Combine results from haplo.score, haplo.group, and haplo.glm for case-control study designs. Analyze the association between the binary (case-control) trait and the haplotypes relevant to the unrelated individuals' genotypes.
haplo.cc(y, geno, x.adj=NA, locus.label=NA, ci.prob=0.95,
miss.val=c(0,NA), weights=NULL, eps.svd=1e-5, simulate=FALSE,
sim.control=score.sim.control(), control=haplo.glm.control())A list including the haplo.score object (score.lst), vector of subject counts by case and control group (group.count), haplo.glm object (fit.lst), confidence interval probability (ci.prob), and a data frame (cc.df) with the following components:
The first K columns contain the haplotypes used in the analysis.
Score statistic for association of haplotype with the binary trait.
P-value for the haplotype score statistic, based on a chi-square distribution with 1 degree of freedom.
Vector of p-values for score.haplo, based on simulations in haplo.score (omitted when simulations not performed). P-value of score.global based on simulations (set equal to NA when simulate=F).
Estimated haplotype frequency for cases and controls pooled together.
Estimated haplotype frequency for control group subjects.
Estimated haplotype frequency for case group subjects.
The haplo.glm function modeled the haplotype effects as: baseline (Base), additive haplotype effect (Eff), or rare haplotypes pooled into a single group (R).
Lower limit of the Odds Ratio Confidence Interval.
Odds Ratio based on haplo.glm model estimated coefficient for the haplotype.
Upper limit of the Odds Ratio Confidence Interval.
Vector of trait values, must be 1 for cases and 0 for controls.
Matrix of alleles, such that each locus has a pair of adjacent columns of alleles, and the order of columns corresponds to the order of loci on a chromosome. If there are K loci, then ncol(geno) = 2*K. Rows represent alleles for each subject.
Matrix of non-genetic covariates used to adjust the score statistics. Note that intercept should not be included, as it will be added in this function.
Probability level for confidence interval on the Odds Ratios of each haplotype to span the true value.
Vector of labels for loci, of length K (see definition of geno matrix)
Vector of codes for missing values of alleles
the weights for observations (rows of the data frame). By default, all observations are weighted equally. One use is to correct for over-sampling of cases in a case-control sample.
epsilon value for singular value cutoff; to be used in the generalized inverse calculation on the variance matrix of the score vector. The degrees of freedom for the global score test is 1 less than the number of haplotypes that are scored (k-1). The degrees of freedom is calculated from the rank of the variance matrix for the score vector. In some instances of numeric instability, the singular value decomposition indicates full rank (k). One remedy has been to give a larger epsilon value.
Logical: if [F]alse, no empirical p-values are computed; if [T]rue, simulations are performed within haplo.score. Specific simulation parameters can be controlled in the sim.control parameter list.
A list of control parameters to determine how simulations are performed for simulated p-values. The list is created by the function score.sim.control and the default values of this function can be changed as desired. See score.sim.control for details.
A list of control parameters for managing the execution of haplo.cc. The list is created by the function haplo.glm.control, which also manages control parameters for the execution of haplo.em.
All function calls within haplo.cc are for the analysis of association between haplotypes and the case-control status (binomial trait). No additional covariates may be modeled with this function. Odd Ratios are in reference to the baseline haplotype. Odds Ratios will change if a different baseline is chosen using haplo.glm.control.
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. Score tests for association of traits with haplotypes when linkage phase is ambiguous. Amer J Hum Genet. 70 (2002): 425-434.
Lake S, LH, Silverman E, Weiss S, Laird N, Schaid DJ. Estimation and tests of haplotype-environment interaction when linkage phase is ambiguous. Human Heredity. 55 (2003): 56-65
haplo.em,
haplo.score,
haplo.group,
haplo.score.merge,
haplo.glm
print.haplo.cc
# For a genotype matrix geno.test, case/control vector y.test
# The function call will be like this
# cc.test <- haplo.cc(y.test, geno.test, locus.label=locus.label, haplo.min.count=3, ci.prob=0.95)
#
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