This is the official repository to reproduce all figures from the Cell-ID manuscript, Cortal et al. Nature Biotechnology 2021: https://rdcu.be/cjFWE. To download Cell-ID please refer to https://github.com/RausellLab/CelliD. The CellID legacy branch on github was used for manuscript results. All input data are downloaded through the code herein.
- Supplementary figures 1 and 2
SupNote3 Capacity of Cell-ID to identify well-established cell types on the basis of reference marker lists.
- Figure 2
- Supplementary figures 3, 4
Supplementary Note 4. Capacity of Cell-ID to match cells of analogous cell types across independent scRNAseq datasets from the same tissue of origin, within and across species.
- Figure 3
- Supplementary figures 5, 6, 7, 8
Supplementary Note 5. Capacity of Cell-ID to match cell types across independent scRNA-seq datasets from different tissues of origin
- Supplementary Figure 9
Supplementary Note 6. Capacity of Cell-ID to match cell types across independent datasets from different single-cell omics technologies: scRNAseq and scATACseq
- Supplementary Figures 10, 11, 12
Supplementary Note 7. Influence of the cell heterogeneity background in the assessment of Cell-ID gene signatures and its impact in label transferring performance across independent datasets.
- Supplementary Table 12
- Supplementary Figure 13
Supplementary Note 9. Novel visualization options for enhanced biological interpretation of cell heterogeneity
- Supplementary Figure 14