snp.score(data, response.var, snp.var, exposure.var, main.vars,
strata.var=NULL, op=NULL)
op$method
=1 (see details).snp.logistic
, the strata.var
in snp.score
cannot currently handle continuous variables like principal components of
population stratification.op$method
= 1 (MScore), the returned object is a list with the following components:
maxTheta
Value ofthetas
where the maximum score test occurs.maxScore
Maximum value of the score test.pval
P-value of the score test.pval.logit
P-value of the standard association test based on logistic regression.model.info
List of information from the model. For op$method
= 2 (JScore), the returned object is
a list containing test statistics, p-values and one-step MLEs for the parameters and
variance-covariance matrices for the UML, CML and EB methods. Any name in the list
containing the string "test", "pval", "parm" or "var" is a test statistic, p-value,
parameter estimate or variance-covariance matrix respectively.
Options list:
Below are the names for the options list op
.
method
1 or 2 for the test. 1 = MScore, 2 = JScore.
The default is 2.thetas
Numeric vector of values in which the test statistic will be calculated over to find the maximum.
Theta values correspond to different risk models, which can take any value of real numbers.
For example, theta = -1 corresponds to an additive model, 0 to a multiplicative model,
and a probit model is between -1 < theta < 0. Supra-multiplicative model corresponds to theta > 1.
The default is seq(-3, 3, 0.1)indep
TRUE or FALSE for the gene-environment independence assumption.
The default is FALSE.doGLM
TRUE or FALSE for calculating the Wald p-value for the SNP main effect. The default is FALSE.sandwich
TRUE or FALSE to return tests and p-values based on a sandwich covariance matrix.
The default is FALSE.Song M., Wheeler B., Chatterjee, N. Using imputed genotype data in joint score tests for genetic association and gene-environment interactions in case-control studies (In preparation).
snp.logistic
# Use the ovarian cancer data
data(Xdata, package="CGEN")
table(Xdata[, "gynSurgery.history"])
# Recode the exposure variable so that it is 0-1
temp <- Xdata[, "gynSurgery.history"] == 2
Xdata[temp, "gynSurgery.history"] <- 1
out <- snp.score(Xdata, "case.control", "BRCA.status", "gynSurgery.history",
main.vars=c("n.children","oral.years"), op=list(method=2))
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