Nothing
run_NOISeq <- function(counts, conds, cutoff, n, runID) {
# Preparing variables for NOISeq run
NR1 = length(conds[conds == "N"])
NR2 = length(conds[conds == "T"])
mydata <- readData(counts, cond1 = c(1:NR1), cond2 = c((NR1 +
1):(NR1 + NR2)))
rownames(mydata[[1]]) <- rownames(counts)
rownames(mydata[[2]]) <- rownames(counts)
# Running NOISeq
if (n > 1) {
myresults <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "rpkm", q = 0.8)
all <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "rpkm", q = 0)
} else {
myresults <- noiseq(mydata[[2]], mydata[[1]], k = NULL,
norm = "rpkm", q = 0.8, pnr = 0.2, nss = 5, v = 0.02)
all <- noiseq(mydata[[2]], mydata[[1]], k = NULL, norm = "rpkm",
q = 0, pnr = 0.2, nss = 5, v = 0.02)
}
# Preparing results to return
result <- new("Result")
result@data <-
as.data.frame(na.omit(all$probab[order(as.numeric(-all$probab))]))
result@id <- rownames(result@data)
result@pval <- as.numeric(result@data[, 1])
return(result)
} # end run_NOISeq
run_NOISeq_uqn <- function(counts, conds, cutoff, n, runID) {
# Preparing variables for NOISeq run
NR1 = length(conds[conds == "N"])
NR2 = length(conds[conds == "T"])
counts <- UQNnormalization(counts)$normCounts
ind <- apply(counts, 1, mean) > 0
counts <- counts[ind, ]
mydata <- readData(counts, cond1 = c(1:NR1), cond2 = c((NR1 +
1):(NR1 + NR2)))
rownames(mydata[[1]]) <- rownames(counts)
rownames(mydata[[2]]) <- rownames(counts)
# Running NOISeq
if (n > 1) {
myresults <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0.8)
all <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0)
} else {
myresults <- noiseq(mydata[[2]], mydata[[1]], k = NULL,
norm = "n", q = 0.8, pnr = 0.2, nss = 5, v = 0.02)
all <- noiseq(mydata[[2]], mydata[[1]], k = NULL, norm = "n",
q = 0, pnr = 0.2, nss = 5, v = 0.02)
}
# Preparing results to return
result <- new("Result")
result@data <-
as.data.frame(na.omit(all$probab[order(as.numeric(-all$probab))]))
result@id <- rownames(result@data)
result@pval <- as.numeric(result@data[, 1])
return(result)
} # end run_NOISeq_uqn
run_NOISeq_Mode <- function(counts, conds, cutoff, n, runID,
winSize) {
# Preparing variables for NOISeq run
NR1 = length(conds[conds == "N"])
NR2 = length(conds[conds == "T"])
counts <- normalizeData(counts, conds, runID, winSize)$normCounts
ind <- apply(counts, 1, mean) > 0
counts <- counts[ind, ]
mydata <- readData(counts, cond1 = c(1:NR1), cond2 = c((NR1 +
1):(NR1 + NR2)))
rownames(mydata[[1]]) <- rownames(counts)
rownames(mydata[[2]]) <- rownames(counts)
# Running NOISeq
if (n > 1) {
myresults <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0.8)
all <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0)
} else {
myresults <- noiseq(mydata[[2]], mydata[[1]], k = NULL,
norm = "n", q = 0.8, pnr = 0.2, nss = 5, v = 0.02)
all <- noiseq(mydata[[2]], mydata[[1]], k = NULL, norm = "n",
q = 0, pnr = 0.2, nss = 5, v = 0.02)
}
# Preparing results to return
result <- new("Result")
result@data <-
as.data.frame(na.omit(all$probab[order(as.numeric(-all$probab))]))
result@id <- rownames(result@data)
result@pval <- as.numeric(result@data[, 1])
return(result)
} # end run_NOISeq_Mode
run_NOISeq_nde <- function(counts, DElist, conds, cutoff, n,
runID) {
# Preparing variables for NOISeq run
NR1 = length(conds[conds == "N"])
NR2 = length(conds[conds == "T"])
mydata <- readData(normalizeNDE(counts, DElist, runID)$normCounts, cond1 = c(1:NR1),
cond2 = c((NR1 + 1):(NR1 + NR2)))
rownames(mydata[[1]]) <- rownames(counts)
rownames(mydata[[2]]) <- rownames(counts)
# Running NOISeq
if (n > 1) {
myresults <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0.8)
all <- noiseq(mydata[[2]], mydata[[1]], repl = "tech",
norm = "n", q = 0)
} else {
myresults <- noiseq(mydata[[2]], mydata[[1]], k = NULL,
norm = "n", q = 0.8, pnr = 0.2, nss = 5, v = 0.02)
all <- noiseq(mydata[[2]], mydata[[1]], k = NULL, norm = "n",
q = 0, pnr = 0.2, nss = 5, v = 0.02)
}
# Preparing results to return
result <- new("Result")
result@data <-
as.data.frame(na.omit(all$probab[order(as.numeric(-all$probab))]))
result@id <- rownames(result@data)
result@pval <- as.numeric(result@data[, 1])
return(result)
} # end run_NOISeq_nde
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