Nothing
`SBL` <-
function (x, sigma2, aAlpha=0.2, estim.sigma2 = FALSE, maxit = 10000,
tol = 1e-08, verbose = FALSE, saveInfo = TRUE)
{
if (!inherits(x, "setupGADA"))
stop("object must be of class 'setupGADA' ")
if (missing(sigma2) & !estim.sigma2)
stop("parameter 'sigma2' is missing. \n It can be estimated using estim.sigma2=TRUE")
if (estim.sigma2)
sigma2 <- -1
gen.info <- attr(x, "gen.info")
debug <- ifelse(verbose, 1, 0)
x$log.ratio[is.na(x$log.ratio)] <- 0 # RPR we finaly use this to deal with the NA?
if (is.null(gen.info)) {
out <- list()
y <- x$log.ratio
M <- length(y)
if (sigma2 < 0) {
sigma2 <- 0.5 * mean(diff(y)^2, trim = 0.01)
cat(" The estimated sigma2 =", sigma2, "\n")
}
out <- SBL.fit(0, y, NULL, NULL, NULL, sigma2, aAlpha,
maxit, tol, debug)
}
else {
chr <- unique(gen.info$chr)
chr <- chr[!is.na(chr)]
control <- 1:nrow(gen.info)
if (sigma2 < 0) {
sigma2 <- 0
totalM <- 0
if (length(chr) > 22)
n.chr <- 22
else n.chr <- length(chr)
for (i in 1:n.chr) {
# Changed to control missing data, JRG
# selec <- control[gen.info$chr == chr[i]]
tt<-gen.info$chr==chr[i]
tt<-tt[!is.na(tt)] # RPR: What is this doing?
selec <- control[tt]
y <- x$log.ratio[selec]
M <- length(y)
totalM <- totalM + (M - 1)
sigma2 <- sigma2 + (M - 1) * 0.5 * mean(diff(y)^2,
trim = 0.01)
}
sigma2 <- sigma2/totalM
cat(" The estimated sigma2 =", sigma2, "\n")
}
out <- lapply(1:length(chr), SBL.fit, x = x$log.ratio,
control = control, gen.info = gen.info, chr = chr,
sigma2 = sigma2, aAlpha = aAlpha, maxit = maxit,
tol = tol, debug = debug)
attr(out, "chr") <- chr #RPR I moved this line inside here bc if no gen
}
# RPR Potential BUG!!! Do we also account for the removed NA probes in the plots?
attr(out, "data") <- x$log.ratio
if (saveInfo) {
attr(out, "gen.info") <- attr(x, "gen.info")
}
class(out) <- "SBL"
out
}
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