the results from normalized=TRUE and normalized = FALSE is the same
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Kai_Qi ▴ 10
@kai_qi-22237
Last seen 12 days ago
Chicago, IL, United States

Hi:

I am going through the tutorial of DESEQ2 published on F1000. In the step of rlog transformation I have done following operation:

dds <- DESeqDataSet(se, design = ~cell + dex)
dds <- dds[rowSums(counts(dds))>1,]
f1<- plot(log2(counts(dds, normalized=FALSE)[,1:2] + 1), pch=16, cex=0.3)
dds <- estimateSizeFactors(dds)
f2 <- plot(log2(counts(dds, normalized=TRUE)[, 1:2] + 1),
     pch=16, cex=0.3)
all(f1 ==f2)

And the result is:

> all(f1 ==f2)
[1] TRUE

In this case, what is the point of "normalization" here? I know this might not related to the tutorial, but i am eager to get understand what each step means, any answer is appreciated!

R deseq2 • 139 views
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@mikelove
Last seen 10 hours ago
United States

You are testing equivalence on the plot() output it looks like.

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Thank you for the answer. Does plot() equal mean the input is equal?

(I use == to test is because i see the image looks same)

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No.

> x <- plot(1)
> y <- plot(2)
> x
NULL
> y
NULL
> x == y
logical(0)
> all(x == y)
[1] TRUE

These aren't really questions related to Bioconductor software though, which is the purpose of this site, so you may want to look up some help on use of R for data analysis.

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Thank you so much for kind answer.

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Thank you so much for kind answer.

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