When I am reading papers that compares bulk RNA sequencing and single-cell RNA sequencing, we often see papers describe bulk RNA seq measures the average cell expression.
For example, in this paper Single-Cell RNA-Seq Technologies and Related Computational Data Analysis
bulk RNA-seq mainly reflects the averaged gene expression across thousands of cells
And this paper A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
the averaging that occurs in pooling large numbers of cells does not allow detailed assessment of the fundamental biological unit—the cell—or the individual nuclei that package the genome
And this paper Differential expression analyses for single-cell RNA-Seq: old questions on new data
Standard RNA-Seq experiments need millions of cells for sequencing [2,3], and therefore can only get averaged measurements of gene expressions of the cells sequenced.
My question is, when we perform the bulk RNA seq and calculates parameters like TPM, we don't actually divide the total number of mRNA transcripts with the number of cells (I think sometimes we don't even have an accurate number on the number of cells that we used in bulk RNA seq), we simply normalise it with the transcript length and count.
Therefore, if we DID NOT divide the number of transcripts with the total cell number, how are we measuring the average of expression, but not the total expression?
Or in other words, what is the "average expression" referring to? Average to what?