Description Usage Arguments Value Examples
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
.
1 2 | voomgls_Symm(v, Subject, Time, ncores = 1, C.matrix = NULL,
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, T or F, to print the progress. |
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | 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)
|
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