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Fig. 4 | BMC Bioinformatics

Fig. 4

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

Fig. 4

– The visualization of the TADs extracted for one chromosome contact map in the simulated dataset. Rows a to g represents the TADs extracted for K = 4, K = 5 and K = 6 (from left, middle to right) for the following combinations of clustering algorithms and distance metrics: (a) HC-eulcidean, (b) KM- eulidean, (c) HC-pearson, (d) KM-pearson, (e) HC-cityblock, (f) KM-cityblock, and (g) EM. HC denotes the hierarchical clustering algorithm, KM the K-means algorithm, and EM the expectation maximization algorithm. HC-euclidean denotes the combination of the hierarchical clustering algorithm with the Euclidean distance metric. The left column visualizes the TADs extracted by the seven algorithms when K = 4, the middle columns the TADs extracted when K = 5, and the right column the TADs extracted when K = 6. A TAD region identified on each contact heatmap is denoted by a blue square within the blue dots along its diagonal. The blue dots represent the boundary of a TAD region. The white squares along the diagonals are unrecognized TADs

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