Table 1.

Overview of computational tools for predicting 3D chromatin structure from scHi-C contact data. For each method, we provide details on the primary reconstruction technique, the implementation programming language, the single-cell datasets utilized in the original study, and links to the corresponding source code.

Method name	Technique	Language	Single cell dataset	Source code link
Nagano et al. 2013 [17]	Simulated Annealing	—	Nagano 2013	—
MBO [37]	Gradient Descent	Matlab	Nagano 2013	http://folk.uio.no/jonaspau/mbo/
ISDHi-C [38]	Hamiltonian Monte Carlo	Python	Nagano 2013	https://github.com/michaelhabeck/isdhic
RPR [39]	Recurrence Plot-based Reconstruction	Matlab	Nagano 2013	—
NucDynamics [28]	Simulated Annealing	Python	Stevens 2017	https://github.com/tjs23/nuc_dynamics
SIMBA3D [40]	Gradient Descent	Python	Stevens 2017	https://github.com/nerettilab/SIMBA3D
SCL [41]	Metropolis-Hastings and Simulated Annealing	C++	Nagano 2013, Stevens 2017, Tan 2018	http://dna.cs.miami.edu/SCL/
Wetterman et al. 2020 [13]	Molecular Dynamics	Python	Stevens 2017	—
Si-C [42]	Gradient Descent	C++	Stevens 2017	https://github.com/TheMengLab/Si-C/
LJ3D [43]	Metropolis-Hastings and Simulated Annealing	C++	Bonev 2017	http://dna.cs.miami.edu/LJ3D
DPDChrom [44]	Dissipative Particle Dynamics	Python	Flyamer 2017, Gassler 2017	https://github.com/polly-code/DPDchrom
Rothörl et al. 2023 [14]	Molecular Dynamics	Python	Tan 2018, Tan 2019	https://gitlab.rlp.net/3d-diploid-chromatin/simulation-code/