haplo.stats (version 1.2.1)

haplo.cc: Haplotype Association Analysis in a Case-Control design

Description

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.

Usage

haplo.cc(y, geno, haplo.min.count=5, locus.label=NA, ci.prob=0.95, miss.val=c(0,NA),
                     simulate=FALSE, sim.control=score.sim.control(),
                     control=haplo.glm.control())

Arguments

y

Vector of trait values, must be 1 for cases and 0 for controls.

geno

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.

haplo.min.count

The minimum number of expected counts for a haplotype in the sample based on estimated frequencies.

ci.prob

Probability level for confidence interval on the Odds Ratios of each haplotype to span the true value.

locus.label

Vector of labels for loci, of length K (see definition of geno matrix)

miss.val

Vector of codes for missing values of alleles

simulate

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.

sim.control

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.

control

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.

Value

• 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:
• haplotypes
  The first K columns contain the haplotypes used in the analysis.
• Hap-Score
  Score statistic for association of haplotype with the binary trait.
• p-val
  P-value for the haplotype score statistic, based on a chi-square distribution with 1 degree of freedom.
• sim.p.val
  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).
• pool.hf
  Estimated haplotype frequency for cases and controls pooled together.
• control.hf
  Estimated haplotype frequency for control group subjects.
• case.hf
  Estimated haplotype frequency for case group subjects.
• glm.eff
  The haplo.glm function modeled the haplotype effects as: baseline (Base), additive haplotype effect (Eff), or rare haplotypes pooled into a single group (R).
• OR.lower
  Lower limit of the Odds Ratio Confidence Interval.
• OR
  Odds Ratio based on haplo.glm model estimated coefficient for the haplotype.
• OR.upper
  Upper limit of the Odds Ratio Confidence Interval.

References

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

Details

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.

See Also

haplo.em, haplo.score, haplo.group, haplo.score.merge, haplo.glm print.haplo.cc

Examples

#  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)
#