Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data

Abstract

Understanding how chromosomes fold provides insights into the transcription regulation, hence, the functional state of the cell. Using the next generation sequencing technology, the recently developed Hi-C approach enables a global view of spatial chromatin organization in the nucleus, which substantially expands our knowledge about genome organization and function. However, due to multiple layers of biases, noises and uncertainties buried in the protocol of Hi-C experiments, analyzing and interpreting Hi-C data poses great challenges, and requires novel statistical methods to be developed. This article provides an overview of recent Hi-C studies and their impacts on biomedical research, describes major challenges in statistical analysis of Hi-C data, and discusses some perspectives for future research.

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Graphical abstract

References

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ACKNOWLEDGEMENTS

This research was supported in part by the NSF grant (No. DMS-1120368) and NIH grants (Nos. R01-HG02518-02 and R01-HG005119).

CONFLICT OF INTEREST

The authors Ming Hu, Ke Deng, Zhaohui Qin and Jun S. Liu declare that they have no conflict of interests.

RIGHTS & PERMISSIONS

2013 Higher Education Press and Springer-Verlag Berlin Heidelberg