How to find significant genes in one-group samples in RNA-seq data?

Question

[jabbari.parnian]

Hi everyone,

I have log2 transformed TPM data of a single-cell RNA-seq experiment. I have selected data representing a specific cell type. As all my columns represent the same cell type, basically I can't use the differential expression analyses to get the significant genes. How can I find genes that are important in this type of cells? I was thinking of evaluating the mean expression level for each gene among the cells (columns) and then sort them based on the mean. But this is just something I came up with, I wanna know if there is any globally-accepted way to find significant genes in this situation. Or when I have the RNA-seq results for different samples of the same tissue?

Thanks

[ATpoint]

I suggest you extensively read manuals and vignettes of prominent scRNA-seq tools such as Seurat, scater and scran plus the Bioconductor single-cell workflow: https://osca.bioconductor.org/

This will give you a background and explain basic concepts.