Creating a Single-Cell Signature Matrix for Bulk RNA-seq Deconvolution

Question

[Lloyd98]

Hello all,

I have performed deconvolution of bulk RNA-seq data using tools such as CIBERSORT, EPIC, quanTIseq, and xCell to estimate the proportions of different cell types in my samples. Additionally, I have single-cell RNA-seq data with already identified clusters. My goal is to use these single-cell clusters as a reference to perform a more precise deconvolution of my bulk RNA-seq data, in order to characterize the cell types present in my samples more accurately. As a novice in single-cell data analysis, I would like to know how to generate a gene signature matrix from my single-cell data that could serve as a reference for bulk data deconvolution. Specifically:

1. What approach do you recommend for creating a robust signature matrix from single-cell clusters?
2. Are there any specific R/Python tools or packages you would recommend for this task?
3. What precautions should I take to ensure that my signature matrix is of good quality and suitable for deconvolution?

Thank you in advance for your advice and recommendations.

[Papyrus]

There are packages such as the R package MuSiC that can do the deconvolution if you simply input the single cell and the bulk gene expression matrices. It automates the gene selection for you.