Deseq2 normalization steps
1
0
Entering edit mode
@santamariagianluca-17739
Last seen 2.0 years ago
Italy

Hi Michael,

I got some question about the tutorial of DESeq2 and I was wondering if you could help me in:

1) normalized metric you use in Deseq is not referring to RPKM or TPKM, but: "counts divided by sample-specific size factors determined by median ratio of gene counts relative to geometric mean per gene" or median of ratio.. so 1) creates a pseudo-reference sample (row-wise geometric mean), 2) calculates ratio of each sample to the reference, 3) calculate the normalization factor for each sample (size factor), 4)calculate the normalized count values using the normalization factor. is that correct?

2) Once I got the DEGs list and I want to take into account whether these differentially transcripts tend to be smaller or larger in transcript size.. I should go back to salmon or kallisto (correct?) approach and run again the analysis or there is a way to get this info out ?

thanks in advance G.

deseq2 normalization • 1.6k views
ADD COMMENT
3
Entering edit mode
@mikelove
Last seen 17 hours ago
United States

1) Yes

2) If you want to see if the DE genes tend to be smaller or larger in transcript length, you can do the following, just a simple example...

res$length <- rowMeans(assay(dds)[["avgTxLength"]])
table(sig=res$padj < .05, length=cut(log10(res$length), 5))

This assumes you used a tximport pipeline.

ADD COMMENT
0
Entering edit mode

Hi Michael,

I got a normalised_rlog_transformed_counts.txt file from a company which means I do have my data already normalized and rlog transformed. Is there a way to import the data as CountDataset and use all the function in Deseq2 including the DEGs analysis ?

Thanks a lot in advance G.

ADD REPLY
0
Entering edit mode

Not really.

ADD REPLY

Login before adding your answer.

Traffic: 653 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6