Nothing
library(Biobase)
data("sultan")
conds <- pData(sultan)$cell.line
########################################################################
## Matrix or data.frame
########################################################################
## Filter genes with total (sum) normalized gene counts < 10
filter <- HTSBasicFilter(exprs(sultan), method="sum", cutoff.type="value",
cutoff = 10)
########################################################################
## DGEExact
########################################################################
library(edgeR)
## Filter genes with CPM values less than 100 in more than 2 samples
dge <- DGEList(counts=exprs(sultan), group=conds)
dge <- calcNormFactors(dge)
filter <- HTSBasicFilter(dge, method="cpm", cutoff.type=2, cutoff=100)
########################################################################
## DESeq2
########################################################################
library(DESeq2)
conds <- gsub(" ", ".", conds)
dds <- DESeqDataSetFromMatrix(countData = exprs(sultan),
colData = data.frame(cell.line = conds),
design = ~ cell.line)
## Not run: Filter genes with mean normalized gene counts < 40% quantile
## dds <- DESeq(dds)
## filter <- HTSBasicFilter(dds, method="mean", cutoff.type="quantile",
## cutoff = 0.4)
## res <- results(filter, independentFiltering=FALSE)
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