lmQtc: Fitting a Linear Model to QTCs

In QTCAT/qtcat: Quantitative Trait Cluster Association Test

Description

Linear model between phenotype and medoids of QTCs (significant SNP clusters).

Usage

lmQtc(object, pheno, geno, alpha = 0.05, min.absCor = 0.05)

Arguments

object	an object of class qtcatHit.
pheno	an object of class qtcatPheno.
geno	an object of class qtcatGeno.
alpha	an alpha level for significance estimation.
min.absCor	minimum absolute value of correlation considered.

Examples

# If you want to run the examples, use:
# example(lmQtc, run.dontrun = TRUE)
## Not run: 
# files containing example data for SNP data and the phenotype
pfile <- system.file("extdata/phenodata.csv", package = "qtcat")
gfile <- system.file("extdata/snpdata.csv", package = "qtcat")
pdat <- read.csv(pfile, header = TRUE)
snp <- read.snpData(gfile, sep = ",")
clust <- qtcatClust(snp)
geno <- qtcatGeno(snp, clust)
pheno <- qtcatPheno(names = pdat[, 1],
                    pheno = pdat[, 2],
                    covariates = model.matrix(~ pdat[, 3]))
fitted <- qtcatHit(pheno, geno)

# fitting a LM to the phenotype and QTC medoids
lmfitted <- lmQtc(fitted, pheno, geno)

## End(Not run)

QTCAT/qtcat documentation built on April 20, 2021, 11:20 p.m.