| First Author | Frishberg A | Year | 2019 |
| Journal | Nat Methods | Volume | 16 |
| Issue | 4 | Pages | 327-332 |
| PubMed ID | 30886410 | Mgi Jnum | J:356078 |
| Mgi Id | MGI:7762170 | Doi | 10.1038/s41592-019-0355-5 |
| Citation | Frishberg A, et al. (2019) Cell composition analysis of bulk genomics using single-cell data. Nat Methods 16(4):327-332 |
| abstractText | Single-cell RNA sequencing (scRNA-seq) is a rich resource of cellular heterogeneity, opening new avenues in the study of complex tissues. We introduce Cell Population Mapping (CPM), a deconvolution algorithm in which reference scRNA-seq profiles are leveraged to infer the composition of cell types and states from bulk transcriptome data ('scBio' CRAN R-package). Analysis of individual variations in lungs of influenza-virus-infected mice reveals that the relationship between cell abundance and clinical symptoms is a cell-state-specific property that varies gradually along the continuum of cell-activation states. The gradual change is confirmed in subsequent experiments and is further explained by a mathematical model in which clinical outcomes relate to cell-state dynamics along the activation process. Our results demonstrate the power of CPM in reconstructing the continuous spectrum of cell states within heterogeneous tissues. |
