Hi
I want to use the DESEQ package between a control (3 biological replicates) and treatment (1 biological replicate).
IN DESeq I herefore used the following code, and got 266 genes with padj < 0.05:
table <- read.delim("test.txt")
row.names(table) <- table$Feature_ID
count_table <- table[, -1]
conds <- c("ctrl", "ctrl", "ctrl", "treatment")
cds <- newCountDataSet(count_table, conds)
cds <- estimateSizeFactors(cds)
cds <- estimateDispersions(cds, method="blind", sharingMode="fit-only")
results <- nbinomTest(cds, "ctrl", "treatment")
In DESeq2 I used the follwing command, but got > 10000 genes with padj < 0.05:
table <- read.delim("test.txt")
row.names(table) <- table$Feature_ID
count_table <- table[, -1]
colData <- DataFrame(condition=factor(c("ctrl", "ctrl", "ctrl", "treatment")))
dds <- DESeqDataSetFromMatrix(count_table, colData, formula(~ condition))
results <- DESeq(dds, minReplicatesForReplace=Inf)
So probably I need to add extra parameters to the DESEQ2 analysis but for now I can't figure out how?
Thank you for helping
Wannes
What is your basis for assuming that you need to add extra parameters to your DESeq2 pipeline?