The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The genpwr package for R (>3.5.1) performs power and sample size calculations for genetic association studies and allows for mis-specification of the genetic model. Calculations can be performed for binary (case/control) and continuous outcomes. Power and sample size calculations are possible for genetic effects as well as gene by environment interactions.
To calculate power to detect an odds ratio of 2 for a 1:1 case control study with 2,000 subjects, assuming an alpha of 0.05, at minor allele frequencies of 0.1, 0.2, and 0.3:
library(genpwr)
#> Loading required package: ggplot2
#> Loading required package: nleqslv
#> Loading required package: MASS
genpwr.calc(calc = "power", model = "logistic", N = 2000, OR = 2,
Alpha = 0.05, MAF = c(0.1,0.2,0.3), Case.Rate = 0.5)
#> Test.Model True.Model MAF OR N_total N_cases N_controls Case.Rate
#> 1 Dominant Dominant 0.1 2 2000 1000 1000 0.5
#> 3 Dominant Additive 0.1 2 2000 1000 1000 0.5
#> 5 Dominant Recessive 0.1 2 2000 1000 1000 0.5
#> 7 Dominant Dominant 0.2 2 2000 1000 1000 0.5
#> 9 Dominant Additive 0.2 2 2000 1000 1000 0.5
#> 11 Dominant Recessive 0.2 2 2000 1000 1000 0.5
#> 13 Dominant Dominant 0.3 2 2000 1000 1000 0.5
#> 15 Dominant Additive 0.3 2 2000 1000 1000 0.5
#> 17 Dominant Recessive 0.3 2 2000 1000 1000 0.5
#> 12 Recessive Dominant 0.1 2 2000 1000 1000 0.5
#> 31 Recessive Additive 0.1 2 2000 1000 1000 0.5
#> 51 Recessive Recessive 0.1 2 2000 1000 1000 0.5
#> 71 Recessive Dominant 0.2 2 2000 1000 1000 0.5
#> 91 Recessive Additive 0.2 2 2000 1000 1000 0.5
#> 111 Recessive Recessive 0.2 2 2000 1000 1000 0.5
#> 131 Recessive Dominant 0.3 2 2000 1000 1000 0.5
#> 151 Recessive Additive 0.3 2 2000 1000 1000 0.5
#> 171 Recessive Recessive 0.3 2 2000 1000 1000 0.5
#> 14 Additive Dominant 0.1 2 2000 1000 1000 0.5
#> 32 Additive Additive 0.1 2 2000 1000 1000 0.5
#> 52 Additive Recessive 0.1 2 2000 1000 1000 0.5
#> 72 Additive Dominant 0.2 2 2000 1000 1000 0.5
#> 92 Additive Additive 0.2 2 2000 1000 1000 0.5
#> 112 Additive Recessive 0.2 2 2000 1000 1000 0.5
#> 132 Additive Dominant 0.3 2 2000 1000 1000 0.5
#> 152 Additive Additive 0.3 2 2000 1000 1000 0.5
#> 172 Additive Recessive 0.3 2 2000 1000 1000 0.5
#> 16 2df Dominant 0.1 2 2000 1000 1000 0.5
#> 33 2df Additive 0.1 2 2000 1000 1000 0.5
#> 53 2df Recessive 0.1 2 2000 1000 1000 0.5
#> 73 2df Dominant 0.2 2 2000 1000 1000 0.5
#> 93 2df Additive 0.2 2 2000 1000 1000 0.5
#> 113 2df Recessive 0.2 2 2000 1000 1000 0.5
#> 133 2df Dominant 0.3 2 2000 1000 1000 0.5
#> 153 2df Additive 0.3 2 2000 1000 1000 0.5
#> 173 2df Recessive 0.3 2 2000 1000 1000 0.5
#> Power_at_Alpha_0.05
#> 1 0.99997130
#> 3 0.99999117
#> 5 0.06094645
#> 7 0.99999997
#> 9 1.00000000
#> 11 0.12562959
#> 13 0.99999999
#> 15 1.00000000
#> 17 0.26400143
#> 12 0.23736708
#> 31 0.72802319
#> 51 0.32261174
#> 71 0.51913618
#> 91 0.99712300
#> 111 0.84110046
#> 131 0.65907220
#> 151 0.99999669
#> 171 0.99128361
#> 14 0.99994745
#> 32 0.99999535
#> 52 0.09704782
#> 72 0.99999973
#> 92 1.00000000
#> 112 0.39542984
#> 132 0.99999976
#> 152 1.00000000
#> 172 0.83339405
#> 16 0.99987562
#> 33 0.99997633
#> 53 0.24913314
#> 73 0.99999976
#> 93 1.00000000
#> 113 0.75849311
#> 133 0.99999996
#> 153 1.00000000
#> 173 0.97950882“The return object contains information about power for additive, dominant, recessive, and 2df / genotypic tests of association, assuming various true underlying genetic effects (additive, dominant, recessive).”
To install genpwr, perform the following steps:
install.packages("genpwr")library(genpwr)Install the genpwr package as described above.
Run the genpwr demo program
demo(genpwr_demo)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.