Fig. 1: Comparison between network inference with bulk RNA-seq and scRNA-seq.
From: Single-cell network biology for resolving cellular heterogeneity in human diseases
a Network inference with bulk RNA-seq analysis. Multiple tissue samples and sequencing are required to produce a gene-by-sample matrix. Correlation between genes can be detected from both expression variation across cell states and variation of cell-type composition across tissue samples. The resultant coregulatory network is mostly composed of cell-type composition-induced coexpression. b Network inference with scRNA-seq. A single tissue sample is disassociated into cells that are individually analyzed in parallel. Clustering of the cells along with dimension reduction enables the identification of cell populations for each of the major cell types. Using a gene-by-cell count matrix for each cell type, we can infer networks mainly composed of within-cell coregulatory links.
