How to compare the human single cell RNA-seq clusters with mouse bulk RNA-seq

Question

[saigro16]

Hello,

I have 13 clusters from human single-cell RNA-seq analysis and I also have mouse RNA-seq data. I would like to compare the 13 clusters from single-cell data (Human) with mouse bulk RNA-Seq. I am thinking the following

Step1) First, convert the mouse genes to human genes Step2) Overlap these converted genes with the human genes from clusters Step3)Take the overlapped genes and their log2 fold changes from both human (single-cell RNA-seq) and mouse (bulk RNA-seq) Step4)Compute the Pearson correlations between the values (obtained from step3).

Is this the correct way to go about it.

Please guide me if this correct way to go about it. It would be great if some point out to literature as an example.

Thank you, Sai

[ATpoint]

Which question do you want to answer? Compare is a vague term. Comparing fold changes across different species and technologies is most likely not meaningful. Bulk RNA-seq and single-cell data have largely different effect sizes due to the sparse nature of single-cell data even when comparing within the same species. Maybe something more robust like Spearman correlation which focuses on ranks rather than linear relationships or a GSEA-like analysis with a subset of genes, but as said, for this we have to know what you try to answer.

[saigro16]

Thank you for reply. My main question is how well human single-cell data correlates with bulk RNA-seq from the mouse. Thank you for your suggestion on the Spearman correlation.

[ajay nair]

Conversion from mouse to human step makes sense. For the next part, here is a comparison of genes expressed in single cell and bulk RNAseq datasets.