intern.sam: Internal function

Description Usage Arguments Value References See Also Examples

View source: R/internal_functions.R

Description

These functions calculate the contribution of covariate or samples to the test statistic. They are called by the function proprius.

Usage

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intern.sam(y, X, mu, phi)

intern.cov(y, X, mu, phi)

Arguments

y

response variable: numeric vector of length n

X

covariate set: numeric matrix with n rows (samples) and p columns (covariates)

mu

mean parameters: numeric vector of length n

phi

dispersion parameter: non-negative real number

Value

Both functions return a numeric vector.

References

A Rauschenberger, MA Jonker, MA van de Wiel, and RX Menezes (2016). "Testing for association between RNA-Seq and high-dimensional data", BMC Bioinformatics. 17:118. html pdf (open access)

JJ Goeman, SA van de Geer, F de Kort, and HC van Houwelingen (2004). "A global test for groups of genes: testing association with a clinical outcome", Bioinformatics. 20:93-99. html pdf (open access)

See Also

This is an internal function. The user functions of the R package globalSeq are cursus, omnibus, and proprius.

Examples

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# simulate high-dimensional data
n <- 30
p <- 100
set.seed(1)
y <- rnbinom(n,mu=10,size=1/0.25)
X <- matrix(rnorm(n*p),nrow=n,ncol=p)

# prepare arguments
mu <- rep(mean(y),n)
phi <- (var(y)-mean(y))/mean(y)^2 

# decompose test statistic
intern.sam(y,X,mu,phi)
intern.cov(y,X,mu,phi)

globalSeq documentation built on Nov. 8, 2020, 7:22 p.m.