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uguy
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@uguy-15219
Last seen 6.7 years ago
Hi,
I am analyzing RNAseq data of two experiments with multiple time points and their own control condition. These two experiments were sequenced in two separate runs. I wonder if I can merged the two raw counts tables and normalize them using the DESeq2 size factors method, or do I need to normalized each table separately with DESeq2 package and then use a quantile normalization on the two datasets ?
Thanks !
Thanks for answering me. There is two type of acclimated cells that were exposed to several stresses. The two types of acclimation were separated for sequencing step in two runs. The time points are not the same accross experiments and there is three biological replicates for each time point.
And yes, I want to analyze the normalized counts together but also compare the differential expression (log2FC) accross stress conditions and acclimation conditions.
Here the experiment design:
"The time points are not the same across experiments"
Because the time points weren't the same across experiments, and you have replicates for each time point, I'd suggest analyzing the two datasets separately. This makes sense for a number of reasons.
I only asked about the design, because if you had the same time points, and no replicates, then you would want to combine them, to provide some amount of replication.
I understand your point. But I then want to use a method that takes reads counts as input and I wonder if it's a problem that the sequencing depth is not normalized between the two datasets. (no comparison against the control reads counts).
Can you name a specific comparison you want to make that goes across the runs? You can’t directly compare across batches because you can’t separate the biological differences from technical. But it is possible to compare LFC across (comparing each to control first).