Dear Michael,

thanks for your instantaneous reply!

>     I hope I can bother you with some questions about your package:
>     1. when analysing for let's say two variables (e.g. ~ type +
>     condition), will this be a difference to change the order of the
>     variables (~ condition + type)? Probably this will do a blocking
>     and hence order is important here similar to edgeR?
>
>
> ​it makes no difference except that the results() function with no 
> arguments will automatically extract results for the last variable in 
> the design formula, and for the last level of this variable over the 
> first level if this variable is a factor.​ But otherwise, no it 
> doesn't make a difference if you are using the arguments of results() 
> to specify which results tables to construct.
>
>     2. For more than 2 variables (e.g. ~type + condition + time) would
>     this be meaning blocking will also be done for the further
>     variables (e.g. type for time)? If I intend no blocking I probably
>     need to do ~ 0 + type + condition + time?
>
>
> ​Yes, adding variables "accounts for" or "controls for" other effects, 
> whether there are 2 variables, 3, 4 etc..​ We do not recommend using 
> the "0" in design formula for DESeq2, because by default we shrink 
> non-intercept effects (see the description of betaPrior in ?DESeq), 
> but we want to have an unshrunken intercept. Can you say more what you 
> mean by "intend no blocking", in my mind, blocking is a property of 
> the experiment.
>

My understanding from working with the edgeR package is, that you can 
consider paired samples or batch effects when comparing two or more 
treatments. Accounting for paired samples seems to be a specific case of 
"blocking" in experimental design. In edgeR doing ~type+condition I can 
retrieve the 'condition' comparison including the correction for the 
paired effect 'type'. Is this also true for DESeq2? And if so, does the 
order matter in the formula e.g.: ~type+condition the same as 
~condition+type?

>
>     3. Is it also possible to study nested effects and other
>     interactions (e.g. condition:time)?
>
>
> ​Yes, you can include interaction terms in the design formula. If you 
> are using DESeq2 v1.2 you can pull out the effects by 'name' argument 
> to results(), using a name in resultsNames(dds). In DESeq2 >= 1.3​, I 
> have added instructions and examples to the ?results manual page, but 
> still need to add a section to the vignette on interaction terms.
>
Cool!
Thanks a lot,
Claudia

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