## load genome description
data(hgA)
## partition genome into overlapping windows
windows <- partitionRegions(hgA)
## load genotype data from VCF file
vcfFile <- system.file("examples/example1.vcf.gz", package="podkat")
Z <- readGenotypeMatrix(vcfFile)
## read phenotype data from CSV file (continuous trait + covariates)
phenoFile <- system.file("examples/example1lin.csv", package="podkat")
pheno <-read.table(phenoFile, header=TRUE, sep=",")
## train null model with all covariates in data frame 'pheno'
nm.lin <- nullModel(y ~ ., pheno)
## perform association test for multiple regions
res <- assocTest(Z, nm.lin, windows)
## perform multiple testing correction
res.adj <- p.adjust(res)
print(res.adj)
## show sorted results
as(sort(res.adj), "GRanges")
## show filtered result
print(filterResult(res.adj, cutoff=0.05, filterBy="p.value.adj"))
## make a Manhattan plot
plot(res.adj, which="p.value.adj")
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