Hello all,

recently, I had been trying to integrate bulk RNAseq data into single-cell data where I treat each sample in my bulk RNAseq data as a single cell and integrate it into the single-cell data based on the overlap of genes from both datasets. The goal was to see how the new integrated "cells" cluster on a UMAP. To match the distribution of the single-cell data, I had scaled and downsampled the bulk RNAseq data. But they don't appear to cluster as hypothesized. Is there a way to integrate bulk and single-cell data together to be able to allow them to cluster on the UMAP? Specific normalization or scaling techniques?

I've tried the cross-platform deconvolution approach in cibersortx, but was not convinced with the results.

Thank you!