Two factors design with DESEq2
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Last seen 4.1 years ago

Hi !

I have a RNAseq samples with this design:

sample genotype traitement

Col_1 wt normal

Col_2 wt normal

Col_3. wt normal

ColHS1 wt heatshock

ColHS2, wt heatshock

ColHS3 wt heatshock

hon4_1 hon4 normal

hon4_2 hon4 normal

hon4_3. hon4 normal

HS1 hon4 heatshock

HS2. hon4 heatshock

HS3. hon4 heatshock

I'm only interest to the genes differently expressed between my two genotypes, so I make this design :

design= ~ genotype + traitement

and then I retrieve my genes of interest in this way:

results(dds,contrast = c("genotype","hon4","wt"))

I the protocol good ?

I have 600 DEG with this method, are all the genes specific to the mutation ?

I mean, there are no genes in this list that could be related to the interaction with the treatment ?

Thank's by advance for you're help, I read help with ?results but I have a little trouble with the experimental designs

deseq2 genes expression • 550 views
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Last seen 1 day ago
United States

Your design assumes the treatment and genotype have independent multiplicative effects on expression. See the vignette section on interactions if you want to specify a different design.

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I had the interaction term on the design formula and so I have multiple set of genes:

DEG for the effect of treatment in my WT DEG for the effect of treatment in my mutant DEG for diff between WT and mutant (no treatment) DEG for diff between WT and mutant (treatment) and finally: DEG for the different response to treatment in genotypes (interaction)

I do not see how really how to approach this notion of interaction, I have around 500 genes deregulated for the interaction term, it would mean that the mutation has a greater impact in case of stress ? (because if I had 0 term, that would have meant that the mutation is independent of the treatment, If I understood correctly)

Thank you for you're time, I'm bioinformatic student and I really need to improve my statistics skills aha


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