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. 2021 Jul;31(7):1296–1311. doi: 10.1101/gr.265595.120

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© 2021 Gao et al.; Published by Cold Spring Harbor Laboratory Press

This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.

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Figure 6. — Comparison of BITFAM with other methods. (A) Clustering performance comparison between BITFAM + Louvain, SCENIC + Louvain, and three traditional clustering methods applied to the Tabula Muris lung, heart, and brain data sets. The clustering quality was evaluated based on three metrics: adjusted Rand index (ARI), Rand index (RI), and normalized mutual information (NMI). (B) Performance of BITFAM and SCENIC in the CRISPRi data. (C) The running time of BITFAM and SCENIC on the Tabula Muris lung data set and the CRISPRi data set.