Abstract
Deconvolution of cell mixtures in “bulk” transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal “gold standard” datasets for evaluating deconvolution methods.
Original language | English (US) |
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Article number | 288 |
Journal | Genome Biology |
Volume | 24 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Externally published | Yes |
Keywords
- Cell sizes
- Deconvolution
- Single-cell RNA-sequencing
- Single-nucleus RNA-sequencing
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Genetics
- Cell Biology