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3DeFDR: statistical methods for identifying cell type-specific looping interactions in 5C and Hi-C data.

Lindsey R Fernandez1, Thomas G Gilgenast1, Jennifer E Phillips-Cremins2,3,4

  • 1Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Genome Biology
|August 30, 2020
PubMed
Summary

Understanding how long-range chromatin loops change is crucial. We developed 3DeFDR, a statistical tool to identify dynamic loops in Chromosome-Conformation-Capture-Carbon-Copy (5C) and Hi-C data across conditions.

Keywords:
3D chromatin looping interactionsChromatin dynamicsChromosome-conformation-captureEpigeneticsFalse discovery rateHigher-order chromatin architecture

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Area of Science:

  • Chromatin biology
  • Genomics
  • Computational biology

Background:

  • Assessing changes in long-range chromatin looping interactions across diverse biological contexts (development, genetics, drugs, disease) remains a challenge.
  • There is a need for robust computational methods to analyze cell type-specific loops in multiple experimental conditions.

Purpose of the Study:

  • To introduce 3DeFDR, a statistical tool for classifying dynamic loops from high-resolution 3D genome structure data.
  • To provide a framework and open-source tools for sensitive detection of cell type-specific loops across various cellular conditions.

Main Methods:

  • Utilized Chromosome-Conformation-Capture-Carbon-Copy (5C) and Hi-C data.
  • Developed and applied a statistical approach (3DeFDR) for loop classification.
  • Leveraged computational analysis of high-resolution genomic interaction data.

Main Results:

  • Demonstrated the effectiveness of 3DeFDR in classifying dynamic loops.
  • Provided open-source coding libraries for analyzing 5C and Hi-C data.
  • Enabled sensitive detection of cell type-specific loops across multiple conditions.

Conclusions:

  • 3DeFDR offers a simple and effective statistical solution for analyzing dynamic chromatin loops.
  • The developed framework facilitates the study of 3D genome organization changes in various biological scenarios.
  • Open-source tools enable broader application in chromatin biology research.