Table 1 Application of high-throughput single-cell and spatial technologies in the liver

ScRNA-seq

Transcriptomic

Applicable for fresh tissue samples only and artificial transcriptional stress responses

[69]

SnRNA-seq

Transcriptomic

Application to fresh and frozen samples, particularly those that are difficult to dissociate into single-cell suspensions. Can provide data on difficult to isolate cells with some loss of transcriptional depth and the cytoplasmic RNA fraction

[16]

Spatial transcriptomics

Transcriptomic

Used to eliminate dependency on landmark genes and adherent cells, and provide spatial annotation of structures

[75, 76]

Sc ATAC-seq

Epigenetic

Unbiased detection of epigenetic landscape across the human genome. Capture of early lineage-determining epigenetic features may allow for a higher resolution when identifying cell subsets than with transcriptomic data

[62]

Single-cell immune profiling

Transcriptomic and TCR sequencing

Enables annotation of invariant T-cells, tracking the expansion of T- and B-cells and the linking of antigen receptor sequences to lymphocyte transcriptome

[190]

Sc MT-seq

Multiomic: epigenetic and transcriptomic

Used to detect transcriptome, methylome, and single nucleotide polymorphism information within single cells to dissect the mechanisms of epigenetic gene regulation

[63, 64]

Sc CITE-seq

Multiomic: transcriptomic and proteomic

Used to provide detailed characterization of cellular phenotypes and be readily scale as the throughput of single-cell sequencing approaches increase

[65]

Single-microbe genomics

Genomic

Contribute high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution

[67]