Complicated paired multi factor design
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@vladimir-krasikov-5097
Last seen 4.4 years ago

Hello Experts!

I encountered somewhat difficult experimental design.

Briefly, blood cells from 2 individuals where treated with 2 different compounds (this compounds supposedly have to force cells switch their type from Phen1 to Phen2). Afterwards cells of different phenotypes were physically separated and sequenced. So this groups are paired, as well as each Treatment paired as applied to the same individual. So design is kind of paired in two-dimensions.

exp.design file:

Sample ind phenotype treatment
sample1 1 Phen1 Comp1
sample2 1 Phen1 Comp2
sample3 2 Phen1 Comp1
sample4 2 Phen1 Comp2
sample5 1 Phen2 Comp1
sample6 1 Phen2 Comp2
sample7 2 Phen2 Comp1
sample8 2 Phen2 Comp2

 

 

 

 

 

 

 

I found nothing better than to create combined Phenotype and Treatment into one Group (as suggested in edgeR):

Ind <- factor(exp.design$ind)

Phenotype <- factor(exp.design$phenotype, levels = c('Phen1', 'Phen2'))

Treatment <- factor(exp.design$treatment, levels = c('Comp1', 'Comp2'))

Group <- factor(paste(exp.design$phenotype, exp.design$treatment, '.',

                       levels = c('Phen1.Comp1', 'Phen1.Comp2', 'Phen2.Comp1', 'Phen2.Comp2'))

Exp.Design <- data.frame(Group, Ind)

and finally 

model.matrix( ~ Ind + Group, Exp.Design) to account for paired samples.

I am interested in all types of comparisons:

Phen1.Comp1 vs Phen1.Comp2 - difference in treatments in Phen1

Phen2.Comp1 vs Phen2.Comp2 - difference in treatments in Phen2

Phen1.Comp1 vs Phen2.Comp1 - difference in Phenotypes caused by Comp1

Phen1.Comp2 vs Phen2.Comp2 - difference in Phenotypes caused by Comp2

 

Is this approach valid?

Any suggestions and remarks are welcome

deseq2 multiple factor design • 1.4k views
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Now if I want to add to the experiment another compound (Comp3), how can I extract genes responded differently to the Comp2 and Comp3 related to the Comp1 in first Phenotype?

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results(dds, contrast=c("group","Phen1.Comp3","Phen1.Comp2"))

This has been asked a few times on the support site, but it would be hard to search for. The Comp1 as baseline for the fold change drops out when you compare Comp3 and Comp2:

(Comp3/Comp1) / (Comp2/Comp1) = Comp3/Comp2

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@mikelove
Last seen 24 minutes ago
United States

hi,

You never mention what kind of comparisons you are interested in. That will help inform the easiest way to set up design and extract results.

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I updated initial post to reflect what comparisons I am interested in

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In that case your design is the right one, you can just use:

design(dds) <-  ~ Ind + Group
dds <- DESeq(dds)
res <- results(dds, contrast=c("group","Phen1.Comp2","Phen1.Comp1"))

Note that I put Comp 2 first, then Comp 1. This will give you a comparison of 2 / 1, which is more typical than 1 / 2. Usually the first condition goes in the denominator, e.g. control which is taken as a "reference".

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Thanks a lot,

this is what I expected

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