greenelab / greenelab/buddi_analysis
Why we have both pseudobulk and real bulk data?
- Dominant language
- Jupyter Notebook
- Stars
- 3
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Description
Both pseudobulk and real bulk data are combined to train the BuDDI model specifically the Variational Autoencoder (VAE).
**In my understanding:**
By simulating **pseudobulks** with random cell-type proportions, BuDDI learns to disentangle various sources of variation in the pseudobulk data, which may include cell type-specific gene expression patterns and other latent factors and also to break the dependence between cell-type proportions and other sources of variation.
**Real bulk** data, which comes from traditional bulk RNA-seq experiments, is integrated with pseudobulk data during the training phase. **Real bulk** data serves as a bridge between the simulated pseudobulk data and the actual biological data. It brings real-world variability, conditions, and responses into the training process.
Contributor guide
No contributing guide indexed for this repository
Assessment
This issue has not been assessed yet.