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CHROMSTRUCT 4: A Python Code to Estimate the Chromatin Structure from Hi-C Data
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DOI：10.1109/TCBB.2018.2838669.png)
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Abstract
En 中文
A method and a stand-alone Python code to estimate the 3D chromatin structure from chromosome conformation capture data are presented. The method is based on a multiresolution, modified-bead-chain chromatin model, evolved through quaternion operators in a Monte Carlo sampling. The solution space to be sampled is generated by a score function with a data-fit part and a constraint part where the available prior knowledge is implicitly coded. The final solution is a set of 3D configurations that are compatible with both the data and the prior knowledge. The iterative code, provided here as additional material, is equipped with a graphical user interface and stores its results in standard-format files for 3D visualization. We describe the mathematical-computational aspects of the method and explain the details of the code. Some experimental results are reported, with a demonstration of their fit to the data.
Keywords:
Chromosome conformation capture
chromatin configuration
Bayesian estimation
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ShareSaveMapping networks of physical interactions between genomic elements using 5C technology.png)
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NATURE PROTOCOLSIF16
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ShareSaveGenome structure determination via 3C-based data integration by the Integrative Modeling PlatformMETHODS
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