voomgls_Symm: General Linear Model Using Voom Output corSymm correlction...

Description Usage Arguments Value Examples

View source: R/TC_CAR1.R

Description

This function run general linear model with corSymm correlation structure in function gls for all genes where the input data come from the output of voom.

Usage

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voomgls_Symm(v, Subject, Time, ncores = 1, C.matrix = NULL,
  beta0 = NULL, print.progress = FALSE)

Arguments

v

output of voom function.

Subject

a vector of subjects or experimental units.

Time

a vector of time points.

ncores

number of cores for embarrassingly parallel procedure. Default value of ncores is 1.

C.matrix

is a list of matrix Ci in testing H0: Ci*beta = 0.

beta0

vector of the hypothesized value of beta, usually, beta0 is a 0 vector. The default option beta0 = NULL means that beta0 is a vector of 0.

print.progress

logical indicator, T or F, to print the progress.

Value

a data frame has G rows (= number of genes) containing all outputs from glsSymm function, shrinkage estimates of error variances, and F-type test statistics calculated by teststat function.

Examples

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data(res)
data(covset)
v <- res$ori.res$v
v$E <- v$E[1:20,]
v$weights <- v$weights[1:20,]
Subject <- covset$ear
Time <- covset$time
ncores <- 1
C.matrix <- list()
C.matrix[[1]] <- limma::makeContrasts(line2, levels = design)
C.matrix[[2]] <- limma::makeContrasts(time2, time6, time24, levels = design)
names(C.matrix) <- c("line2", "time")
beta0 <- NULL
print.progress <- FALSE
voomglsout <- rmRNAseq:::voomgls_Symm(v, Subject, Time, ncores, C.matrix, beta0, print.progress)

rmRNAseq documentation built on Nov. 8, 2019, 5:06 p.m.