#' Pipeline function for neuronal prediction with RBP sepcific exons
#'
#' @param data input splicing matrix with NA and extreme value replaced
#' @return data.frame with Predicated maturation stage and Predication confidence score
#' @export
#'
#' @examples
rbp.predict <- function(data) {
rbp <- 6:9
res <- data.frame(matrix("", ncol = 0, nrow = ncol(data)), stringsAsFactors = F)
rownames(res) <- colnames(data)
for (idx in rbp) {
rbp.bn <- subset(rbpAll.bn, rbpAll.bn[, idx] != 0)
rbp.bn <- rbp.bn[order(rbp.bn[, idx]), ]
rbp.tissue.Smodule <- data[match(rbp.bn$name, rownames(data), nomatch = 0), ]
devcortex.rbp.Smodule2 <- devcortex.Smodule2[match(rbp.bn$name, rownames(devcortex.Smodule2),
nomatch = 0), ]
# rbp.tissue.Smodule2 <- na.replace(rbp.tissue.Smodule)
tmp.res <- rbp.beta.predict(rbp.tissue.Smodule, devcortex.rbp.Smodule2)
colnames(tmp.res) <- c(paste(colnames(rbpAll.bn)[idx], "Maturation", sep = ""), paste(colnames(rbpAll.bn)[idx],
"ConfidenceScore", sep = ""))
res <- cbind(res, tmp.res)
}
res <- as.data.frame(lapply(res, as.numeric))
rownames(res) <- colnames(data)
newcolnames<- c("PtbpMaturation", "PtbpConfidenceScore", "NovaMaturation", "NovaConfidenceScore", "RbfoxMaturation", "RbfoxConfidenceScore", "MbnlMaturation", "MbnlConfidenceScore")
res <- res[, match(newcolnames, colnames(res))]
res
}
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