Pseudo-bulk DEG analysis with Multi-tissue in scRNA-seq
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12 weeks ago

Hi all,

I have 4 datasets (Brain region A (Control & Disease), Brain region B (Control & Disease)) and performed scRNA-seq by integrating all data.

And I want to compare Disease and Control in each brain region using pseudo-bulk DEG analysis. (ex. Region A Disease vs Region A Control)

Even if area A and area B are integrated, is it ok to perform DEG analysis for each brain region with the code below?

dds <- DESeqDataSetFromMatrix(cluster_counts,
design = ~ group_id)
contrast <- c("group_id", "Region A Disease", "Region A Control")
### or contrast <- c("group_id", "Region B Disease", "Region B Control")
res <- results(dds,
contrast = contrast,
alpha = 0.05)


group_id contains 'Region A Disease', 'Region A Control', 'Region B Disease', and 'Region B Control'.

Or should I do it another way?

Joonhong

scRNA-seq Pseudo-bulk Seurat DEG DESeq2 • 592 views
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Are these regions from the same experiment or is this independent studies?

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Regions A and B are from the same patient (individual).

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So then it should be possible to quantitatively compare them. But you mention pseudobulk...if it is the same patient, isn't it then 1 vs 1 so no replication as required for pseudobulks?

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I have a total 24 samples from 12 individual (6 Region A Disease, 6 Region A Control, 6 Region B Disease and 6 Region B Control).

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Then it should be fine. I usually do pseudobulk in these situations to avoid overly much (but meaningless) statistical power due to the large number of cells, and rather focus on the meaningful biological replication which is the individuals.

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