hapPower | R Documentation |
Simulates the statistical power of genetic analyses assessing fetal effects, maternal effects and/or parent-of-origin effects. Effects of X-chromosome genes and gene-environment interaction effects are also allowed.
hapPower(hapRun.result, alpha = 0.05)
hapRun.result |
The result of running |
alpha |
|
The Haplin framework includes different modules for assessing genetic effects: haplin
,
haplinStrat
and haplinSlide
. hapPower
simulates the power of these analyses, which enables power calculations of fetal effects, maternal effects and/or parent-of-origin effects. Various family designs, i.e., triads, case-control, the hybrid design, and all intermediate designs, are possible.
It also allows power calculation of gene-environment interaction effects and effects on X-chromosome markers.
hapPower
calculates statistical power using the result of hapRun
, and the target effects must be specified in this function, see Examples below, and details in https://haplin.bitbucket.io/docu/Haplin_power.pdf.
hapPower
returns the simulated power.
Miriam Gjerdevik,
with Hakon K. Gjessing
Professor of Biostatistics
Division of Epidemiology
Norwegian Institute of Public Health
Web Site: https://haplin.bitbucket.io
haplin
, haplinSlide
, hapSim
, hapRun
, snpPower
, snpSampleSize
, hapPowerAsymp
## Not run:
## Simulate power from 100 files using haplin.
## The files consist of fetal effects at two diallelic markers,
## corresponding to haplo.freq = rep(0.25, 4), RR = c(2,1,1,1) and RRstar = c(1,1,1,1).
## The power is simulated for the combination of 100 case triads
## and 100 control triads with no missing data at a 0.05 significance level,
## applying a multiplicative model.
hapRun.res <- hapRun(nall = c(2,2), n.strata = 1, cases = c(mfc=100), controls = c(mfc=100),
haplo.freq = rep(0.25,4), RR = c(2,1,1,1), RRstar = c(1,1,1,1),
hapfunc = "haplin", response = "mult", n.sim = 100, dire = "simfiles", ask = FALSE)
hapPower(hapRun.res)
## Simulate power from 100 files applying haplinStrat.
## The files consist of fetal and maternal effects at two diallelic markers.
## The data is simulated for 500 case triads and 200 control families in the first stratum,
## and 500 case triads and 500 control trids in the second.
## The fetal effects vary across strata,
## whereas the maternal effects are the same.
## One percent of the case triads are missing at random in the second stratum.
hapRun.res <- hapRun(nall = c(2,2), n.strata = 2, cases = c(mfc=500),
controls = list(c(mfc=200),c(mfc=500)), haplo.freq = rep(0.25,4), maternal = TRUE,
RR = list(c(1.5,1,1,1),c(1,1,1,1)), RRstar = c(1,1,1,1),
RR.mat = c(1.5,1,1,1), RRstar.mat = c(1,1,1,1), gen.missing.cases = list(NULL,0.01),
use.missing = TRUE, hapfunc = "haplinStrat", n.sim = 100, ask = FALSE)
hapPower(hapRun.res)
## Simulate power at the 0.1 significance level from 1000 files using haplin.
## The files consist of fetal effects at one diallelic locus,
## corresponding to haplo.freq = c(0.1,0.9), RR = c(2,1) and RRstar = c(1,1).
## The data consists of a combination of 100 case triads and 100 control triads.
hapRun.res <- hapRun(nall = c(2), cases = c(mfc=100), controls = c(mfc=100),
haplo.freq = c(0.1,0.9), RR = c(2,1), RRstar = c(1,1),
hapfunc = "haplin", response = "mult", n.sim = 1000, ask = FALSE)
hapPower(hapRun.res, alpha= 0.10)
## The latter example, applying response = "mult", should be comparable to
## the theoretic calculations of snpPower.
snpPower(cases = list(mfc=100), controls = list(mfc=100),
RR = 2, MAF = 0.1, alpha = 0.10)
## End(Not run)
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