Applying BERMUDA to bulk RNA seq

txWang / BERMUDA

BERMUDA (Batch Effect ReMoval Using Deep Autoencoders) is a novel transfer-learning-based method for batch correction in scRNA-seq data.

MIT License

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Applying BERMUDA to bulk RNA seq #10

Open mdanb opened 3 years ago

mdanb commented 3 years ago

I have a relatively large bulk RNA seq dataset (~ 1300 samples, from ~70 experiments) that I'd like to correct for significant batch effects. Is it valid/possible to apply BERMUDA to my dataset? Instead of clustering cells of patients, I'd just cluster patients to remove batch effects. Is this valid?

txWang commented 3 years ago

While the use of domain adaptation in BERMUDA does not specifically restrict to single-cell data, the whole workflow of BERMUDA also depends on Seurat and Metaneighbor, which are designed for single-cell data. We also only applied BERMUDA in single-cell data in our paper. Therefore, I would suggest using the batch correction method designed for bulk data for your dataset.