Package 'CHAPGWAS'

RANDOM: Mixed model and haplotype random effect test

Description

Internal core function used in SEL.HAP() to fit mixed models and test the random effect of a haplotype design matrix z.

Usage

RANDOM(z, YFIX, KIN, PAR)

Arguments

z	Haplotype design matrix (n x r). When PAR is NULL, z can be NULL and the function only estimates variance components in the mixed model.
YFIX	A data.frame or matrix with phenotype in the first column and fixed-effect covariates in the remaining columns.
KIN	A list of kinship matrices.
PAR	Optional vector of (log) variance components. If NULL, they are estimated by the internal mixed model.

Value

If PAR is NULL, returns the estimated parameters (vector). Otherwise returns a list with likelihood ratio test statistics and parameter estimates.

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SEL.HAP: Haplotype selection and extension along the genome

Description

Perform genome-wide haplotype selection and extension using the CHAP-GWAS framework. The function scans along each chromosome, builds local haplotype segments, and adaptively extends them based on association evidence with the phenotype.

Usage

SEL.HAP(GEN, YFIX, KIN, nHap, p.threshold, PAR)

Arguments

GEN	Genotype matrix with rows corresponding to markers and columns corresponding to individuals. The first two columns give chromosome (chr) and physical position (pos); the remaining columns contain alleles for each individual (e.g. "A", "C", "G", "T"), one allele per haplotype copy.
YFIX	A matrix or data.frame with phenotype in the first column and fixed-effect covariates (e.g. intercept, PCs) in the remaining columns, one row per individual.
KIN	A list of kinship matrices, each of dimension $n \times n$, where $n$ is the number of individuals.
nHap	Initial haplotype window size (number of consecutive markers).
p.threshold	P-value threshold for haplotype extension.
PAR	Optional variance component parameters passed to RANDOM(). If NULL, they are estimated internally.

Value

A list of three matrices summarizing:

• FINAL[[1]]: initial haplotype segments

• FINAL[[2]]: extended haplotype segments

• FINAL[[3]]: final selected segments after extension

Examples

## Minimal example with small simulated data (alleles encoded as A/C/G/T)
set.seed(1)

## Number of individuals and markers
n_ind  <- 200
n_mark <- 50

## Construct a simple GEN matrix:
## first two columns: chromosome and position
## each individual is represented by two allele columns (A1/A2)
chr <- rep(1, n_mark)
pos <- seq_len(n_mark) * 100
alleles <- c("A", "C", "G", "T")

geno <- matrix(NA_character_, nrow = n_mark, ncol = 2 * n_ind)
for (m in seq_len(n_mark)) {
  a <- sample(alleles, 2, replace = FALSE)   # biallelic per marker
  geno[m, ] <- sample(a, 2 * n_ind, replace = TRUE)
}

colnames(geno) <- as.vector(rbind(
  paste0("id", seq_len(n_ind), "_A1"),
  paste0("id", seq_len(n_ind), "_A2")
))

GEN <- cbind(chr, pos, geno)

## Phenotype + intercept as fixed effect
y <- rnorm(n_ind)
X <- cbind(1, rnorm(n_ind))  # intercept + one covariate
YFIX <- cbind(y, X)

## Simple kinship: identity matrix
KIN <- list(diag(n_ind))

## Run SEL.HAP with a small initial window and mild threshold
res <- SEL.HAP(GEN, YFIX, KIN,
               nHap = 2,
               p.threshold = 0.05,
               PAR = NULL)

## Inspect the structure of the result (three matrices)
str(res)

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test.HAP: Test haplotype effects for a local region

Description

test.HAP: Test haplotype effects for a local region

Usage

test.HAP(HAP.X, YFIX, KIN, PAR)

Arguments

HAP.X	Haplotype genotype matrix for a candidate genomic region. Each column corresponds to a SNP within the region. Every two consecutive rows correspond to the two homologous haplotypes of the same individual (rows 1–2 = individual 1, rows 3–4 = individual 2, etc.).
YFIX	Phenotype and fixed-effect covariates.
KIN	List of kinship matrices.
PAR	Optional vector of variance components; if NULL, estimated internally.

Value

A list containing: * my.scan – scan statistics * z – haplotype design matrix (n x number of haplotypes) * ELEMENT – labels of distinct haplotype categories

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