Fig. 7
From: A comparison of automatic cell identification methods for single-cell RNA sequencing data
Computation time evaluation across different numbers of features, cells, and annotation levels. Line plots show a the median F1-score, b percentage of unlabeled cells, and e computation time of each classifier applied to the TM dataset with the top 100, 200, 500, 1000, 2000, 5000, and 19,791 (all) genes as input feature sets. Genes were ranked based on dropout-based feature selection. c The median F1-score, d percentage of unlabeled cells, and f computation time of each classifier applied to the downsampled TM datasets containing 463, 2280, 4553, 9099, 22,737, and 45,469 (all) cells. g The computation time of each classifier is plotted against the number of cell populations. Note that the y-axis is 100^x scaled in a and c and log-scaled in e–g. The x-axis is log-scaled in a–f