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Capturing Chromosome Conformation Across Length Scales
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Chromosome Conformation Capture on Chip (4C): Data Processing.

Benjamin Leblanc1,2, Itys Comet3,4, Frédéric Bantignies3

  • 1Institut de Génétique Humaine, CNRS UPR 1142, 141, rue de la Cardonille, 34396, Montpellier, France. benjamin.leblanc@bric.ku.dk.

Methods in Molecular Biology (Clifton, N.J.)
|September 24, 2016
PubMed
Summary
This summary is machine-generated.

This study presents a data analysis protocol for 4C (Circular Chromosome Conformation Capture) experiments. The methods, implemented in the R package MRA.TA, enhance the detection of chromatin contacts and are applicable to ChIP-on-chip data.

Keywords:
4CBioinformaticsChromatinChromosome Conformation CaptureEpigeneticsMicroarrayMulti-resolution statisticsNormalizationPolycomb

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • 4C (Circular Chromosome Conformation Capture) methods reveal interactions between regulatory elements and chromatin structures.
  • Understanding these interactions is crucial for deciphering gene regulation.
  • Previous studies have utilized 4C for large-scale chromatin interaction profiling.

Purpose of the Study:

  • To describe an updated protocol for analyzing microarray-based 4C experiment data.
  • To present methods for data preparation, normalization, probe selection, and contact detection.
  • To demonstrate the protocol's versatility and the importance of data processing in 4C.

Main Methods:

  • The protocol details data preparation and normalization steps.
  • It includes multi-resolution detection of regions with enriched chromatin contacts.
  • Methods are implemented in the R package MRA.TA (Multi-Resolution Analyses on Tiling Array data).

Main Results:

  • The protocol was successfully reanalyzed on two independent mouse datasets.
  • It illustrates the versatility of the data processing pipeline.
  • The importance of rigorous data processing in 4C analysis was highlighted.

Conclusions:

  • The presented protocol offers a robust framework for analyzing 4C data.
  • The MRA.TA package facilitates the detection of chromatin contacts.
  • These methods can also be applied to analyze ChIP-on-chip data for histone marks.