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An improved 3DMax algorithm to reconstruct the three-dimensional structure of the chromosome

Liwei Liu; Huili Yao

2020-07-09 bioinformatics
10.1101/2020.07.09.195693 bioRxiv
Show abstract

In recent years, with the development of high-throughput chromosome conformation capture (Hi-C) technology and the reduction of high-throughput sequencing cost, the data volume of whole-genome interaction has increased rapidly, and the resolution of interaction map keeps improving. Great progress has been made in the research of 3D structure modeling of chromosomes and genomes. Several methods have been proposed to construct the chromosome structure from chromosome conformation capture data. Based on the Hi-C data, this paper analyses the relevant literature of chromosome 3D structure reconstruction and it summarizes the principle of 3DMAX, which is a classical algorithm to construct the 3D structure of a chromosome. In this paper, we introduce a new gradient ascent optimization algorithm called XNadam that is a variant of Nadam optimization method. When XNadam is applied to 3DMax algorithm, the performance of 3DMax algorithm can be improved, which can be used to predict the three-dimensional structure of a chromosome.Author summary The exploration of the three-dimensional structure of chromosomes has gradually become a necessary means to understand the relationship between genome function and gene regulation. An important problem in the construction of three-dimensional model is how to use the interaction map. Usually, the interaction frequency can be transformed into the spatial distance according to the deterministic or non-deterministic function relationship, and the interaction frequency can be weighted as weight in the objective function of the optimization problem. When the frequency of interaction is weighted as weight in the objective function of the optimization problem, what kind of optimization method is used to optimize the objective function is the problem we consider. In order to solve this problem, we provide an improved stochastic gradient ascent optimization algorithm(XNadam). The XNadam optimization algorithm combined with maximum likelihood algorithm is applied to high resolution Hi-C data set to infer 3D chromosome structure.View Full Text

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