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run_edgeR <- function(counts, conds, cutoff, n, runID) {
# Preparing variables for edgeR run
d <- DGEList(counts = counts, group = conds)
d = calcNormFactors(d, method = "TMM")
d = estimateCommonDisp(d)
de.com = exactTest(d)
options(digits = 4)
detags.com = rownames(topTags(de.com)$table)
all <- topTags(de.com, n = nrow(counts))$table
good = sum(all$PValue < cutoff)
goodList = topTags(de.com, n = good)
# Preparing results to return
result <- new("Result")
result@data <- all[order(as.numeric(all$PValue)), ]
result@id <- rownames(result@data)
result@pval <- result@data$PValue
result@de <- d$common.dispersion
return(result)
}
run_edgeR_uqn <- function(counts, conds, cutoff, n, runID) {
d <- DGEList(counts = counts, group = conds)
d = calcNormFactors(d, method = "upperquartile")
d = estimateCommonDisp(d)
de.com = exactTest(d)
options(digits = 4)
detags.com = rownames(topTags(de.com)$table)
all <- topTags(de.com, n = nrow(counts))$table
good = sum(all$PValue < cutoff)
goodList = topTags(de.com, n = good)
# Preparing results to return
result <- new("Result")
result@data <- all[order(as.numeric(all$PValue)), ]
result@id <- rownames(result@data)
result@pval <- result@data$PValue
return(result)
}
run_edgeR_Mode <- function(counts, conds, cutoff, n, runID, winSize) {
d <- DGEList(counts = normalizeData(counts, conds, runID,
winSize)$normCounts, group = conds)
d$samples$norm.factors <- rep(1, length(conds))
d = estimateCommonDispMode(d)
de.com = exactTestMode(d)
options(digits = 4)
detags.com = rownames(topTags(de.com)$table)
all <- topTags(de.com, n = nrow(counts))$table
good = sum(all$PValue < cutoff)
goodList = topTags(de.com, n = good)
# Preparing results to return
result <- new("Result")
result@data <- all[order(as.numeric(all$PValue)), ]
result@id <- rownames(result@data)
result@pval <- result@data$PValue
return(result)
}
run_edgeR_nde <- function(counts, DElist, conds, cutoff, n, runID) {
# Preparing variables for edgeR run
d <- DGEList(counts = normalizeNDE(counts, DElist, runID)$normCounts,
group = conds)
d$samples$norm.factors <- rep(1, n * 2)
# d$samples$norm.factors <- normFactors; d =
# calcNormFactors(d);
d = estimateCommonDispMode(d)
de.com = exactTestMode(d)
options(digits = 4)
detags.com = rownames(topTags(de.com)$table)
all <- topTags(de.com, n = nrow(counts))$table
good = sum(all$PValue < cutoff)
goodList = topTags(de.com, n = good)
# Preparing results to return
result <- new("Result")
result@data <- all[order(as.numeric(all$PValue)), ]
result@id <- rownames(result@data)
result@pval <- result@data$PValue
return(result)
}
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