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. Author manuscript; available in PMC: 2018 Jan 11.
Published in final edited form as: Nat Rev Mol Cell Biol. 2016 Sep 1;17(12):743–755. doi: 10.1038/nrm.2016.104

Table 4.

Approaches for the analysis of global chromatin conformation

Approach Objective Pros Cons Refs
PCA Detect nuclear compartments Easy to implement; straightforward interpretation First eigenvector may not work; arbitrary compartment assigning 22
DI/HMM Detect TADs Model the change of upstream and downstream interaction bias Heuristic tuning parameters 6
Arrowhead Detect TADs High computational efficiency with dynamic programming Heuristic tuning parameters 27
Insulation score Detect TADs Robust to different sequencing depth; can detect dynamics of TAD boundaries Heuristic tuning parameters 90
Armatus Detect TADs TAD calling robust in different resolutions Fails to provide uncertainty in TAD calling 88
HiCseg Detect TADs Models the uncertainty in Hi-C data Fails to detect multi-level TADs 89

DI, directionality index; HMM, hidden Markov model; PCA, principle component analysis; TAD, topologically associating domain.