cudaMMC: GPU-enhanced multiscale Monte Carlo chromatin 3D modelling - Wlasnowolski, Michal; Grabowski, Pawel; Roszczyk, Damian; Kaczmarski, Krzysztof; Plewczynski, Dariusz (Bioinformatics (Oxford, England), 2023)
Abstract Motivation Investigating the 3D structure of chromatin provides new insights into transcriptional regulation. With the evolution of 3C next-generation sequencing methods like ChiA-PET and Hi-C, the surge in data volume has highlighted the need for more efficient chromatin spatial modelling algorithms. This study introduces the cudaMMC method, based on the Simulated Annealing Monte Carlo approach and enhanced by GPU-accelerated computing, to efficiently generate ensembles of chromatin 3D structures. Results The cudaMMC calculations demonstrate significantly faster performance with better stability compared to our previous method on the same workstation. cudaMMC also substantially reduces the computation time required for generating ensembles of large chromatin models, making it an invaluable tool for studying chromatin spatial conformation. Availability and implementation Open-source software and manual and sample data are freely available on https://github.com/SFGLab/cudaMMC.