voomgls_CAR1 | R Documentation |
This function run general linear model with corCAR1
correlation structure in function gls
for all genes where
the input data come from the output of voom
.
voomgls_CAR1(
v,
Subject,
Time,
ncores = 1,
C.matrix,
beta0 = NULL,
print.progress = FALSE
)
v |
output of |
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 |
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 |
print.progress |
logical indicator, TRUE or FALSE, to print the progress. |
a data frame has G rows (= number of genes) containing all outputs from
glsCAR1
function, shrinkage estimates of error variances, and
F-type test statistics calculated by teststat
function.
data(res)
data(covset)
v <- res$ori.res$v
v$E <- v$E[1:50,]
v$weights <- v$weights[1:50,]
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, levels = design)
C.matrix[[3]] <- limma::makeContrasts(time6, levels = design)
C.matrix[[4]] <- limma::makeContrasts(time24, levels = design)
C.matrix[[5]] <- limma::makeContrasts(linetime2, levels = design)
C.matrix[[6]] <- limma::makeContrasts(linetime6, levels = design)
C.matrix[[7]] <- limma::makeContrasts(linetime24, levels = design)
C.matrix[[8]] <- limma::makeContrasts(time2, time6, time24, levels = design)
C.matrix[[9]] <- limma::makeContrasts(linetime2,linetime6, linetime24, levels = design)
names(C.matrix) <- c("line2", "time2", "time6", "time24",
"linetime2", "linetime6", "linetime24",
"time", "int")
beta0 <- NULL
print.progress <- FALSE
voomglsout <- rmRNAseq:::voomgls_CAR1(v, Subject, Time, ncores,
C.matrix, beta0, print.progress)
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