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Exporting normalized counts data from DeSeq2

Hi,

I am working with large RNA-Seq dataset downloaded from the NCBI GEO. I would like to export the normalized counts data from DeSeq2 based on size factor normalization for further downstream analysis. It seems like running dds <- DESeq(dds) and dds <- estimateSizeFactors(dds) outputs the same results. Is my understanding correct? Please let me know if I could use any of these to export the normalized counts data.

library("DESeq2")

dds <- DESeqDataSetFromMatrix(countData = round(Counts_data), colData = sample_info, design = ~ Disease_state)


## 1
dds <- estimateSizeFactors(dds)
sizeFactors(dds)
normalized_counts <- counts(dds, normalized=TRUE)
write.csv(normalized_counts, file="normalized_counts.csv")


## 2
dds <- DESeq(dds)
sizeFactors(dds)
normalized_counts_DESeq <- counts(dds, normalized=TRUE)
write.csv(normalized_counts_DESeq, file="normalized_counts_DESeq.csv")

Created on 2021-09-20 by the [reprex package][1] (v2.0.1)

Thank you,
Toufiq

deseq2 normalization expression rna-seq
• 5,381 views • link
updated by Ram Ram • written by mohammedtoufiq91 mohammedtoufiq91

1 answer

It is the same:

> set.seed(1)
> dds <- makeExampleDESeqDataSet()
> all(counts(DESeq(dds), normalized=TRUE) == counts(estimateSizeFactors(dds), normalized=TRUE))
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
[1] TRUE

estimateSizeFactors runs as part of DESeq as, see the manual,

https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#what-are-the-exact-steps-performed-by-deseq

and ?DESeq:

(...)
This function performs a default analysis through the steps:

estimation of size factors: estimateSizeFactors

estimation of dispersion: estimateDispersions

Negative Binomial GLM fitting and Wald statistics: nbinomWaldTest
(...)
• 0 views • link
written by ATpoint ATpoint

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