Skip to main content
Fig. 5 | BMC Bioinformatics

Fig. 5

From: ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data

Fig. 5

Evaluation on a real Hi-C dataset. a The workflow of the iterative application of ClusterTAD. b The average size of TADs identified for the mouse embryonic stem cell by three rounds of clustering of ClusterTAD (ClusterTAD_1, ClusterTAD_2, and ClusterTAD_3). c The average size of TADs identified for the mouse cortex cell by three rounds of clustering of ClusterTAD. d The box plot of the quality scores of TADs extracted for the mouse embryonic stem cell by the three rounds of clustering of ClusterTAD. e The box plot of the quality scores of TADs extracted for the mouse Cortex cell for the different clustering operations performed by ClusterTAD

Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us