<p>Typical tools to use for this would be the DEXseq packages (<a href="https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/0471142905.hg1116s87" rel="nofollow noreferrer">as done here</a>) or <a href="http://rnaseq-mats.sourceforge.net/" rel="nofollow noreferrer">rMATS</a>, which will calculate intron retention rates.</p>

<p>I would generally suggest not summing intronic counts by gene and using that in DESeq2 (I assume that's what you meant by DESeq, since there's no reason to use the original DESeq for anything). What you'd be getting if you did this is less expressed introns and more sample-specific bias in enriching for mature versus pre-mRNA.</p>

CC BY-SA 4.0
2018-05-03T08:16:53.097Z
Thank you Ryan. Yeah, I will use either DEXseq or rMATS in that case.
jagat shrestha
CC BY-SA 4.0
2018-05-02T12:33:42.243Z
2018-05-02T12:33:42.243Z
Devon Ryan
<p>I have used Deseq for estimating the differentially expressed introns for the RNA seq data using the UCSC intron bed file. can Deseq be used for differentially expressed intron analysis?</p>

CC BY-SA 4.0
2018-05-02T13:49:24.877Z
Welcome to the site. You write Deseq in the question but you tagged with deseq2 (of the DEseq2 package). Which one do you really use? Also if you did it can be used, but it seems like you have problems with the results or something, if this is the case, you will need to provide more of information like the relevant part of the code used
llrs
<rna-seq><deseq2><ucsc>
differentially expressed intron analysis?
# differentially expressed intron analysis?

(Asked by: username_0 on 2018-05-02)

I have used Deseq for estimating the differentially expressed introns for the RNA seq data using the UCSC intron bed file. can Deseq be used for differentially expressed intron analysis?

**Tags:** rna-seq, deseq2, ucsc
> **Comments:**
> **username_1**: Welcome to the site. You write Deseq in the question but you tagged with deseq2 (of the DEseq2 package). Which one do you really use? Also if you did it can be used, but it seems like you have problems with the results or something, if this is the case, you will need to provide more of information like the relevant part of the code used  

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## 1 answers

### Answer by username_2 on 2018-05-02. Score: 2

Typical tools to use for this would be the DEXseq packages ([as done here](https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/0471142905.hg1116s87)) or [rMATS](http://rnaseq-mats.sourceforge.net/), which will calculate intron retention rates.

I would generally suggest not summing intronic counts by gene and using that in DESeq2 (I assume that's what you meant by DESeq, since there's no reason to use the original DESeq for anything). What you'd be getting if you did this is less expressed introns and more sample-specific bias in enriching for mature versus pre-mRNA.

> **Comments:**
> **username_0**: Thank you Ryan. Yeah, I will use either DEXseq or rMATS in that case.  

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