Methods to Assess the Reproducibility and Similarity of Hi-C Data

Tao Yang, Xi He, Lin An, Qunhua Li

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages17-37
Number of pages21
DOIs
StatePublished - 2022

Publication series

NameMethods in Molecular Biology
Volume2301
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

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