intern.select: Internal function

In rauschenberger/globalSeq: Global Test for Counts

Description

Communicates between cursus and omnibus by selecting the covariates of interest.

Usage

intern.select(i, Y, Ystart, Yend, X, Xloc,
             window, offset, group,
             perm, phi, kind)

Arguments

i	index
Y	RNA-Seq data: numeric matrix with q rows (genes) and n columns (samples); or a SummarizedExperiment object
Ystart	location (or start location)
Yend	location (or end location)
X	genomic profile: numeric matrix with p rows (covariates) and n columns (samples)
Xloc	location covariates: numeric vector of length p
window	maximum distance: non-negative real number
offset	numeric vector of length n
group	confounding variable: factor of length n
perm	number of iterations: positive integer
phi	dispersion parameters: vector of length q
kind	computation : number between 0 and 1

Value

The function returns a dataframe, with the p-value in the first column, and the test statistic in the second column.

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)

See Also

This is an internal function. The user functions are cursus, omnibus, and proprius.

Examples

# simulate high-dimensional data
n <- 30
q <- 10
p <- 100
set.seed(1)
Y <- matrix(rnbinom(q*n,mu=10,
    size=1/0.25),nrow=q,ncol=n)
X <- matrix(rnorm(p*n),nrow=p,ncol=n)
Yloc <- seq(0,1,length.out=q)
Xloc <- seq(0,1,length.out=p)
window <- 1

# hypothesis testing
cursus(Y,Yloc,X,Xloc,window)

rauschenberger/globalSeq documentation built on May 19, 2020, 4:09 a.m.