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Methods to Assess the Reproducibility and Similarity of Hi-C Data
1Bioinformatics and Genomics Program, Pennsylvania State University, University Park, PA, USA.
Methods in Molecular Biology (Clifton, N.J.)
|August 20, 2021
Abstract:
Hi-C experiments are costly to perform and involve multiple complex experimental steps. Reproducibility of Hi-C data is essential for ensuring the validity of the scientific conclusions drawn from the data. In this chapter, we describe several recently developed computational methods for assessing reproducibility of Hi-C replicate experiments. These methods can also be used to assess the similarity between any two Hi-C samples.

