DESeq2 for longitudinal data
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@95c80da2
Last seen 29 days ago
United States

Hi Michael,

I have a couple of questions about DESeq2.

1) Could we use it for repeated measured outcome? Do we only need to add a time variable in the design as below?

dds <- DESeqDataSetFromMatrix(countData = cts, colData = coldata, design= ~ time + condition)

2) For the condition variable, could we use continuous outcome here? Or we can only use the factor variable for condition due to NB distribution behind the DESeq2?

3) I saw you mentioned that DESeq2 only works for replicates data, here replicates data means biological replicate or technical replicate?

Thanks in advance.

Elena

DESeq2 • 147 views
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swbarnes2 ▴ 800
@swbarnes2-14086
Last seen 7 hours ago
San Diego

You can use continuous variables. Just make sure you don't convert them to factors when importing. When using continuous variables, you get not so much a fold change, but the slope of the line of logged counts versus the continuous variable.

Biological replicates. Technical replicates should be merged. You can't make biological replicates by taking one library and running it twice

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And regarding (1), yes you can use this design for changes over time and condition. There is an example also in the workflow (linked from vignette abstract).

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