Fig. 21
From: A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Efficacy and efficiency of the 14 batch-effect correction methods. a Rank sum of the assessment metrics. Methods were ranked based on each of the ASW, ARI, LISI, and kBET metrics, and the rankings were then combined across all metrics using the rank sum approach. The height of the ridgelines represents the rank sum scores across different datasets, with a lower rank sum score denoting better performance. Methods are ordered from bottom to top by increasing sum of rank scores across all ten datasets. Thus, methods appearing at the bottom are the best. b Memory usage of ten methods on dataset 8. c Runtime of 14 methods on ten datasets. Color represents log10(time in seconds), node size represents log10(cell number)