Go Back   SEQanswers > Bioinformatics > Bioinformatics

Similar Threads
Thread Thread Starter Forum Replies Last Post
DESeq2 without biol replicates sisterdot Bioinformatics 23 02-24-2019 09:01 AM
DESeq2 Simon Anders Bioinformatics 123 07-06-2015 02:45 AM
DESeq V DESeq2 sebastion RNA Sequencing 35 10-16-2014 07:04 AM
Error Message in nbinomLRT in DESeq2 ToddB Bioinformatics 13 09-05-2013 07:22 AM
Venn diagram type analysis of ~6 conditions Noa Bioinformatics 1 05-10-2012 08:01 PM

Thread Tools
Old 08-21-2013, 01:08 AM   #1
Junior Member
Location: Germany

Join Date: Aug 2013
Posts: 2
Default DESeq2: Difference between condition+type vs. 3 conditions

Dear all.

I am unsure about how to use DESeq2 in the case of 3 conditions vs. 2 conditions + 2 types. Assuming I have the following design table
          condition    type
sample1   A            T1
sample2   A            T1
sample3   B            T2
sample4   B            T2
sample5   A            T2
sample6   A            T2
I am unsure about how this would be treated differently from
sample1   A:T1
sample2   A:T1
sample3   B:T2
sample4   B:T2
sample5   A:T2
sample6   A:T2
The second design table describes a 3-condition scenario.

Now, obviously one would be interested in a detailed analysis of the counts for
  1. A:T2 vs. B:T2 (since they have the same type but a different conditions), and potentially
  2. A:T2 vs. A:T1 (since they have the same condition but different types).

Question 1: If I reduce the problem to that of a 3-condition no-type design table, is this correctly taken into account?

I know I would have to re-factor the columns of the 2nd matrix to reflect the correct order of fold changes that I want to calculate. So for example following re-factoring the levels as
and performing a DESeq2 analysis
dds<-DESeqDataSetFromMatrix(countData = countData, colData = design, design = ~ condition + type);
Question 2: I could calculate the fold changes of B:T2 wrt A:T2 and A:T1 wrt A:T2, is this correct?
I do get some issues with non-convergent dispersion fits, which I can get around if I call estimateDispersions manually with fitType="local".

Question 3: But what happens in the case of the 1st condition+type table? I am confused as to the output of DESeq2. What role does the type play in the differential expression analysis and/or the dispersion fitting?

Any help on this issue would be greatly appreciated.


Last edited by mevers; 08-22-2013 at 02:38 AM. Reason: Typo
mevers is offline   Reply With Quote
Old 08-22-2013, 01:39 AM   #2
Simon Anders
Senior Member
Location: Heidelberg, Germany

Join Date: Feb 2010
Posts: 994

In your first table, the type is always the same. Is this a typo? If not, I'm not sure I understand your question.
Simon Anders is offline   Reply With Quote
Old 08-22-2013, 02:35 AM   #3
Junior Member
Location: Germany

Join Date: Aug 2013
Posts: 2

Hi Simon.

Yes, that was a silly mistake, you are absolutely right. I've changed it now in the original post. It should have read
mevers is offline   Reply With Quote
Old 09-02-2013, 02:17 AM   #4
Michael Love
Senior Member
Location: Boston

Join Date: Jul 2013
Posts: 333

Question 1:

You can technically represent it either way, although I would recommend to keep the variables separate for the following reason: if you combined the variables (as in "A:T1"), then you cannot make a clean B vs A comparison. Instead you have a B:T2 vs A:T1 comparison which mixes the effect of B vs A and T2 vs T1.

Question 2:

Note that fitType is also an argument for DESeq()

Question 3:

Both variables are used for finding fitted means (mu in the GLM formula given in the reference manual and vignette). And then the fitted means mu is used to estimate the dispersion. Dispersion is a measure of how far the counts deviate from the mu for that sample. Both variables will have fitted coefficients (betas in the GLM formula) and you can extract tests for each variable of the null hypothesis that the coefficients are equal to zero. By default the results for the last variable is provided by results(). For more, see the section in the vignette on "Multi-factor designs" and the man page for results().
Michael Love is offline   Reply With Quote

deseq, deseq2

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

All times are GMT -8. The time now is 02:55 PM.

Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2021, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO