usually 80-90).

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

Gives the result in a data frame, easy to print in a plot.

Author(s)

Author and maintainer: Aurora Baluja. Email: mariauror@gmail.com

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

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
plot(mydata)

Power calculations - mtDNA 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: mariauror@gmail.com

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)