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Fig. 7 | Genome Biology

Fig. 7

From: Assessment of computational methods for the analysis of single-cell ATAC-seq data

Fig. 7

Aggregate benchmark results. a For each method, the rank based on the best-performing clustering method is measured for each metric (e.g., ARI, AMI, H, or RAGI). The average metric ranks for each dataset were used to calculate a performance score for each method. Each method was then assigned a cumulative average score based on its performance across all datasets. The asterisk indicates a downsampled dataset of the indicated original dataset. b For methods that specify an end-to-end clustering pipeline, average rank and cumulative average scores for each method were calculated as in a. c Plot of running time against performance for each method. Cumulative average scores, which were calculated in part a are shown on the x-axis, and the average running time across the three real datasets (Buenrostro2018, 10X PBMCs, and downsampled sci-ATAC-seq mouse) is shown on the y-axis

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