mbkmeans: Fast clustering for single cell data using mini-batch k-means
Fig 2
The accuracy of mbkmeans depends on batch size.
Performance evaluation (y-axis) with (A) adjusted Rand index (ARI) and (B) within clusters sum of squares (WCSS) for increasing batch sizes ranging from 75 to 1000 cells (x-axis) using simulated gene expression data (G = 1000) with a fixed k = 3 true centroids with three sizes of datasets (N = 5000, 10000, 25000). (C) WCSS (y-axis) for increasing batch sizes (x-axis) using real scRNA-seq gene expression data from 10X Genomics and k = 15 for both algorithms. ARI and WCSS is reported as an average across 50 runs.