EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient

Author:

Wang Xiao1,Gu Wei-Cheng1,Li Jie1,Ma Bin-Guang1ORCID

Affiliation:

1. Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University , Wuhan 430070, China

Abstract

Abstract Motivation Reconstruction of 3D structure models is of great importance for the study of chromosome function. Software tools for this task are highly needed. Results We present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. As an update of our previous EVR algorithm, EVRC now can deal with both single and multiple chromosomes in structure modeling. To evaluate the effectiveness and accuracy of the EVRC algorithm, we applied it to simulation datasets and real Hi-C datasets. The results show that the reconstructed structures have high similarity to the original/real structures, indicating the effectiveness and robustness of the EVRC algorithm. Furthermore, we applied the algorithm to the 3D conformation reconstruction of the wild-type and mutant Arabidopsis thaliana chromosomes and demonstrated the differences in structural characteristics between different chromosomes. We also accurately showed the conformational change in the centromere region of the mutant compared with the wild-type of Arabidopsis chromosome 1. Our EVRC algorithm is a valuable software tool for the field of chromatin structure reconstruction, and holds great promise for advancing our understanding on the chromosome functions. Availability and implementation The software is available at https://github.com/mbglab/EVRC.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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