Dear DESeq2 users,
I’m completely new to transcriptome analyses, and I’ve neither used R or DESeq2 before, so I apologize for the probably basic question...
I luckily managed to install & run the DESeq2 package with my own samples by using the "default" settings from the vignette.
Now I’d like to turn off Cook’s distance testing (by using the argument “cooksCutoff=FALSE”), but here is where I’m stuck: no matter what I try I get the error “unused argument (cooksCutoff = FALSE)”.
Here’s the script I’m using for the “default” analysis of my samples:
# Counts-Matrix
CountTableAC <- read.table("CountTableAC.txt", header=TRUE, row.names=1)
head(CountTableAC)
# column information as data.frame
DesignAC <- data.frame(
row.names = colnames( CountTableAC ),
condition = c( "A", "A", "C", "C" ) )
DesignAC
dds <- DESeqDataSetFromMatrix(countData = CountTableAC,
colData = DesignAC,
design = ~ condition)
colData(dds)$condition <- factor(colData(dds)$condition,
levels=c("A","C" ))
dds
#Differential Expression Analysis:
dds <- DESeq(dds)
res <- results(dds)
res <- res[order(res$padj),]
head(res)
plotMA(dds,ylim=c(-2,2),main="DESeq2")
Can anyone please tell me exactly where and what to change to disable Cook’s testing?
Thanks a lot for any advice!
Nelala
I’m completely new to transcriptome analyses, and I’ve neither used R or DESeq2 before, so I apologize for the probably basic question...
I luckily managed to install & run the DESeq2 package with my own samples by using the "default" settings from the vignette.
Now I’d like to turn off Cook’s distance testing (by using the argument “cooksCutoff=FALSE”), but here is where I’m stuck: no matter what I try I get the error “unused argument (cooksCutoff = FALSE)”.
Here’s the script I’m using for the “default” analysis of my samples:
# Counts-Matrix
CountTableAC <- read.table("CountTableAC.txt", header=TRUE, row.names=1)
head(CountTableAC)
# column information as data.frame
DesignAC <- data.frame(
row.names = colnames( CountTableAC ),
condition = c( "A", "A", "C", "C" ) )
DesignAC
dds <- DESeqDataSetFromMatrix(countData = CountTableAC,
colData = DesignAC,
design = ~ condition)
colData(dds)$condition <- factor(colData(dds)$condition,
levels=c("A","C" ))
dds
#Differential Expression Analysis:
dds <- DESeq(dds)
res <- results(dds)
res <- res[order(res$padj),]
head(res)
plotMA(dds,ylim=c(-2,2),main="DESeq2")
Can anyone please tell me exactly where and what to change to disable Cook’s testing?
Thanks a lot for any advice!
Nelala
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