Fig. 2
From: scPred: accurate supervised method for cell-type classification from single-cell RNA-seq data
Classification performance of tumor cells from gastric adenocarcinoma. scPred shows high prediction accuracy to classify tumor cells (0.979 (95% bootstrap CI 0.973–0.984) and non-tumor cells 0.974 (95% bootstrap CI 0.960–0.989). scPred outperforms predictions based on differentially expressed genes and per-cell mean of log2(CPM + 1) (prediction baseline). Ten bootstrap replicates were used to assess the prediction performance of all methods