Table 1:
Precision and recall of detecting RCPs on simulated data.
| RCPs | Major cell types | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cell types | RCP-A | RCP-B | Progenitor | Precursor-A | Precursor B | Mature-A | Mature-B | |||||||
| Abundance | 2.55% | 2.68% | 21.23% | 22.43% | 19.83% | 16.73% | 15.30% | |||||||
| Precision/recall | Pre. | Rec. | Pre. | Rec. | Pre. | Rec. | Pre. | Rec. | Pre. | Rec. | Pre. | Rec. | Pre. | Rec. |
| SCMER | 0.82 | 0.68 | 0.87 | 0.67 | 0.97 | 0.96 | 0.95 | 0.96 | 0.94 | 0.94 | 0.95 | 0.96 | 0.94 | 0.93 |
| DE analysis | 0.61 | 0.34 | 0.73 | 0.40 | 0.94 | 0.95 | 0.94 | 0.93 | 0.95 | 0.94 | 0.94 | 0.95 | 0.95 | 0.96 |
| Correlation | 0.48 | 0.36 | 0.43 | 0.28 | 0.91 | 0.96 | 0.76 | 0.67 | 0.76 | 0.67 | 0.88 | 0.95 | 0.88 | 0.92 |
Listed are precision (pre.) and recall (rec.) using a K-NN classifier for one cell type at a time using feature selected by SCMER, DE analysis using known cell types, and correlation using pseudo-time (Supplementary Note 2). Higher is better for both metrics. Also shown are the abundances of the cell types.